Client device-implemented method and client device - Patents.com

Abstract

To provide a 3D data creation method capable of achieving simplification of device configuration, and a client device or a server.SOLUTION: A method according to an aspect is a method that is performed by a client device 902 with multiple sensors including a first sensor and a second sensor. The method includes the steps of: acquiring first sensor data using the first sensor; acquiring second sensor data using a second sensor; and creating combined data that includes 3D coordinate values and color information of multiple points. The 3D coordinate values are acquired from the first sensor data, and the color information is acquired from the second sensor data.SELECTED DRAWING: None

Description

[Technical field]

[0001] The present disclosure relates to a three-dimensional data creation method, a client device, and a server. [Background technology]

[0002] In the future, devices and services that utilize 3D data are expected to become widespread in a wide range of fields, such as computer vision for autonomous operation of automobiles or robots, map information, monitoring, infrastructure inspection, video distribution, etc. 3D data is acquired in various ways, such as distance sensors such as range finders, stereo cameras, or a combination of multiple monocular cameras.

[0003] One method of expressing three-dimensional data is a method called a point cloud, which represents the shape of a three-dimensional structure using a group of points in a three-dimensional space. In a point cloud, the positions and colors of the points are stored. Point clouds are expected to become the mainstream method of expressing three-dimensional data, but point clouds have a very large amount of data. Therefore, when storing or transmitting three-dimensional data, it is essential to compress the amount of data by encoding, just like two-dimensional video images (examples include MPEG-4 AVC or HEVC standardized by MPEG).

[0004] In addition, compression of point clouds is partially supported by public libraries (Point Cloud Library) that perform point cloud-related processing.

[0005] Furthermore, a technique is known that uses three-dimensional map data to search for and display facilities located around a vehicle (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0006] [Patent Document 1] International Publication No. 2014 / 020663 Summary of the Invention [Problem to be solved by the invention]

[0007] In such a three-dimensional data creation method for creating three-dimensional data, it is desirable to reduce the amount of data transmitted and to simplify the configuration of the device.

[0008] An object of the present disclosure is to provide a three-dimensional data creation method, client device, or server that can reduce the amount of data transmitted or simplify the device configuration. [Means for solving the problem]

[0009] A method according to one aspect of the present disclosure is a method implemented by a client device having a first sensor and a second sensor, the method comprising: acquiring first sensor data using the first sensor; acquiring second sensor data using the second sensor; and generating combined data including three-dimensional coordinate values ​​and color information of a plurality of points, the three-dimensional coordinate values ​​being obtained from the first sensor data, and the color information being obtained from the second sensor data. and when a difference between the combined data and the three-dimensional map is greater than a predetermined threshold, transmitting sensor information including the first sensor data and the second sensor data to a server. .

[0010] A three-dimensional data creation method according to one aspect of the present disclosure is a three-dimensional data creation method in a server capable of communicating with a client device mounted on a moving body, which receives sensor information from the client device, the sensor information being obtained by a sensor mounted on the moving body and indicating the surrounding conditions of the moving body, and creates three-dimensional data of the surroundings of the moving body from the received sensor information. Effect of the Invention

[0011] The present disclosure can provide a three-dimensional data creation method, client device, or server that can reduce the amount of data transmitted or simplify the device configuration. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram showing a structure of encoded three-dimensional data according to the first embodiment. [Diagram 2] FIG. 2 is a diagram showing an example of a prediction structure between SPCs belonging to the lowest layer of a GOS according to the first embodiment. [Diagram 3] FIG. 3 is a diagram showing an example of an inter-layer prediction structure according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing an example of the coding order of GOS according to the first embodiment. [Diagram 5] FIG. 5 is a diagram showing an example of the coding order of GOS according to the first embodiment. [Figure 6] FIG. 6 is a block diagram of the three-dimensional data encoding device according to the first embodiment. [Figure 7] FIG. 7 is a flowchart of the encoding process according to the first embodiment. [Figure 8] FIG. 8 is a block diagram of the three-dimensional data decoding device according to the first embodiment. [Figure 9] FIG. 9 is a flowchart of the decoding process according to the first embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of meta information according to the first embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of a configuration of an SWLD according to the second embodiment. [Figure 12] FIG. 12 is a diagram illustrating an example of the operation of the server and the client according to the second embodiment. [Figure 13] FIG. 13 is a diagram illustrating an example of the operation of the server and the client according to the second embodiment. [Figure 14] FIG. 14 is a diagram illustrating an example of the operation of the server and the client according to the second embodiment. [Figure 15] FIG. 15 is a diagram illustrating an example of the operation of the server and the client according to the second embodiment. [Figure 16] FIG. 16 is a block diagram of a three-dimensional data encoding device according to the second embodiment. [Figure 17] FIG. 17 is a flowchart of the encoding process according to the second embodiment. [Figure 18]FIG. 18 is a block diagram of a three-dimensional data decoding device according to the second embodiment. [Figure 19] FIG. 19 is a flowchart of the decoding process according to the second embodiment. [Figure 20] FIG. 20 is a diagram illustrating an example of a configuration of a WLD according to the second embodiment. [Figure 21] FIG. 21 is a diagram illustrating an example of an octree structure of a WLD according to the second embodiment. [Figure 22] FIG. 22 is a diagram illustrating an example of a configuration of an SWLD according to the second embodiment. [Diagram 23] FIG. 23 is a diagram illustrating an example of an octree structure of the SWLD according to the second embodiment. [Figure 24] FIG. 24 is a schematic diagram showing transmission and reception of three-dimensional data between vehicles according to the third embodiment. [Diagram 25] FIG. 25 is a diagram illustrating an example of three-dimensional data transmitted between vehicles according to the third embodiment. [Figure 26] FIG. 26 is a block diagram of a three-dimensional data creation device according to the third embodiment. [Figure 27] FIG. 27 is a flowchart of a three-dimensional data creation process according to the third embodiment. [Figure 28] FIG. 28 is a block diagram of a three-dimensional data transmission device according to the third embodiment. [Figure 29] FIG. 29 is a flowchart of a three-dimensional data transmission process according to the third embodiment. [Diagram 30] FIG. 30 is a block diagram of a three-dimensional data creation device according to the third embodiment. [Diagram 31] FIG. 31 is a flowchart of a three-dimensional data creation process according to the third embodiment. [Diagram 32] FIG. 32 is a block diagram of a three-dimensional data transmission device according to the third embodiment. [Diagram 33] FIG. 33 is a flowchart of a three-dimensional data transmission process according to the third embodiment. [Diagram 34] FIG. 34 is a block diagram of a three-dimensional information processing device according to the fourth embodiment. [Diagram 35] FIG. 35 is a flowchart of a three-dimensional information processing method according to the fourth embodiment. [Diagram 36] FIG. 36 is a flowchart of a three-dimensional information processing method according to the fourth embodiment. [Figure 37] FIG. 37 is a diagram for explaining a transmission process of three-dimensional data according to the fifth embodiment. In FIG. [Figure 38] FIG. 38 is a block diagram of a three-dimensional data creation device according to the fifth embodiment. [Figure 39] FIG. 39 is a flowchart of a three-dimensional data creating method according to the fifth embodiment. [Diagram 40] FIG. 40 is a flowchart of a three-dimensional data creating method according to the fifth embodiment. [Diagram 41] FIG. 41 is a flowchart of a display method according to the sixth embodiment. [Diagram 42] FIG. 42 is a diagram showing an example of the surrounding environment seen through a windshield according to the sixth embodiment. [Diagram 43] FIG. 43 is a diagram showing a display example of a head-up display according to the sixth embodiment. [Diagram 44] FIG. 44 is a diagram showing a display example of the head-up display after adjustment according to the sixth embodiment. [Diagram 45] FIG. 45 is a diagram showing a configuration of a system according to the seventh embodiment. In FIG. [Figure 46] FIG. 46 is a block diagram of a client device according to the seventh embodiment. [Figure 47] FIG. 47 is a block diagram of a server according to the seventh embodiment. [Figure 48] FIG. 48 is a flowchart of three-dimensional data creation processing by the client device according to the seventh embodiment. [Figure 49] FIG. 49 is a flowchart of a sensor information transmission process by a client device according to the seventh embodiment. [Figure 50]FIG. 50 is a flowchart of three-dimensional data creation processing by the server according to the seventh embodiment. [Figure 51] FIG. 51 is a flowchart of a three-dimensional map transmission process performed by a server according to the seventh embodiment. [Figure 52] FIG. 52 is a diagram showing a configuration of a modified example of the system according to the seventh embodiment. In FIG. [Diagram 53] FIG. 53 is a diagram showing configurations of a server and a client device according to the seventh embodiment. In FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] When using encoded data such as point clouds in actual devices or services, random access to desired spatial positions or objects is essential, but until now, there has been no function for random access in three-dimensional encoded data, and no encoding method for this purpose.

[0014] This disclosure describes a three-dimensional data encoding method, a three-dimensional data decoding method, a three-dimensional data encoding device, or a three-dimensional data decoding device that can provide a random access function in encoded three-dimensional data.

[0015] A three-dimensional data encoding method according to one embodiment of the present disclosure is a three-dimensional data encoding method for encoding three-dimensional data, and includes a division step of dividing the three-dimensional data into first processing units, which are random access units and each of which corresponds to a three-dimensional coordinate, and an encoding step of generating encoded data by encoding each of a plurality of the first processing units.

[0016] This enables random access for each first processing unit. In this manner, the three-dimensional data encoding method can provide a random access function for encoded three-dimensional data.

[0017] For example, the three-dimensional data encoding method may include a generation step of generating first information indicating the plurality of first processing units and three-dimensional coordinates corresponding to each of the plurality of first processing units, and the encoded data may include the first information.

[0018] For example, the first information may further indicate at least one of an object, a time, and a data storage destination associated with each of the plurality of first processing units.

[0019] For example, the dividing step may further include dividing the first processing unit into a plurality of second processing units, and the encoding step may include encoding each of the plurality of second processing units.

[0020] For example, in the encoding step, a second processing unit to be processed that is included in a first processing unit to be processed may be encoded by referring to another second processing unit that is included in the first processing unit to be processed.

[0021] According to this, by referring to other second processing units, it is possible to improve the coding efficiency.

[0022] For example, in the encoding step, the type of the second processing unit to be processed may be selected from among a first type that does not reference other second processing units, a second type that references one other second processing unit, and a third type that references two other second processing units, and the second processing unit to be processed may be encoded according to the selected type.

[0023] For example, in the encoding step, the frequency of selecting the first type may be changed depending on the number or density of objects included in the three-dimensional data.

[0024] This allows appropriate setting of random accessibility and coding efficiency, which are in a trade-off relationship.

[0025] For example, in the encoding step, the size of the first processing unit may be determined according to the number or density of objects or dynamic objects included in the three-dimensional data.

[0026] This allows appropriate setting of random accessibility and coding efficiency, which are in a trade-off relationship.

[0027] For example, the first processing unit may be spatially divided in a predetermined direction and include a plurality of layers, each including one or more of the second processing units, and in the encoding step, the second processing unit may be encoded by referring to the second processing unit included in the same layer as the second processing unit or in a layer lower than the second processing unit.

[0028] This makes it possible, for example, to improve random accessibility to layers that are important in the system and to suppress a decrease in coding efficiency.

[0029] For example, in the dividing step, a second processing unit including only static objects and a second processing unit including only dynamic objects may be assigned to different first processing units.

[0030] This allows easy control of dynamic and static objects.

[0031] For example, in the encoding step, a plurality of dynamic objects may be encoded individually, and encoded data of the plurality of dynamic objects may be associated with a second processing unit including only static objects.

[0032] This allows easy control of dynamic and static objects.

[0033] For example, the dividing step may further divide the second processing unit into a plurality of third processing units, and the encoding step may encode each of the plurality of third processing units.

[0034] For example, the third processing unit may include one or more voxels, which are the smallest units to which position information can be associated.

[0035] For example, the second processing unit may include a group of feature points derived from information obtained by a sensor.

[0036] For example, the encoded data may include information indicating a coding order of the first processing units.

[0037] For example, the encoded data may include information indicating the sizes of the first processing units.

[0038] For example, in the encoding step, the plurality of first processing units may be encoded in parallel.

[0039] Furthermore, a three-dimensional data decoding method according to one embodiment of the present disclosure is a three-dimensional data decoding method for decoding three-dimensional data, and includes a decoding step of generating three-dimensional data of a first processing unit by decoding each piece of encoded data of the first processing unit, the first processing unit being a random access unit and each piece of encoded data corresponding to a three-dimensional coordinate.

[0040] This enables random access for each first processing unit. In this manner, the three-dimensional data decoding method can provide a random access function for encoded three-dimensional data.

[0041] In addition, a three-dimensional data encoding device according to one embodiment of the present disclosure may be a three-dimensional data encoding device that encodes three-dimensional data, and may include a division unit that divides the three-dimensional data into first processing units, which are random access units and each of which corresponds to a three-dimensional coordinate, and an encoding unit that generates encoded data by encoding each of a plurality of the first processing units.

[0042] This enables random access for each first processing unit. In this manner, the three-dimensional data encoding device can provide a random access function for encoded three-dimensional data.

[0043] In addition, a three-dimensional data decoding device according to one embodiment of the present disclosure may be a three-dimensional data decoding device that decodes three-dimensional data, and may include a decoding unit that generates three-dimensional data of a first processing unit by decoding each piece of encoded data of the first processing unit, the first processing unit being a random access unit and each piece of encoded data corresponding to a three-dimensional coordinate.

[0044] This enables random access for each first processing unit. In this manner, the three-dimensional data decoding device can provide a random access function for the encoded three-dimensional data.

[0045] Note that the present disclosure enables spatial quantization, prediction, and the like, by using a configuration in which space is divided and coded, and is effective even in cases where random access is not necessarily performed.

[0046] In addition, a three-dimensional data encoding method according to one embodiment of the present disclosure includes an extraction step of extracting second three-dimensional data from first three-dimensional data, the second three-dimensional data having a feature amount equal to or greater than a threshold value, and a first encoding step of generating first encoded three-dimensional data by encoding the second three-dimensional data.

[0047] According to this, the three-dimensional data encoding method generates first encoded three-dimensional data by encoding data whose feature amount is equal to or greater than a threshold. This makes it possible to reduce the amount of encoded three-dimensional data compared to the case where the first three-dimensional data is encoded as is. Therefore, the three-dimensional data encoding method can reduce the amount of data to be transmitted.

[0048] For example, the three-dimensional data encoding method may further include a second encoding step of generating second encoded three-dimensional data by encoding the first three-dimensional data.

[0049] According to this, the three-dimensional data encoding method can selectively transmit the first encoded three-dimensional data and the second encoded three-dimensional data depending on, for example, the intended use.

[0050] For example, the second three-dimensional data may be encoded by a first encoding method, and the first three-dimensional data may be encoded by a second encoding method different from the first encoding method.

[0051] According to this, the three-dimensional data encoding method can use encoding methods suitable for the first three-dimensional data and the second three-dimensional data, respectively.

[0052] For example, in the first encoding method, of intra prediction and inter prediction, inter prediction may be given priority over the second encoding method.

[0053] According to this, the 3D data encoding method can increase the priority of inter prediction for the second 3D data in which the correlation between adjacent data is likely to be low.

[0054] For example, the first encoding method and the second encoding method may differ in the way they express a three-dimensional position.

[0055] According to this, the three-dimensional data encoding method can use a more suitable three-dimensional position expression method for three-dimensional data having different amounts of data.

[0056] For example, at least one of the first encoded three-dimensional data and the second encoded three-dimensional data may include an identifier indicating whether the encoded three-dimensional data is encoded three-dimensional data obtained by encoding the first three-dimensional data or encoded three-dimensional data obtained by encoding a portion of the first three-dimensional data.

[0057] This allows the decoding device to easily determine whether the acquired encoded three-dimensional data is the first encoded three-dimensional data or the second encoded three-dimensional data.

[0058] For example, in the first encoding step, the second three-dimensional data may be encoded so that the data amount of the first encoded three-dimensional data is smaller than the data amount of the second encoded three-dimensional data.

[0059] According to this, the three-dimensional data encoding method can make the data amount of the first encoded three-dimensional data smaller than the data amount of the second encoded three-dimensional data.

[0060] For example, the extracting step may further include extracting data corresponding to an object having a predetermined attribute from the first three-dimensional data as the second three-dimensional data.

[0061] According to this, the three-dimensional data encoding method can generate first encoded three-dimensional data including data required by the decoding device.

[0062] For example, the three-dimensional data encoding method may further include a transmitting step of transmitting one of the first encoded three-dimensional data and the second encoded three-dimensional data to the client depending on a state of the client.

[0063] According to this, the three-dimensional data encoding method can transmit appropriate data depending on the state of the client.

[0064] For example, the state of the client may include the communication status of the client or the moving speed of the client.

[0065] For example, the three-dimensional data encoding method may further include a transmitting step of transmitting one of the first encoded three-dimensional data and the second encoded three-dimensional data to a client in response to a request from the client.

[0066] According to this, the three-dimensional data encoding method can transmit appropriate data in response to a client's request.

[0067] Furthermore, a three-dimensional data decoding method according to one embodiment of the present disclosure includes a first decoding step of decoding, by a first decoding method, first encoded three-dimensional data obtained by encoding second three-dimensional data, the second encoded three-dimensional data having a feature amount extracted from the first three-dimensional data that is equal to or greater than a threshold value, and a second decoding step of decoding, by a second decoding method different from the first decoding method, the second encoded three-dimensional data obtained by encoding the first three-dimensional data.

[0068] According to this, the three-dimensional data decoding method can selectively receive the first encoded three-dimensional data, in which data with a feature amount equal to or greater than a threshold is encoded, and the second encoded three-dimensional data, depending on, for example, the intended use. This allows the three-dimensional data decoding method to reduce the amount of data to be transmitted. Furthermore, the three-dimensional data decoding method can use a decoding method suitable for each of the first three-dimensional data and the second three-dimensional data.

[0069] For example, in the first decoding method, of intra prediction and inter prediction, inter prediction may be given priority over the second decoding method.

[0070] According to this, the 3D data decoding method can increase the priority of inter prediction for the second 3D data in which the correlation between adjacent data is likely to be low.

[0071] For example, the first decoding method and the second decoding method may use different methods for expressing a three-dimensional position.

[0072] According to this, the three-dimensional data decoding method can use a more suitable three-dimensional position expression method for three-dimensional data having a different number of pieces of data.

[0073] For example, at least one of the first encoded three-dimensional data and the second encoded three-dimensional data may include an identifier indicating whether the encoded three-dimensional data is encoded three-dimensional data obtained by encoding the first three-dimensional data or encoded three-dimensional data obtained by encoding a portion of the first three-dimensional data, and the first encoded three-dimensional data and the second encoded three-dimensional data may be identified by referring to the identifier.

[0074] According to this, the three-dimensional data decoding method can easily determine whether the acquired encoded three-dimensional data is first encoded three-dimensional data or second encoded three-dimensional data.

[0075] For example, the three-dimensional data decoding method may further include a notification step of notifying a server of a client's status, and a receiving step of receiving one of the first encoded three-dimensional data and the second encoded three-dimensional data transmitted from the server depending on the client's status.

[0076] According to this, the three-dimensional data decoding method can receive appropriate data depending on the state of the client.

[0077] For example, the state of the client may include the communication status of the client or the moving speed of the client.

[0078] For example, the three-dimensional data decoding method may further include a requesting step of requesting one of the first encoded three-dimensional data and the second encoded three-dimensional data from a server, and a receiving step of receiving one of the first encoded three-dimensional data and the second encoded three-dimensional data transmitted from the server in response to the request.

[0079] According to this, the three-dimensional data decoding method can receive appropriate data according to the purpose.

[0080] In addition, a three-dimensional data encoding device according to one embodiment of the present disclosure includes an extraction unit that extracts second three-dimensional data from the first three-dimensional data, the second three-dimensional data having a feature amount equal to or greater than a threshold value, and a first encoding unit that generates first encoded three-dimensional data by encoding the second three-dimensional data.

[0081] According to this, the three-dimensional data encoding device generates first encoded three-dimensional data by encoding data whose feature amount is equal to or greater than a threshold value. This makes it possible to reduce the amount of data compared to when the first three-dimensional data is encoded as is. Therefore, the three-dimensional data encoding device can reduce the amount of data to be transmitted.

[0082] In addition, a three-dimensional data decoding device according to one embodiment of the present disclosure includes a first decoding unit that decodes, by a first decoding method, first encoded three-dimensional data obtained by encoding second three-dimensional data, the feature amount of which is extracted from the first three-dimensional data and is equal to or greater than a threshold value, and a second decoding unit that decodes, by a second decoding method different from the first decoding method, the second encoded three-dimensional data obtained by encoding the first three-dimensional data.

[0083] According to this, the three-dimensional data decoding device can selectively receive the first encoded three-dimensional data, which is obtained by encoding data whose feature amount is equal to or greater than a threshold value, and the second encoded three-dimensional data, depending on, for example, the intended use. This allows the three-dimensional data decoding device to reduce the amount of data to be transmitted. Furthermore, the three-dimensional data decoding device can use a decoding method suitable for each of the first three-dimensional data and the second three-dimensional data.

[0084] Furthermore, a three-dimensional data creation method according to one embodiment of the present disclosure includes a creation step of creating first three-dimensional data from information detected by a sensor, a receiving step of receiving encoded three-dimensional data in which second three-dimensional data is encoded, a decoding step of obtaining the second three-dimensional data by decoding the received encoded three-dimensional data, and a synthesis step of creating third three-dimensional data by synthesizing the first three-dimensional data and the second three-dimensional data.

[0085] According to this, the three-dimensional data creation method can create detailed third three-dimensional data by using the created first three-dimensional data and the received second three-dimensional data.

[0086] For example, in the combining step, the first three-dimensional data and the second three-dimensional data may be combined to generate third three-dimensional data having a higher density than the first three-dimensional data and the second three-dimensional data.

[0087] For example, the second three-dimensional data may be three-dimensional data generated by extracting data having a feature amount equal to or greater than a threshold value from the fourth three-dimensional data.

[0088] According to this, the three-dimensional data creation method can reduce the amount of three-dimensional data to be transmitted.

[0089] For example, the three-dimensional data creation method may further include a search step of searching for a transmitting device that is the source of the encoded three-dimensional data, and in the receiving step, the encoded three-dimensional data may be received from the searched transmitting device.

[0090] According to this, the three-dimensional data creation method can, for example, identify a transmitting device that has the required three-dimensional data by searching.

[0091] For example, the three-dimensional data creation method may further include a determination step of determining a requested range, which is a range of three-dimensional space for which three-dimensional data is requested, and a transmission step of transmitting information indicating the requested range to the transmitting device, and the second three-dimensional data may include three-dimensional data of the requested range.

[0092] According to this, the three-dimensional data creation method can receive necessary three-dimensional data and reduce the amount of three-dimensional data to be transmitted.

[0093] For example, in the determining step, a spatial range including an occlusion region that cannot be detected by the sensor may be determined as the required range.

[0094] A three-dimensional data transmission method according to one embodiment of the present disclosure includes a creation step of creating fifth three-dimensional data from information detected by a sensor, an extraction step of creating sixth three-dimensional data by extracting a portion of the fifth three-dimensional data, an encoding step of generating encoded three-dimensional data by encoding the sixth three-dimensional data, and a transmission step of transmitting the encoded three-dimensional data.

[0095] According to this, the three-dimensional data transmission method can transmit the three-dimensional data created by itself to another device, and can reduce the amount of the three-dimensional data to be transmitted.

[0096] For example, in the creation step, seventh three-dimensional data may be created from information detected by the sensor, and the fifth three-dimensional data may be created by extracting data having a feature amount equal to or greater than a threshold value from the seventh three-dimensional data.

[0097] According to this, the three-dimensional data transmission method can reduce the amount of three-dimensional data to be transmitted.

[0098] For example, the three-dimensional data transmission method may further include a receiving step of receiving information indicating a requested range, which is a range of three-dimensional space for which three-dimensional data is requested, from a receiving device, wherein the extraction step creates the sixth three-dimensional data by extracting three-dimensional data of the requested range from the fifth three-dimensional data, and the transmission step transmits the encoded three-dimensional data to the receiving device.

[0099] According to this, the three-dimensional data transmission method can reduce the amount of three-dimensional data to be transmitted.

[0100] Furthermore, a three-dimensional data creation device according to one embodiment of the present disclosure includes a creation unit that creates first three-dimensional data from information detected by a sensor, a receiving unit that receives encoded three-dimensional data in which second three-dimensional data is encoded, a decoding unit that obtains the second three-dimensional data by decoding the received encoded three-dimensional data, and a synthesis unit that creates third three-dimensional data by synthesizing the first three-dimensional data and the second three-dimensional data.

[0101] According to this, the three-dimensional data creation device can create detailed third three-dimensional data by using the created first three-dimensional data and the received second three-dimensional data.

[0102] Furthermore, a three-dimensional data transmission device according to one embodiment of the present disclosure includes a creation unit that creates fifth three-dimensional data from information detected by a sensor, an extraction unit that creates sixth three-dimensional data by extracting a portion of the fifth three-dimensional data, an encoding unit that generates encoded three-dimensional data by encoding the sixth three-dimensional data, and a transmission unit that transmits the encoded three-dimensional data.

[0103] This allows the three-dimensional data transmission device to transmit the three-dimensional data it has created to another device, and also reduces the amount of three-dimensional data to be transmitted.

[0104] Furthermore, a three-dimensional information processing method according to one embodiment of the present disclosure includes an acquisition step of acquiring map data including first three-dimensional position information via a communication path, a generation step of generating second three-dimensional position information from information detected by a sensor, a determination step of determining whether the first three-dimensional position information or the second three-dimensional position information is abnormal by performing an abnormality determination process on the first three-dimensional position information or the second three-dimensional position information, a determination step of determining a countermeasure action for the abnormality if the first three-dimensional position information or the second three-dimensional position information is determined to be abnormal, and an operation control step of performing control necessary to carry out the countermeasure action.

[0105] According to this, the three-dimensional information processing method can detect an abnormality in the first three-dimensional position information or the second three-dimensional position information and take a corresponding action.

[0106] For example, the first three-dimensional position information may be encoded in units of subspaces having three-dimensional coordinate information, each of which is a collection of one or more subspaces and includes multiple random access units that can each be decoded independently.

[0107] According to this, the three-dimensional information processing method can reduce the amount of data of the first three-dimensional position information to be acquired.

[0108] For example, the first three-dimensional position information may be data in which feature points whose three-dimensional feature amounts are equal to or greater than a predetermined threshold value are encoded.

[0109] According to this, the three-dimensional information processing method can reduce the amount of data of the first three-dimensional position information to be acquired.

[0110] For example, in the determination step, it may be determined whether the first three-dimensional position information can be acquired via the communication path, and if the first three-dimensional position information cannot be acquired via the communication path, it may be determined that the first three-dimensional position information is abnormal.

[0111] According to this, the three-dimensional information processing method can take an appropriate action in response to a communication situation or the like when the first three-dimensional position information cannot be acquired.

[0112] For example, the three-dimensional information processing method may further include a self-location estimation step of estimating a self-location of a moving body having the sensor using the first three-dimensional position information and the second three-dimensional position information, wherein the determination step predicts whether the moving body will enter an area where communication conditions are poor, and in the operation control step, if it is predicted that the moving body will enter an area where communication conditions are poor, the moving body may acquire the first three-dimensional information before entering the area.

[0113] According to this, the three-dimensional information processing method can acquire the first three-dimensional position information in advance when there is a possibility that the first three-dimensional position information will not be acquired.

[0114] For example, in the operation control step, if the first three-dimensional position information cannot be obtained via the communication path, third three-dimensional position information having a narrower range than the first three-dimensional position information may be obtained via the communication path.

[0115] According to this, the three-dimensional information processing method can reduce the amount of data acquired via a communication path, so that three-dimensional position information can be acquired even in poor communication conditions.

[0116] For example, the three-dimensional information processing method may further include a self-location estimation step of estimating a self-location of a moving body having the sensor using the first three-dimensional position information and the second three-dimensional position information, and in the operation control step, if the first three-dimensional position information cannot be obtained via the communication path, map data including two-dimensional position information may be obtained via the communication path, and the self-location of the moving body having the sensor may be estimated using the two-dimensional position information and the second three-dimensional position information.

[0117] According to this, the three-dimensional information processing method can reduce the amount of data acquired via a communication path, so that three-dimensional position information can be acquired even in poor communication conditions.

[0118] For example, the three-dimensional information processing method may further include an automatic driving step of automatically driving the moving body using the result of the self-position estimation, and the determination step may further determine whether or not to automatically drive the moving body using the result of the self-position estimation of the moving body using the two-dimensional position information and the second three-dimensional position information, based on the movement environment of the moving body.

[0119] According to this, the three-dimensional information processing method can determine whether or not to continue autonomous driving depending on the moving environment of the moving body.

[0120] For example, the three-dimensional information processing method may further include an automatic driving step of automatically driving the moving body using the result of the self-position estimation, and in the operation control step, the automatic driving mode may be switched based on the moving environment of the moving body.

[0121] According to this, the three-dimensional information processing method can set an appropriate automatic driving mode depending on the moving environment of the moving body.

[0122] For example, the determination step may determine whether the data of the first three-dimensional position information is complete, and if the data of the first three-dimensional position information is not complete, it may be determined that the first three-dimensional position information is abnormal.

[0123] According to this, the three-dimensional information processing method can take appropriate action in cases where the first three-dimensional position information is corrupted, for example.

[0124] For example, the determination step may determine whether the generation accuracy of the data of the second three-dimensional position information is equal to or greater than a reference value, and if the generation accuracy of the data of the second three-dimensional position information is not equal to or greater than the reference value, it may be determined that the second three-dimensional position information is abnormal.

[0125] According to this, the three-dimensional information processing method can take appropriate countermeasures when the second three-dimensional position information has low accuracy.

[0126] For example, in the operation control step, if the generation accuracy of the second three-dimensional position information data is not equal to or greater than the reference value, fourth three-dimensional position information may be generated from information detected by an alternative sensor different from the sensor.

[0127] According to this, the three-dimensional information processing method can obtain three-dimensional position information using an alternative sensor when, for example, a sensor is broken.

[0128] For example, the three-dimensional information processing method further includes a self-location estimation step of estimating a self-location of a moving body having the sensor using the first three-dimensional position information and the second three-dimensional position information, and an automatic driving step of automatically driving the moving body using a result of the self-location estimation, and in the operation control step, the automatic driving mode may be switched if the generation accuracy of the data of the second three-dimensional position information is not equal to or greater than the reference value.

[0129] According to this, the three-dimensional information processing method can take appropriate countermeasures when the second three-dimensional position information has low accuracy.

[0130] For example, in the operation control step, if the generation accuracy of the second three-dimensional position information data is not equal to or greater than the reference value, an operation correction of the sensor may be performed.

[0131] According to this, in the three-dimensional information processing method, when the accuracy of the second three-dimensional position information is low, it is possible to increase the accuracy of the second three-dimensional position information.

[0132] Moreover, a three-dimensional information processing device according to one embodiment of the present disclosure includes an acquisition unit that acquires map data including first three-dimensional position information via a communication path, a generation unit that generates second three-dimensional position information from information detected by a sensor, a determination unit that determines whether the first three-dimensional position information or the second three-dimensional position information is abnormal by performing an abnormality determination process on the first three-dimensional position information or the second three-dimensional position information, a determination unit that determines a countermeasure action for the abnormality when it is determined that the first three-dimensional position information or the second three-dimensional position information is abnormal, and an operation control unit that performs control necessary to carry out the countermeasure action.

[0133] This allows the three-dimensional information processing apparatus to detect an abnormality in the first three-dimensional position information or the second three-dimensional position information, and to take appropriate action.

[0134] Furthermore, a three-dimensional data creation method according to one embodiment of the present disclosure is a three-dimensional data creation method in a mobile body equipped with a sensor and a communication unit for transmitting and receiving three-dimensional data with an outside, and includes a three-dimensional data creation step of creating second three-dimensional data based on information detected by the sensor and first three-dimensional data received by the communication unit, and a transmission step of transmitting third three-dimensional data, which is part of the second three-dimensional data, to the outside.

[0135] According to this, the three-dimensional data creation method can generate three-dimensional data in a range that cannot be detected by a moving object. In other words, the three-dimensional data creation method can generate detailed three-dimensional data. Furthermore, the three-dimensional data creation method can transmit three-dimensional data in a range that cannot be detected by other moving objects, etc., to the other moving objects, etc.

[0136] For example, the three-dimensional data creation step and the transmission step may be performed repeatedly, and the third three-dimensional data may be three-dimensional data of a small space of a predetermined size located a predetermined distance forward in the direction of movement of the moving body from the current position of the moving body.

[0137] This makes it possible to reduce the amount of third three-dimensional data to be transmitted.

[0138] For example, the predetermined distance may change depending on the moving speed of the moving object.

[0139] According to this, the three-dimensional data creation method can set an appropriate small space according to the moving speed of the moving body, and can transmit the three-dimensional data of the small space to another moving body, etc.

[0140] For example, the predetermined size may change depending on the moving speed of the moving object.

[0141] According to this, the three-dimensional data creation method can set an appropriate small space according to the moving speed of the moving body, and can transmit the three-dimensional data of the small space to another moving body, etc.

[0142] For example, the three-dimensional data creation method may further determine whether there is a change in the second three-dimensional data of the small space corresponding to the third three-dimensional data that has already been transmitted, and if there is a change, transmit fourth three-dimensional data, which is at least a part of the second three-dimensional data that has changed, to the outside.

[0143] According to this, the three-dimensional data creation method can transmit the fourth three-dimensional data of the space where a change has occurred to another moving body or the like.

[0144] For example, the fourth three-dimensional data may be transmitted with priority over the third three-dimensional data.

[0145] According to this, the three-dimensional data creation method preferentially transmits the fourth three-dimensional data of the space where a change has occurred to other moving bodies, etc., so that the other moving bodies, etc. can, for example, quickly make decisions based on the three-dimensional data.

[0146] For example, if there is a change, the fourth three-dimensional data may be transmitted before the third three-dimensional data is transmitted.

[0147] For example, the fourth three-dimensional data may indicate a difference between the second three-dimensional data of the small space corresponding to the transmitted third three-dimensional data and the second three-dimensional data after the change.

[0148] According to this, the three-dimensional data creation method can reduce the amount of three-dimensional data to be transmitted.

[0149] For example, in the transmitting step, if there is no difference between the third three-dimensional data of the small space and the first three-dimensional data of the small space, the third three-dimensional data does not have to be transmitted.

[0150] This makes it possible to reduce the amount of third three-dimensional data to be transmitted.

[0151] For example, in the transmitting step, if there is no difference between the third three-dimensional data of the small space and the first three-dimensional data of the small space, information indicating that there is no difference between the third three-dimensional data of the small space and the first three-dimensional data of the small space may be transmitted to the outside.

[0152] For example, the information sensed by the sensor may be three-dimensional data.

[0153] Furthermore, a three-dimensional data creation device according to one embodiment of the present disclosure is a three-dimensional data creation device mounted on a moving body, and includes a sensor, a receiving unit that receives first three-dimensional data from an outside, a creation unit that creates second three-dimensional data based on information detected by the sensor and the first three-dimensional data, and a transmitting unit that transmits third three-dimensional data, which is part of the second three-dimensional data, to the outside.

[0154] According to this, the three-dimensional data creation device can generate three-dimensional data in a range that cannot be detected by a moving object. In other words, the three-dimensional data creation device can generate detailed three-dimensional data. Furthermore, the three-dimensional data creation device can transmit three-dimensional data in a range that cannot be detected by other moving objects to the other moving objects.

[0155] Furthermore, a display method according to one embodiment of the present disclosure is a display method in a display device that operates in cooperation with a moving body, and includes a decision step of deciding, based on a driving condition of the moving body, whether to display first surrounding information, which is information indicating the surrounding condition of the moving body and generated using two-dimensional data, or second surrounding information, which is information indicating the surrounding condition of the moving body and generated using three-dimensional data, and a display step of displaying the first surrounding information or the second surrounding information decided to be displayed.

[0156] According to this, the display method can switch between displaying first surrounding information generated using two-dimensional data and second surrounding information generated using three-dimensional data, based on the driving situation of the moving object. For example, the display method displays the second surrounding information with a large amount of information when detailed information is required, and displays the first surrounding information with a small amount of data and processing amount, etc., when detailed information is not required. This allows the display method to display appropriate information according to the situation, while reducing the amount of communication data and processing amount, etc.

[0157] For example, the driving status may be whether the moving body is moving autonomously or being manually driven, and in the decision step, if the moving body is moving autonomously, it may be decided to display the first surrounding information, and if the moving body is being manually driven, it may be decided to display the second surrounding information.

[0158] This allows detailed information to be displayed during manual driving, while also reducing the amount of processing required during automatic driving.

[0159] For example, the driving situation may be an area in which the moving object is located.

[0160] This makes it possible to display appropriate information depending on the location of the moving object.

[0161] For example, the three-dimensional data may be data obtained by extracting a point cloud having a feature amount equal to or greater than a threshold value from three-dimensional point cloud data.

[0162] This makes it possible to reduce the amount of communication data or the amount of stored data.

[0163] For example, the three-dimensional data may be data having a mesh structure generated from three-dimensional point cloud data.

[0164] This makes it possible to reduce the amount of communication data or the amount of stored data.

[0165] For example, the three-dimensional data may be data obtained by extracting a point cloud from three-dimensional point cloud data, the point cloud having a feature amount equal to or greater than a threshold value and required for self-position estimation, driving assistance, or autonomous driving.

[0166] This makes it possible to reduce the amount of communication data or the amount of stored data.

[0167] For example, the three-dimensional data may be three-dimensional point cloud data.

[0168] This can improve the accuracy of the second surrounding information.

[0169] For example, the display step may include displaying the second peripheral information on a head-up display, and the display method may further adjust the display position of the second peripheral information depending on the posture, body type, or eye position of a user riding on the moving body.

[0170] This allows information to be displayed at an appropriate position depending on the user's posture, body type, or eye position.

[0171] In addition, a display device according to one embodiment of the present disclosure is a display device that operates in cooperation with a moving body, and includes a decision unit that decides whether to display first surrounding information, which is an image showing the surrounding situation of the moving body and generated using two-dimensional data, or second surrounding information, which is an image showing the surrounding situation of the moving body and generated using three-dimensional data, based on the driving situation of the moving body, and a display unit that displays the first surrounding information or the second surrounding information that has been decided to be displayed.

[0172] According to this, the display device can switch between displaying first surrounding information generated using two-dimensional data and second surrounding information generated using three-dimensional data, based on the driving situation of the moving object. For example, when detailed information is required, the display device displays second surrounding information with a large amount of information, and when detailed information is not required, displays first surrounding information with a small amount of data and processing amount, etc. This allows the display device to display appropriate information according to the situation and reduce the amount of communication data and processing amount, etc.

[0173] Furthermore, a three-dimensional data creation method according to one aspect of the present disclosure is a three-dimensional data creation method in a client device mounted on a moving body, which creates three-dimensional data about the surroundings of the moving body from sensor information indicating the surrounding conditions of the moving body obtained by a sensor mounted on the moving body, estimates the self-position of the moving body using the created three-dimensional data, and transmits the obtained sensor information to a server or another moving body.

[0174] According to this, the three-dimensional data creation method transmits sensor information to a server or the like. This may reduce the amount of data transmitted compared to when three-dimensional data is transmitted. In addition, since the client device does not need to perform processing such as compression or encoding of the three-dimensional data, the amount of processing on the client device can be reduced. Therefore, the three-dimensional data creation method can reduce the amount of data transmitted or simplify the device configuration.

[0175] For example, the three-dimensional data creation method may further include sending a request to send a three-dimensional map to the server, receiving the three-dimensional map from the server, and estimating the self-position using the three-dimensional data and the three-dimensional map.

[0176] For example, the sensor information may include at least one of information obtained by a laser sensor, a luminance image, an infrared image, a depth image, sensor position information, and sensor velocity information.

[0177] For example, the sensor information may include at least one of information obtained by a laser sensor, a luminance image, an infrared image, a depth image, sensor position information, and sensor velocity information.

[0178] For example, the sensor information may be encoded or compressed, and the sensor information may be transmitted after being encoded or compressed to the server or the other mobile body.

[0179] According to this, the three-dimensional data creation method can reduce the amount of data to be transmitted.

[0180] Furthermore, a three-dimensional data creation method according to one aspect of the present disclosure is a three-dimensional data creation method in a server capable of communicating with a client device mounted on a moving body, which receives sensor information indicating the surrounding conditions of the moving body obtained by a sensor mounted on the moving body from the client device, and creates three-dimensional data of the surroundings of the moving body from the received sensor information.

[0181] According to this, the three-dimensional data creation method creates three-dimensional data using sensor information transmitted from a client device. This may reduce the amount of data transmitted compared to when the client device transmits the three-dimensional data. In addition, since the client device does not need to perform processing such as compression or encoding of the three-dimensional data, the amount of processing by the client device can be reduced. Therefore, the three-dimensional data creation method can reduce the amount of data transmitted or simplify the device configuration.

[0182] For example, the three-dimensional data creation method may further include transmitting a request to the client device to transmit the sensor information.

[0183] For example, the three-dimensional data creation method may further include updating a three-dimensional map using the created three-dimensional data, and transmitting the three-dimensional map to the client device in response to a request to transmit the three-dimensional map from the client device.

[0184] For example, the sensor information may include at least one of information obtained by a laser sensor, a luminance image, an infrared image, a depth image, sensor position information, and sensor velocity information.

[0185] For example, the sensor information may include information indicative of performance of the sensor.

[0186] For example, the three-dimensional data creation method may further include correcting the three-dimensional data in accordance with performance of the sensor.

[0187] According to this, the three-dimensional data creation method can improve the quality of the three-dimensional data.

[0188] For example, when receiving the sensor information, multiple pieces of sensor information may be received from multiple client devices, and the sensor information to be used for creating the three-dimensional data may be selected based on multiple pieces of information indicating the performance of the sensor contained in the multiple pieces of sensor information.

[0189] According to this, the three-dimensional data creation method can improve the quality of the three-dimensional data.

[0190] For example, the received sensor information may be decoded or decompressed, and the three-dimensional data may be created from the decoded or decompressed sensor information.

[0191] According to this, the three-dimensional data creation method can reduce the amount of data to be transmitted.

[0192] Moreover, a client device according to one aspect of the present disclosure is a client device mounted on a moving body, and is equipped with a processor and a memory, wherein the processor uses the memory to create three-dimensional data about the surroundings of the moving body from sensor information indicating the surrounding conditions of the moving body obtained by a sensor mounted on the moving body, estimates the self-position of the moving body using the created three-dimensional data, and transmits the acquired sensor information to a server or another moving body.

[0193] According to this, the client device transmits sensor information to a server or the like. This may reduce the amount of data transmitted compared to when transmitting three-dimensional data. In addition, since the client device does not need to perform processing such as compression or encoding of the three-dimensional data, the amount of processing by the client device can be reduced. Therefore, the client device can reduce the amount of data transmitted or simplify the device configuration.

[0194] In addition, a server according to one aspect of the present disclosure is a server capable of communicating with a client device mounted on a mobile body, and is equipped with a processor and a memory, and the processor uses the memory to receive sensor information indicating the surrounding conditions of the mobile body obtained by a sensor mounted on the mobile body from the client device, and creates three-dimensional data of the surroundings of the mobile body from the received sensor information.

[0195] According to this, the server creates three-dimensional data using sensor information transmitted from the client device. This may reduce the amount of data transmitted compared to when the client device transmits the three-dimensional data. In addition, since the client device does not need to perform processing such as compression or encoding of the three-dimensional data, the amount of processing of the client device can be reduced. Therefore, the server can reduce the amount of data transmitted or simplify the device configuration.

[0196] These comprehensive or specific aspects may be realized as a system, a method, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM, or may be realized as any combination of a system, a method, an integrated circuit, a computer program, and a recording medium.

[0197] Hereinafter, the embodiments will be described in detail with reference to the drawings. Note that each of the embodiments described below shows a specific example of the present disclosure. The numerical values, shapes, materials, components, arrangement and connection forms of the components, steps, and order of steps shown in the following embodiments are merely examples and are not intended to limit the present disclosure. In addition, among the components in the following embodiments, components that are not described in an independent claim showing a top concept are described as optional components.

[0198] (Embodiment 1) First, the data structure of encoded three-dimensional data (hereinafter, also referred to as encoded data) according to this embodiment will be described. Fig. 1 is a diagram showing the structure of encoded three-dimensional data according to this embodiment.

[0199] In this embodiment, the three-dimensional space is divided into spaces (SPC) corresponding to pictures in video coding, and the three-dimensional data is coded using the spaces as units. The space is further divided into volumes (VLM) corresponding to macroblocks in video coding, and prediction and conversion are performed using the VLM as units. The volume includes a plurality of voxels (VXL), which are the smallest units to which position coordinates are associated. Note that prediction refers to, as with prediction performed on two-dimensional images, generating predicted three-dimensional data similar to the processing unit to be processed by referring to other processing units, and coding the difference between the predicted three-dimensional data and the processing unit to be processed. In addition, this prediction includes not only spatial prediction that refers to other prediction units at the same time, but also temporal prediction that refers to prediction units at different times.

[0200] For example, when a three-dimensional data encoding device (hereinafter also referred to as an encoding device) encodes a three-dimensional space represented by point cloud data such as a point cloud, it encodes each point of the point cloud or a group of points contained in a voxel according to the size of the voxel. By subdividing the voxel, the three-dimensional shape of the point cloud can be expressed with high accuracy, and by increasing the size of the voxel, the three-dimensional shape of the point cloud can be expressed roughly.

[0201] In the following, an example will be described in which the three-dimensional data is a point cloud; however, the three-dimensional data is not limited to a point cloud, and may be three-dimensional data in any format.

[0202] Also, voxels with a hierarchical structure may be used. In this case, in the nth layer, it may be indicated in order whether a sample point exists in the n-1th or lower layer (a layer below the nth layer). For example, when decoding only the nth layer, if a sample point exists in the n-1th or lower layer, the sample point can be decoded by considering it to exist at the center of the voxel in the nth layer.

[0203] In addition, the encoding device acquires the point cloud data using a distance sensor, a stereo camera, a monocular camera, a gyro, an inertial sensor, or the like.

[0204] As in video coding, the space is classified into at least three prediction structures, including an independently decodable intra space (I-SPC), a unidirectionally referable predictive space (P-SPC), and a bidirectionally referable bidirectional space (B-SPC). The space also has two types of time information: the decoding time and the display time.

[0205] As shown in Fig. 1, there is a random access unit called a Group Of Space (GOS) which is a processing unit including multiple spaces. Furthermore, there is a World (WLD) which is a processing unit including multiple GOS.

[0206] The spatial region that the world occupies is associated with an absolute position on the earth by GPS or latitude and longitude information, etc. This position information is stored as meta information. Note that the meta information may be included in the encoded data or may be transmitted separately from the encoded data.

[0207] Furthermore, within a GOS, all SPCs may be three-dimensionally adjacent, or there may be SPCs that are not three-dimensionally adjacent to other SPCs.

[0208] In the following, the process of encoding, decoding, referencing, etc. of three-dimensional data included in a processing unit such as a GOS, SPC, or VLM will also be simply referred to as encoding, decoding, referencing, etc. of a processing unit. Also, the three-dimensional data included in a processing unit includes at least one pair of a spatial position such as three-dimensional coordinates and a characteristic value such as color information.

[0209] Next, the prediction structure of SPCs in a GOS will be explained. Multiple SPCs in the same GOS, or multiple VLMs in the same SPC, occupy different spaces from each other, but have the same time information (decoding time and display time).

[0210] In addition, the first SPC in a GOS in decoding order is the I-SPC. There are two types of GOS: closed GOS and open GOS. A closed GOS is a GOS in which all SPCs in the GOS can be decoded when decoding starts from the first I-SPC. In an open GOS, some SPCs in the GOS whose display time precedes the first I-SPC refer to a different GOS, and cannot be decoded using only that GOS.

[0211] In addition, in coded data such as map information, the WLD may be decoded in the reverse order from the coding order, and if there is a dependency between the GOS, reverse playback is difficult. Therefore, in such cases, closed GOS is basically used.

[0212] Furthermore, the GOS has a layer structure in the height direction, and encoding or decoding is performed in order starting from the SPC in the lower layer.

[0213] Fig. 2 is a diagram showing an example of a prediction structure between SPCs belonging to the lowest layer of a GOS, and Fig. 3 is a diagram showing an example of a prediction structure between layers.

[0214] There are one or more I-SPCs in a GOS. Objects such as humans, animals, cars, bicycles, traffic lights, and landmark buildings exist in a three-dimensional space, and it is effective to encode small objects as I-SPCs. For example, a three-dimensional data decoding device (hereinafter also referred to as a decoding device) decodes only the I-SPCs in the GOS when decoding the GOS with low processing load or at high speed.

[0215] Furthermore, the encoding device may switch the encoding interval or occurrence frequency of I-SPC depending on the density of objects in the WLD.

[0216] In addition, in the configuration shown in Fig. 3, the encoding device or decoding device encodes or decodes multiple layers in order from the lower layer (layer 1). This allows, for example, an autonomous vehicle to increase the priority of data near the ground, which contains more information.

[0217] In addition, in the case of encoded data used by drones, etc., encoding or decoded may be performed in order from the SPC of the upper layer in the height direction within the GOS.

[0218] Alternatively, the encoding device or decoding device may encode or decode multiple layers so that the decoding device can roughly grasp the GOS and gradually increase the resolution. For example, the encoding device or decoding device may encode or decode layers 3, 8, 1, 9, etc. in that order.

[0219] Next, how to handle static and dynamic objects will be described.

[0220] In a three-dimensional space, there exist static objects or scenes such as buildings or roads (hereinafter collectively referred to as static objects), and dynamic objects such as cars or people (hereinafter referred to as dynamic objects). Object detection is performed separately by extracting feature points from point cloud data or camera images such as a stereo camera. Here, an example of a method for encoding dynamic objects will be described.

[0221] The first method is to encode the static objects without distinguishing between the static objects and the dynamic objects, and the second method is to distinguish between the static objects and the dynamic objects by using identification information.

[0222] For example, a GOS is used as an identification unit. In this case, a GOS including SPCs constituting static objects and a GOS including SPCs constituting dynamic objects are distinguished by identification information stored in the coded data or separately from the coded data.

[0223] Alternatively, the SPC may be used as the identification unit. In this case, the SPC including the VLM constituting the static object and the SPC including the VLM constituting the dynamic object are distinguished by the above-mentioned identification information.

[0224] Alternatively, the VLM or VXL may be used as the identification unit. In this case, the VLM or VXL including a static object is distinguished from the VLM or VXL including a dynamic object by the above-mentioned identification information.

[0225] The encoding device may also encode a dynamic object as one or more VLMs or SPCs, and encode a VLM or SPC including a static object and an SPC including a dynamic object as different GOSs. In addition, when the size of the GOS varies depending on the size of the dynamic object, the encoding device stores the size of the GOS separately as meta information.

[0226] The encoding device may also encode the static object and the dynamic object independently of each other, and overlay the dynamic object on the world composed of the static objects. In this case, the dynamic object is composed of one or more SPCs, and each SPC is associated with one or more SPCs constituting the static object on which the SPC is overlaid. Note that the dynamic object may be represented by one or more VLMs or VXLs instead of SPCs.

[0227] The encoding device may also encode static objects and dynamic objects as different streams.

[0228] The encoding device may also generate a GOS including one or more SPCs that constitute a dynamic object. Furthermore, the encoding device may set the GOS including the dynamic object (GOS_M) and the GOS of the static object corresponding to the spatial area of ​​GOS_M to the same size (occupy the same spatial area). This allows the superimposition process to be performed on a GOS-by-GOS basis.

[0229] A P-SPC or B-SPC constituting a dynamic object may refer to an SPC included in a different encoded GOS. In cases where the position of a dynamic object changes over time and the same dynamic object is encoded as a GOS at a different time, referencing across GOS is effective in terms of compression ratio.

[0230] Also, the first method and the second method may be switched depending on the use of the encoded data. For example, when the encoded three-dimensional data is used as a map, it is desirable to be able to separate dynamic objects, so the encoding device uses the second method. On the other hand, when encoding three-dimensional data of an event such as a concert or sporting event, if there is no need to separate dynamic objects, the encoding device uses the first method.

[0231] Furthermore, the decode time and display time of the GOS or SPC can be stored in the encoded data or as meta information. Furthermore, all time information of static objects may be the same. In this case, the actual decode time and display time may be determined by the decoding device. Alternatively, a different value may be assigned as the decode time for each GOS or SPC, and the same value may be assigned as the display time for all. Furthermore, a model may be introduced in which the decoder has a buffer of a predetermined size, and guarantees that decoding can be performed without failure if a bitstream is read at a predetermined bit rate according to the decode time, as in a decoder model in video coding such as the HRD (Hypothetical Reference Decoder) of HEVC.

[0232] Next, the arrangement of GOS in the world will be described. The coordinates of the three-dimensional space in the world are expressed by three mutually orthogonal coordinate axes (x-axis, y-axis, z-axis). By setting a predetermined rule for the coding order of GOS, coding can be performed so that spatially adjacent GOS are continuous in the coded data. For example, in the example shown in FIG. 4, GOS in the xz plane are coded continuously. After coding of all GOS in a certain xz plane is completed, the value of the y axis is updated. In other words, as coding progresses, the world extends in the y axis direction. Also, the index numbers of GOS are set in the coding order.

[0233] Here, the three-dimensional space of the world is associated one-to-one with absolute geographical coordinates such as GPS or latitude and longitude. Alternatively, the three-dimensional space may be expressed by a relative position from a preset reference position. The directions of the x-axis, y-axis, and z-axis of the three-dimensional space are expressed as direction vectors determined based on the latitude and longitude, and the direction vectors are stored as meta information together with the encoded data.

[0234] Moreover, the size of the GOS is fixed, and the encoding device stores the size as meta information. The size of the GOS may be switched depending on, for example, whether it is an urban area or not, or whether it is indoors or outdoors. That is, the size of the GOS may be switched depending on the amount or nature of objects that have information value. Alternatively, the encoding device may adaptively switch the size of the GOS or the interval of I-SPCs in the GOS depending on the density of objects within the same world. For example, the higher the density of objects, the smaller the size of the GOS and the shorter the interval of I-SPCs in the GOS.

[0235] In the example of Figure 5, the third to tenth GOS areas have a high density of objects, so the GOS are subdivided to achieve fine-grained random access. Note that the seventh to tenth GOS are located behind the third to sixth GOS, respectively.

[0236] Next, the configuration and operation flow of the three-dimensional data encoding device according to this embodiment will be described. Fig. 6 is a block diagram of the three-dimensional data encoding device 100 according to this embodiment. Fig. 7 is a flowchart showing an example of the operation of the three-dimensional data encoding device 100.

[0237] 6 generates encoded three-dimensional data 112 by encoding three-dimensional data 111. The three-dimensional data encoding device 100 includes an acquisition unit 101, an encoding region determination unit 102, a division unit 103, and an encoding unit 104.

[0238] As shown in FIG. 7, first, the acquisition unit 101 acquires three-dimensional data 111, which is point cloud data (S101).

[0239] Next, the coding region determination unit 102 determines a region to be coded from among the spatial regions corresponding to the acquired point cloud data (S102). For example, the coding region determination unit 102 determines a spatial region around a position of a user or a vehicle as a region to be coded, depending on the position of the user or the vehicle.

[0240] Next, the division unit 103 divides the point cloud data included in the region to be coded into each processing unit. Here, the processing units are the above-mentioned GOS and SPC, etc. Furthermore, this region to be coded corresponds to, for example, the above-mentioned world. Specifically, the division unit 103 divides the point cloud data into processing units based on a preset size of the GOS, or the presence or absence or size of a dynamic object (S103). Furthermore, the division unit 103 determines the start position of the SPC that is the first in the coding order in each GOS.

[0241] Next, the encoding unit 104 generates encoded three-dimensional data 112 by sequentially encoding a plurality of SPCs in each GOS (S104).

[0242] In this example, the area to be coded is divided into GOS and SPC, and then each GOS is coded, but the processing procedure is not limited to the above. For example, a procedure may be used in which the configuration of one GOS is determined, the GOS is coded, and then the configuration of the next GOS is determined.

[0243] In this way, the three-dimensional data encoding device 100 generates encoded three-dimensional data 112 by encoding the three-dimensional data 111. Specifically, the three-dimensional data encoding device 100 divides the three-dimensional data into first processing units (GOS), which are random access units and each of which corresponds to a three-dimensional coordinate, divides the first processing units (GOS) into a plurality of second processing units (SPC), and divides the second processing units (SPC) into a plurality of third processing units (VLM). Furthermore, the third processing units (VLM) include one or more voxels (VXL), which are the smallest units to which position information corresponds.

[0244] Next, the three-dimensional data encoding device 100 generates encoded three-dimensional data 112 by encoding each of the multiple first processing units (GOS). Specifically, the three-dimensional data encoding device 100 encodes each of the multiple second processing units (SPC) in each first processing unit (GOS). Also, the three-dimensional data encoding device 100 encodes each of the multiple third processing units (VLM) in each second processing unit (SPC).

[0245] For example, when the first processing unit (GOS) to be processed is a closed GOS, the three-dimensional data encoding device 100 encodes the second processing unit (SPC) to be processed included in the first processing unit (GOS) to be processed by referring to other second processing units (SPC) included in the first processing unit (GOS) to be processed. In other words, the three-dimensional data encoding device 100 does not refer to the second processing unit (SPC) included in a first processing unit (GOS) different from the first processing unit (GOS) to be processed.

[0246] On the other hand, when the first processing unit (GOS) to be processed is an open GOS, the second processing unit (SPC) to be processed included in the first processing unit (GOS) to be processed is encoded by referring to other second processing units (SPC) included in the first processing unit (GOS) to be processed, or a second processing unit (SPC) included in a first processing unit (GOS) different from the first processing unit (GOS) to be processed.

[0247] In addition, the three-dimensional data encoding device 100 selects, as the type of the second processing unit (SPC) to be processed, one of a first type (I-SPC) that does not reference other second processing units (SPCs), a second type (P-SPC) that references one other second processing unit (SPC), and a third type that references two other second processing units (SPCs), and encodes the second processing unit (SPC) to be processed according to the selected type.

[0248] Next, the configuration and operation flow of the three-dimensional data decoding device according to this embodiment will be described. Fig. 8 is a block diagram of the blocks of the three-dimensional data decoding device 200 according to this embodiment. Fig. 9 is a flowchart showing an example of the operation of the three-dimensional data decoding device 200.

[0249] 8 generates decoded three-dimensional data 212 by decoding encoded three-dimensional data 211. Here, the encoded three-dimensional data 211 is, for example, the encoded three-dimensional data 112 generated by the three-dimensional data encoding device 100. This three-dimensional data decoding device 200 includes an acquisition unit 201, a decoding start GOS determination unit 202, a decoding SPC determination unit 203, and a decoding unit 204.

[0250] First, the acquisition unit 201 acquires the encoded 3D data 211 (S201). Next, the decoding start GOS determination unit 202 determines a GOS to be decoded (S202). Specifically, the decoding start GOS determination unit 202 refers to meta information stored in the encoded 3D data 211 or separately from the encoded 3D data, and determines a GOS including an SPC corresponding to a spatial position, object, or time at which decoding starts as a GOS to be decoded.

[0251] Next, the decoding SPC determination unit 203 determines the type (I, P, B) of the SPC to be decoded in the GOS (S203). For example, the decoding SPC determination unit 203 determines whether to (1) decode only the I-SPC, (2) decode the I-SPC and P-SPC, or (3) decode all types. Note that if the type of SPC to be decoded has been determined in advance, such as when all SPCs are to be decoded, this step does not need to be performed.

[0252] Next, the decoding unit 204 obtains the address position at which the first SPC in the GOS in decoding order (the same as the encoding order) starts in the encoded 3D data 211, obtains the encoded data of the first SPC from the address position, and sequentially decodes each SPC in order starting from the first SPC (S204). Note that the address position is stored in meta information or the like.

[0253] In this manner, the three-dimensional data decoding device 200 decodes the decoded three-dimensional data 212. Specifically, the three-dimensional data decoding device 200 generates the decoded three-dimensional data 212 of the first processing unit (GOS) by decoding each of the encoded three-dimensional data 211 of the first processing unit (GOS), which is a random access unit and corresponds to a three-dimensional coordinate. More specifically, the three-dimensional data decoding device 200 decodes each of the multiple second processing units (SPC) in each first processing unit (GOS). Also, the three-dimensional data decoding device 200 decodes each of the multiple third processing units (VLM) in each second processing unit (SPC).

[0254] The meta information for random access will be described below. This meta information is generated by the three-dimensional data encoding device 100 and is included in the encoded three-dimensional data 112 (211).

[0255] In conventional random access for two-dimensional video, decoding is started from the first frame of a random access unit that is close to a specified time. On the other hand, in the world, random access to space (coordinates, objects, etc.) is assumed in addition to time.

[0256] Therefore, in order to realize random access to at least three elements, coordinates, object, and time, a table is prepared that associates each element with a GOS index number. Furthermore, the GOS index number is associated with the address of the I-SPC at the beginning of the GOS. FIG. 10 is a diagram showing an example of a table included in the meta information. Note that it is not necessary to use all of the tables shown in FIG. 10, and it is sufficient to use at least one table.

[0257] Hereinafter, as an example, random access starting from coordinates will be described. When accessing coordinates (x2, y2, z2), first, the coordinate-GOS table is referenced and it is found that the point with coordinates (x2, y2, z2) is included in the second GOS. Next, the GOS address table is referenced and it is found that the address of the first I-SPC in the second GOS is addr(2), so the decoding unit 204 obtains data from this address and starts decoding.

[0258] The address may be an address in a logical format or a physical address of a HDD or memory. Information that identifies a file segment may be used instead of the address. For example, a file segment is a unit obtained by segmenting one or more GOS.

[0259] In addition, if an object spans multiple GOSs, the object-GOS table may indicate multiple GOSs to which the object belongs. If the multiple GOSs are closed GOSs, the encoding device and the decoding device can perform encoding or decoding in parallel. On the other hand, if the multiple GOSs are open GOSs, the multiple GOSs can refer to each other to improve compression efficiency.

[0260] Examples of objects include humans, animals, cars, bicycles, traffic lights, landmark buildings, etc. For example, the three-dimensional data encoding device 100 can extract feature points specific to objects from a three-dimensional point cloud or the like when encoding a world, detect objects based on the feature points, and set the detected objects as random access points.

[0261] In this way, the three-dimensional data encoding device 100 generates first information indicating a plurality of first processing units (GOS) and three-dimensional coordinates associated with each of the plurality of first processing units (GOS). The encoded three-dimensional data 112 (211) includes this first information. The first information further indicates at least one of an object, a time, and a data storage destination associated with each of the plurality of first processing units (GOS).

[0262] The three-dimensional data decoding device 200 acquires first information from the encoded three-dimensional data 211, and uses the first information to identify the encoded three-dimensional data 211 of a first processing unit corresponding to a specified three-dimensional coordinate, object or time, and decodes the encoded three-dimensional data 211.

[0263] Other examples of meta information will be described below. In addition to the meta information for random access, the three-dimensional data encoding device 100 may generate and store the following meta information. Furthermore, the three-dimensional data decoding device 200 may use this meta information during decoding.

[0264] When using three-dimensional data as map information, a profile may be defined according to the application, and information indicating the profile may be included in the meta information. For example, a profile for urban areas or suburban areas, or for flying objects may be defined, and the maximum or minimum size of the world, SPC, or VLM may be defined for each. For example, the minimum size of the VLM is set to be smaller for urban areas, since more detailed information is required than for suburban areas.

[0265] The meta information may include a tag value indicating the type of object. This tag value is associated with the VLM, SPC, or GOS that constitutes the object. For example, a tag value may be set for each type of object, such as a tag value of "0" indicating a "person," a tag value of "1" indicating a "car," and a tag value of "2" indicating a "traffic light." Alternatively, when it is difficult to determine the type of object or there is no need to determine it, a tag value indicating a property such as size or whether the object is a dynamic or static object may be used.

[0266] The meta information may also include information indicating the extent of the spatial region that the world occupies.

[0267] The meta information may also store the size of an SPC or VXL as header information common to a plurality of SPCs, such as an SPC in an entire stream of encoded data or a GOS.

[0268] The meta information may also include identification information for the range sensor or camera used to generate the point cloud, or information indicating the positional accuracy of the points in the point cloud.

[0269] The meta information may also include information indicating whether the world is made up of only static objects or whether it also includes dynamic objects.

[0270] A modification of this embodiment will now be described.

[0271] The encoding device or the decoding device may encode or decode two or more different SPCs or GOSs in parallel. The GOSs to be encoded or decoded in parallel can be determined based on meta-information indicating the spatial positions of the GOSs.

[0272] In cases where three-dimensional data is used as a spatial map for the movement of a vehicle or flying object, or where such a spatial map is to be generated, the encoding device or decoding device may encode or decode a GOS or SPC contained in a space identified based on a GPS, route information, zoom magnification, etc.

[0273] The decoding device may also decode spaces in order from the closest to the self-location or the driving route. The encoding device or decoding device may code or decode spaces farther from the self-location or the driving route by lowering the priority compared to closer spaces. Here, lowering the priority means lowering the processing order, lowering the resolution (thinning out the data before processing), or lowering the image quality (increasing the encoding efficiency, for example, by increasing the quantization step), etc.

[0274] Furthermore, when decoding encoded data that has been hierarchically encoded in space, the decoding device may decode only the lower hierarchical layers.

[0275] The decoding device may also give priority to decoding from the lower layers depending on the zoom factor or purpose of the map.

[0276] In addition, for applications such as self-position estimation or object recognition performed when a car or robot is driving autonomously, the encoding device or decoding device may perform encoding or decoding with reduced resolution except for areas within a specific height from the road surface (area where recognition is performed).

[0277] The encoding device may also encode point clouds that represent the spatial shapes of the interior and exterior of a room separately. For example, by separating the GOS that represent the interior of a room (indoor GOS) from the GOS that represent the exterior of a room (outdoor GOS), the decoding device can select the GOS to be decoded according to the viewpoint position when using the encoded data.

[0278] The encoding device may also encode the indoor GOS and the outdoor GOS that are close to each other in the encoded stream so that they are adjacent to each other. For example, the encoding device may associate identifiers of the two and store information indicating the associated identifiers in the encoded stream or in meta information stored separately. This allows the decoding device to identify the indoor GOS and the outdoor GOS that are close to each other by referring to the information in the meta information.

[0279] The encoding device may also switch the size of the GOS or SPC between the indoor GOS and the outdoor GOS. For example, the encoding device may set the size of the GOS smaller indoors than outdoors. The encoding device may also change the accuracy of extracting feature points from the point cloud or the accuracy of object detection between the indoor GOS and the outdoor GOS.

[0280] The encoding device may also add information to the encoded data that allows the decoding device to distinguish dynamic objects from static objects. This allows the decoding device to display dynamic objects together with red frames or explanatory text. The decoding device may display only red frames or explanatory text instead of dynamic objects. The decoding device may also display more specific object types. For example, a red frame may be used for cars and a yellow frame for people.

[0281] Furthermore, the encoding device or decoding device may determine whether to encode or decode dynamic objects and static objects as different SPCs or GOSs, depending on the frequency of appearance of the dynamic objects, or the ratio of static objects to dynamic objects, etc. For example, if the frequency of appearance or the ratio of dynamic objects exceeds a threshold, an SPC or GOS in which dynamic objects and static objects are mixed is permitted, and if the frequency of appearance or the ratio of dynamic objects does not exceed the threshold, an SPC or GOS in which dynamic objects and static objects are mixed is not permitted.

[0282] When detecting a dynamic object from two-dimensional image information from a camera, rather than from a point cloud, the encoding device may separately obtain information for identifying the detection result (such as a frame or text) and the object position, and encode this information as part of the three-dimensional encoded data. In this case, the decoding device displays auxiliary information (a frame or text) indicating the dynamic object by superimposing it on the decoding result of the static object.

[0283] The encoding device may also change the density of the VXL or VLM in the SPC depending on the complexity of the shape of the static object, etc. For example, the encoding device sets the VXL or VLM to be denser the more complex the shape of the static object. Furthermore, the encoding device may determine the quantization step, etc., when quantizing spatial position or color information, depending on the density of the VXL or VLM. For example, the encoding device sets the quantization step to be smaller the more dense the VXL or VLM.

[0284] As described above, the encoding device or decoding device according to this embodiment performs spatial encoding or decoding in units of spaces having coordinate information.

[0285] Furthermore, the encoding device and the decoding device perform encoding and decoding in units of volumes within a space. A volume includes voxels, which are the smallest units to which position information can be associated.

[0286] The encoding device and the decoding device perform encoding or decoding by associating any elements with each other using a table that associates each element of spatial information including coordinates, objects, and time with a GOP, or a table that associates each element with each other. The decoding device determines coordinates using the value of a selected element, identifies a volume, voxel, or space from the coordinates, and decodes the space including the volume or voxel, or the identified space.

[0287] The encoding device also determines volumes, voxels, or spaces that can be selected by elements by feature point extraction or object recognition, and encodes them as randomly accessible volumes, voxels, or spaces.

[0288] Spaces are classified into three types: I-SPC, which can be encoded or decoded by itself; P-SPC, which is encoded or decoded by reference to any one processed space; and B-SPC, which is encoded or decoded by reference to any two processed spaces.

[0289] One or more volumes correspond to static objects or dynamic objects. The space containing the static objects and the space containing the dynamic objects are encoded or decoded as different GOS. That is, the SPC containing the static objects and the SPC containing the dynamic objects are assigned to different GOS.

[0290] Dynamic objects are encoded or decoded on an object-by-object basis and associated with one or more spaces containing static objects, i.e., multiple dynamic objects are encoded individually and the resulting encoded data for the multiple dynamic objects are associated with an SPC containing the static objects.

[0291] The encoding device and the decoding device increase the priority of the I-SPC in the GOS and perform encoding or decoding. For example, the encoding device performs encoding so as to reduce degradation of the I-SPC (so that the original three-dimensional data is reproduced more faithfully after decoding). Also, the decoding device decodes only the I-SPC, for example.

[0292] The encoding device may perform encoding by changing the frequency of using I-SPC depending on the density or number (amount) of objects in the world. In other words, the encoding device changes the frequency of selecting I-SPC depending on the number or density of objects included in the three-dimensional data. For example, the encoding device increases the frequency of using I-space as the density of objects in the world increases.

[0293] Furthermore, the encoding device sets random access points in units of GOS, and stores information indicating a spatial region corresponding to the GOS in the header information.

[0294] The encoding device uses, for example, a default value as the spatial size of the GOS. The encoding device may change the size of the GOS depending on the number (quantity) or density of objects or dynamic objects. For example, the encoding device reduces the spatial size of the GOS as the objects or dynamic objects are denser or the number of objects or dynamic objects is greater.

[0295] The space or volume may also include a set of feature points derived using information obtained by sensors such as a depth sensor, a gyro, or a camera. The coordinates of the feature points are set at the center positions of the voxels. Furthermore, the position information can be highly accurate by subdividing the voxels.

[0296] The feature points are derived using a plurality of pictures having at least two types of time information: actual time information and time information that is the same for a plurality of pictures associated with the space (e.g., encoding time used for rate control, etc.).

[0297] Moreover, encoding or decoding is performed in units of GOS including one or more spaces.

[0298] The encoding device and the decoding device refer to spaces in a GOS that have already been processed to predict a P space or a B space in a GOS to be processed.

[0299] Alternatively, the encoding device and the decoding device predict the P space or the B space in the GOS to be processed by using a processed space in the GOS to be processed, without referring to a different GOS.

[0300] Furthermore, the encoding device and the decoding device transmit or receive an encoded stream in units of worlds, each world including one or more GOSs.

[0301] Furthermore, the GOS has a layer structure in at least one direction within a world, and the encoding device and decoding device encode or decode from the lower layer. For example, a randomly accessible GOS belongs to the lowest layer. A GOS belonging to a higher layer refers to a GOS belonging to the same layer or lower. In other words, the GOS is spatially divided in a predetermined direction and includes multiple layers, each of which includes one or more SPCs. The encoding device and decoding device encode or decode each SPC by referring to an SPC included in the same layer as the SPC or in a layer lower than the SPC.

[0302] In addition, the encoding device and the decoding device encode or decode the GOSs continuously within a world unit including multiple GOSs. The encoding device and the decoding device write or read information indicating the order (direction) of encoding or decoding as metadata. In other words, the encoded data includes information indicating the encoding order of multiple GOSs.

[0303] Furthermore, the encoding device and the decoding device encode or decode two or more different spaces or GOS in parallel.

[0304] In addition, the encoding device and the decoding device encode and decode spatial information (coordinates, size, etc.) of the space or GOS.

[0305] In addition, the encoding device and the decoding device encode or decode a space or GOS included in a specific space that is identified based on external information related to its own position and / or area size, such as GPS, route information, or magnification.

[0306] The encoding device or decoding device encodes or decodes a space far from its own position with a lower priority than a space close to its own position.

[0307] The encoding device sets one direction in a world according to a magnification or a use, and encodes a GOS having a layer structure in the direction. The decoding device decodes the GOS having a layer structure in one direction in a world set according to a magnification or a use, preferentially from a lower layer.

[0308] The encoding device changes the feature point extraction, object recognition accuracy, or spatial region size included in the indoor and outdoor spaces. However, the encoding device and the decoding device encode or decode the indoor GOS and the outdoor GOS that are close in coordinates as adjacent in the world, and also encode or decode their identifiers in association with each other.

[0309] (Embodiment 2) When using the encoded data of a point cloud in an actual device or service, it is desirable to transmit and receive the necessary information according to the purpose in order to reduce the network bandwidth. However, until now, such a function has not existed in the encoding structure of three-dimensional data, and there has been no encoding method for this purpose.

[0310] In this embodiment, we describe a three-dimensional data encoding method and a three-dimensional data encoding device that provide the function of transmitting and receiving only the information necessary depending on the application in the encoded data of a three-dimensional point cloud, as well as a three-dimensional decoding method and a three-dimensional data device that decodes the encoded data.

[0311] A voxel (VXL) having a certain amount of features or more is defined as a feature voxel (FVXL), and a world (WLD) composed of FVXL is defined as a sparse world (SWLD). FIG. 11 is a diagram showing an example of the configuration of a sparse world and a world. SWLD includes FGOS, which is a GOS composed of FVXL, FSPC, which is an SPC composed of FVXL, and FVLM, which is a VLM composed of FVXL. The data structures and prediction structures of FGOS, FSPS, and FVLM may be the same as those of GOS, SPS, and VLM.

[0312] The feature amount is a feature amount that expresses three-dimensional position information of the VXL or visible light information of the VXL position, and is a feature amount that is often detected especially at corners and edges of a three-dimensional object. Specifically, this feature amount is a three-dimensional feature amount or visible light feature amount as described below, but any feature amount that expresses the position, brightness, or color information of the VXL, etc., may be used.

[0313] As the three-dimensional features, SHOT features (Signature of Histograms of OrienTations), PFH features (Point Feature Histograms), or PPF features (Point Pair Feature) are used.

[0314] The SHOT feature is obtained by dividing the VXL area, calculating the inner product of the reference point and the normal vector of the divided area, and forming a histogram. This SHOT feature has a high dimensionality and is characterized by its high expressiveness.

[0315] The PFH feature is obtained by selecting many pairs of two points near the VXL, calculating normal vectors from those two points, and creating a histogram. Since the PFH feature is a histogram feature, it is robust against some disturbances and has high feature expression power.

[0316] The PPF feature is calculated using normal vectors for each of two VXL points. Since the entire VXL is used for the PPF feature, it is robust against occlusion.

[0317] In addition, as a feature of visible light, Scale-Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF), Histogram of Oriented Gradients (HOG), or the like, which uses information such as luminance gradient information of an image, can be used.

[0318] The SWLD is generated by calculating the above feature amount from each VXL of the WLD and extracting the FVXL. Here, the SWLD may be updated every time the WLD is updated, or may be updated periodically after a certain period of time has elapsed, regardless of the timing of updating the WLD.

[0319] A SWLD may be generated for each feature. For example, a separate SWLD may be generated for each feature, such as SWLD1 based on SHOT features and SWLD2 based on SIFT features, and the SWLDs may be used according to the purpose. Also, the calculated feature of each FVXL may be stored in each FVXL as feature information.

[0320] Next, we explain how to use sparse world learning (SWLD). SWLDs contain only feature voxels (FVXL), so their data size is generally smaller than WLDs that contain all VXL.

[0321] In applications that use features to achieve some purpose, the time required to read from a hard disk, as well as the bandwidth and transfer time required for network transfer, can be reduced by using SWLD information instead of WLD information. For example, by storing WDL and SWLD as map information on a server and switching the map information to be sent to WLD or SWLD depending on the client's request, the network bandwidth and transfer time can be reduced. A specific example is shown below.

[0322] 12 and 13 are diagrams showing examples of using SWLD and WLD. As shown in FIG. 12, when a client 1, which is an in-vehicle device, needs map information for self-location determination, the client 1 sends a request for map data for self-location estimation to the server (S301). The server transmits an SWLD to the client 1 in response to the request (S302). The client 1 performs self-location determination using the received SWLD (S303). At this time, the client 1 obtains VXL information around the client 1 using various methods such as a distance sensor such as a range finder, a stereo camera, or a combination of multiple monocular cameras, and estimates self-location information from the obtained VXL information and SWLD. Here, the self-location information includes three-dimensional position information and orientation of the client 1.

[0323] As shown in Fig. 13, when the client 2, which is an in-vehicle device, needs map information for the purpose of drawing a map such as a three-dimensional map, the client 2 sends a request to the server to obtain map data for map drawing (S311). The server transmits a WLD to the client 2 in response to the request (S312). The client 2 uses the received WLD to draw the map (S313). At this time, the client 2 creates a rendering image using, for example, an image captured by itself using a visible light camera or the like and the WLD obtained from the server, and draws the created image on the screen of a car navigation system or the like.

[0324] As described above, the server transmits SWLD to the client for applications that mainly require the feature values ​​of each VXL, such as self-location estimation, and transmits WLD to the client for applications that require detailed VXL information, such as map drawing. This makes it possible to transmit and receive map data efficiently.

[0325] The client may determine whether it needs a SWLD or a WLD and request the server to send either a SWLD or a WLD. The server may determine whether it should send a SWLD or a WLD depending on the client or network conditions.

[0326] Next, we will explain how to switch between sending and receiving data in the sparse world (SWLD) and the world (WLD).

[0327] It is also possible to switch between receiving the WLD or the SWLD depending on the network bandwidth. Fig. 14 is a diagram showing an example of operation in this case. For example, when a low-speed network with a limited available network bandwidth such as an LTE (Long Term Evolution) environment is used, the client accesses the server via the low-speed network (S321) and acquires the SWLD as map information from the server (S322). On the other hand, when a high-speed network with ample network bandwidth such as a Wi-Fi (registered trademark) environment is used, the client accesses the server via the high-speed network (S323) and acquires the WLD from the server (S324). This allows the client to acquire appropriate map information depending on the network bandwidth of the client.

[0328] Specifically, the client receives SWLD via LTE when outdoors, and obtains WLD via Wi-Fi (registered trademark) when inside a facility, etc. This enables the client to obtain more detailed map information about the indoor area.

[0329] In this way, the client may request a WLD or SWLD from the server depending on the bandwidth of the network that the client uses. Alternatively, the client may send information indicating the bandwidth of the network that the client uses to the server, and the server may send data (WLD or SWLD) suitable for the client depending on the information. Alternatively, the server may determine the network bandwidth of the client and send data (WLD or SWLD) suitable for the client.

[0330] Also, whether to receive the WLD or SWLD may be switched depending on the moving speed. FIG. 15 is a diagram showing an example of the operation in this case. For example, when the client is moving at high speed (S331), the client receives the SWLD from the server (S332). On the other hand, when the client is moving at low speed (S333), the client receives the WLD from the server (S334). This allows the client to obtain map information suited to the speed while suppressing the network bandwidth. Specifically, the client can update rough map information at an appropriate speed by receiving SWLD with a small amount of data while traveling on a highway. On the other hand, the client can obtain more detailed map information by receiving WLD while traveling on an ordinary road.

[0331] In this way, the client may request the server for the WLD or SWLD depending on its own moving speed. Alternatively, the client may transmit information indicating its own moving speed to the server, and the server may transmit data (WLD or SWLD) suitable for the client depending on the information. Alternatively, the server may determine the moving speed of the client and transmit data (WLD or SWLD) suitable for the client.

[0332] Alternatively, the client may first obtain SWLD from the server, and then obtain WLD for important areas from that. For example, when obtaining map data, the client may first obtain rough map information in SWLD, narrow down the map information to areas where buildings, signs, people, or other features appear frequently, and obtain WLD for the narrowed down area later. This allows the client to obtain detailed information for the required area while suppressing the amount of data received from the server.

[0333] Also, the server may create separate SWLDs for each object from the WLD, and the client may receive each according to the purpose. This can reduce network bandwidth. For example, the server may recognize people or cars from the WLD in advance, and create SWLDs for people and SWLDs for cars. The client receives SWLDs for people when it wants to obtain information about people in the vicinity, and SWLDs for cars when it wants to obtain information about cars. Also, the types of SWLDs may be distinguished by information (flags, types, etc.) added to the header, etc.

[0334] Next, the configuration and operation flow of a three-dimensional data encoding device (e.g., a server) according to this embodiment will be described. Fig. 16 is a block diagram of a three-dimensional data encoding device 400 according to this embodiment. Fig. 17 is a flowchart of a three-dimensional data encoding process by the three-dimensional data encoding device 400.

[0335] 16 generates encoded three-dimensional data 413 and 414, which are encoded streams, by encoding input three-dimensional data 411. Here, the encoded three-dimensional data 413 is encoded three-dimensional data corresponding to a WLD, and the encoded three-dimensional data 414 is encoded three-dimensional data corresponding to a SWLD. This three-dimensional data encoding device 400 includes an acquisition unit 401, an encoding region determination unit 402, an SWLD extraction unit 403, a WLD encoding unit 404, and an SWLD encoding unit 405.

[0336] As shown in FIG. 17, first, the acquisition unit 401 acquires input three-dimensional data 411, which is point cloud data in a three-dimensional space (S401).

[0337] Next, the coding region determination unit 402 determines a spatial region to be coded based on the spatial region in which the point cloud data exists (S402).

[0338] Next, the SWLD extraction unit 403 defines the spatial region to be encoded as a WLD, and calculates a feature amount from each VXL included in the WLD.The SWLD extraction unit 403 then extracts VXLs whose feature amount is equal to or greater than a predetermined threshold, defines the extracted VXLs as FVXLs, and adds the FVXLs to the SWLD to generate extracted three-dimensional data 412 (S403).That is, extracted three-dimensional data 412 whose feature amount is equal to or greater than a threshold is extracted from the input three-dimensional data 411.

[0339] Next, the WLD encoding unit 404 generates encoded 3D data 413 corresponding to the WLD by encoding the input 3D data 411 corresponding to the WLD (S404). At this time, the WLD encoding unit 404 adds information to the header of the encoded 3D data 413 for distinguishing that the encoded 3D data 413 is a stream including a WLD.

[0340] Furthermore, the SWLD encoding unit 405 generates encoded three-dimensional data 414 corresponding to the SWLD by encoding the extracted three-dimensional data 412 corresponding to the SWLD (S405). At this time, the SWLD encoding unit 405 adds information to the header of the encoded three-dimensional data 414 for distinguishing that the encoded three-dimensional data 414 is a stream including a SWLD.

[0341] The order of the process for generating the encoded three-dimensional data 413 and the process for generating the encoded three-dimensional data 414 may be reversed. Also, some or all of these processes may be performed in parallel.

[0342] For example, a parameter "world_type" is defined as information to be added to the headers of the encoded 3D data 413 and 414. When world_type=0, it indicates that the stream includes a WLD, and when world_type=1, it indicates that the stream includes a SWLD. When defining many other types, the assigned numerical value may be increased, such as world_type=2. Also, a specific flag may be included in one of the encoded 3D data 413 and 414. For example, a flag indicating that the stream includes a SWLD may be added to the encoded 3D data 414. In this case, the decoding device can determine whether the stream includes a WLD or a SWLD depending on the presence or absence of the flag.

[0343] Furthermore, the encoding method used by the WLD encoding unit 404 when encoding the WLD may be different from the encoding method used by the SWLD encoding unit 405 when encoding the SWLD.

[0344] For example, in SWLD, data is thinned, so that the correlation with surrounding data may be lower than in WLD. Therefore, in the encoding method used in SWLD, among intra prediction and inter prediction, inter prediction may be prioritized over the encoding method used in WLD.

[0345] In addition, the encoding method used for SWLD and the encoding method used for WLD may differ in the way of expressing the three-dimensional position. For example, in SWLD, the three-dimensional position of SVXL may be expressed by three-dimensional coordinates, and in WLD, the three-dimensional position may be expressed by an octree, which will be described later, or vice versa.

[0346] Furthermore, the SWLD encoding unit 405 performs encoding so that the data size of the encoded three-dimensional data 414 of SWLD is smaller than the data size of the encoded three-dimensional data 413 of WLD. For example, as described above, the correlation between data of SWLD may be lower than that of WLD. This may result in a decrease in encoding efficiency, and the data size of the encoded three-dimensional data 414 may be larger than the data size of the encoded three-dimensional data 413 of WLD. Therefore, when the data size of the obtained encoded three-dimensional data 414 is larger than the data size of the encoded three-dimensional data 413 of WLD, the SWLD encoding unit 405 regenerates the encoded three-dimensional data 414 with a reduced data size by performing re-encoding.

[0347] For example, the SWLD extraction unit 403 regenerates the extracted three-dimensional data 412 with a reduced number of extracted feature points, and the SWLD encoding unit 405 encodes the extracted three-dimensional data 412. Alternatively, the degree of quantization in the SWLD encoding unit 405 may be made coarser. For example, in an octree structure described later, the degree of quantization can be made coarser by rounding the data in the lowest layer.

[0348] Furthermore, if the data size of the encoded three-dimensional data 414 of SWLD cannot be made smaller than the data size of the encoded three-dimensional data 413 of WLD, the SWLD encoding unit 405 may not generate the encoded three-dimensional data 414 of SWLD. Alternatively, the encoded three-dimensional data 413 of WLD may be copied to the encoded three-dimensional data 414 of SWLD. In other words, the encoded three-dimensional data 413 of WLD may be used as it is as the encoded three-dimensional data 414 of SWLD.

[0349] Next, the configuration and operation flow of a three-dimensional data decoding device (e.g., a client) according to this embodiment will be described. Fig. 18 is a block diagram of a three-dimensional data decoding device 500 according to this embodiment. Fig. 19 is a flowchart of three-dimensional data decoding processing by the three-dimensional data decoding device 500.

[0350] 18 generates decoded three-dimensional data 512 or 513 by decoding encoded three-dimensional data 511. Here, the encoded three-dimensional data 511 is, for example, the encoded three-dimensional data 413 or 414 generated by the three-dimensional data encoding device 400.

[0351] This three-dimensional data decoding device 500 includes an acquisition unit 501 , a header analysis unit 502 , a WLD decoding unit 503 , and a SWLD decoding unit 504 .

[0352] 19, first, an acquisition unit 501 acquires encoded 3D data 511 (S501). Next, a header analysis unit 502 analyzes the header of the encoded 3D data 511 and determines whether the encoded 3D data 511 is a stream including a WLD or a stream including a SWLD (S502). For example, the above-mentioned world_type parameter is referenced to perform the determination.

[0353] If the encoded three-dimensional data 511 is a stream including a WLD (Yes in S503), the WLD decoding unit 503 generates decoded three-dimensional data 512 of the WLD by decoding the encoded three-dimensional data 511 (S504). On the other hand, if the encoded three-dimensional data 511 is a stream including a SWLD (No in S503), the SWLD decoding unit 504 generates decoded three-dimensional data 513 of the SWLD by decoding the encoded three-dimensional data 511 (S505).

[0354] Also, similarly to the encoding device, the decoding method used by the WLD decoding unit 503 when decoding the WLD may be different from the decoding method used by the SWLD decoding unit 504 when decoding the SWLD. For example, in the decoding method used for the SWLD, inter prediction may be prioritized over the decoding method used for the WLD, out of intra prediction and inter prediction.

[0355] In addition, the decoding method used for SWLD and the decoding method used for WLD may have different methods of expressing three-dimensional positions. For example, in SWLD, the three-dimensional position of SVXL may be expressed by three-dimensional coordinates, and in WLD, the three-dimensional position may be expressed by an octet tree, which will be described later, or vice versa.

[0356] Next, an octree representation, which is a method of representing a three-dimensional position, will be described. The VXL data included in the three-dimensional data is converted into an octree structure and then encoded. FIG. 20 is a diagram showing an example of a VXL in a WLD. FIG. 21 is a diagram showing the octree structure of the WLD shown in FIG. 20. In the example shown in FIG. 20, there are three VXLs VXL1 to 3 that are VXLs (hereinafter, valid VXLs) that include point groups. As shown in FIG. 21, the octree structure is composed of nodes and leaves. Each node has a maximum of eight nodes or leaves. Each leaf has VXL information. Here, among the leaves shown in FIG. 21, leaves 1, 2, and 3 respectively represent VXL1, VXL2, and VXL3 shown in FIG. 20.

[0357] Specifically, each node and leaf corresponds to a three-dimensional position. Node 1 corresponds to the entire block shown in FIG. 20. The block corresponding to node 1 is divided into eight blocks, and among the eight blocks, the block containing a valid VXL is set as a node, and the other blocks are set as leaves. The block corresponding to the node is further divided into eight nodes or leaves, and this process is repeated for the number of layers of the tree structure. Also, all the blocks in the lowest layer are set as leaves.

[0358] FIG. 22 is a diagram showing an example of a SWLD generated from the WLD shown in FIG. 20. As a result of feature extraction, VXL1 and VXL2 shown in FIG. 20 are determined to be FVXL1 and FVXL2, and are added to the SWLD. On the other hand, VXL3 is not determined to be FVXL, and is not included in the SWLD. FIG. 23 is a diagram showing an octree structure of the SWLD shown in FIG. 22. In the octree structure shown in FIG. 23, leaf 3 corresponding to VXL3 shown in FIG. 21 is deleted. As a result, node 3 shown in FIG. 21 no longer has a valid VXL, and is changed to a leaf. In this way, the number of leaves in the SWLD is generally smaller than the number of leaves in the WLD, and the encoded three-dimensional data of the SWLD is also smaller than the encoded three-dimensional data of the WLD.

[0359] A modification of this embodiment will now be described.

[0360] For example, when a client such as an in-vehicle device estimates its own location, it receives an SWLD from a server and estimates its own location using the SWLD. When performing obstacle detection, the client may perform obstacle detection based on three-dimensional information of the surrounding area that it has acquired using various methods such as a distance sensor such as a range finder, a stereo camera, or a combination of multiple monocular cameras.

[0361] In addition, SWLDs generally do not include VXL data for flat areas. Therefore, the server may hold a subsampled world (subWLD) that is a subsample of WLD for static obstacle detection, and transmit SWLD and subWLD to the client. This allows the client to perform self-location estimation and obstacle detection while suppressing network bandwidth.

[0362] Also, when a client wants to quickly draw 3D map data, it may be more convenient for the map information to have a mesh structure. Therefore, the server may generate a mesh from the WLD and store it in advance as a mesh world (MWLD). For example, a client receives an MWLD when it needs a rough 3D drawing, and receives a WLD when it needs a detailed 3D drawing. This can reduce the network bandwidth.

[0363] In addition, the server sets the VXL whose feature amount is equal to or greater than the threshold value as the FVXL among the VXLs, but the FVXL may be calculated by a different method. For example, the server may determine that the VXL, VLM, SPS, or GOS constituting a signal or an intersection is necessary for self-location estimation, driving assistance, or automatic driving, and may include the VXL, VLM, FSPS, or GOS in the SWLD. The above determination may be performed manually. The FVXL, etc. obtained by the above method may be added to the FVXL, etc. set based on the feature amount. That is, the SWLD extraction unit 403 may further extract data corresponding to an object having a predetermined attribute from the input three-dimensional data 411 as the extracted three-dimensional data 412.

[0364] In addition, the fact that it is necessary for those uses may be labeled separately from the feature. In addition, the server may separately hold FVXL necessary for self-location estimation at signals or intersections, driving assistance, autonomous driving, etc., as a higher layer (e.g., lane world) of SWLD.

[0365] The server may also add attributes to the VXL in the WLD for each random access unit or for each predetermined unit. The attributes include, for example, information indicating whether it is necessary or unnecessary for self-location estimation, or information indicating whether it is important as traffic information such as a signal or an intersection. The attributes may also include a correspondence relationship with a feature (such as an intersection or a road) in lane information (such as GDF: Geographic Data Files).

[0366] In addition, the following method may be used as a method for updating the WLD or SWLD.

[0367] Updates, such as changes in people, construction, or tree-lined streets (for trucks), are uploaded to the server as point clouds or metadata. The server updates the WLD based on the upload, and then updates the SWLD with the updated WLD.

[0368] In addition, when the client detects an inconsistency between the 3D information generated by itself during self-location estimation and the 3D information received from the server, the client may transmit the 3D information generated by itself together with an update notification to the server. In this case, the server updates the SWLD using the WLD. If the SWLD is not updated, the server determines that the WLD itself is out of date.

[0369] In addition, although information for distinguishing between WLD and SWLD is added as header information of the encoded stream, when there are many kinds of worlds, such as mesh world and lane world, information for distinguishing them may be added to the header information. In addition, when there are many SWLDs with different features, information for distinguishing them may be added to the header information.

[0370] Although the SWLD is described as being composed of FVXL, it may include VXL that is not determined to be FVXL. For example, the SWLD may include adjacent VXL used when calculating the feature amount of FVXL. This allows the client to calculate the feature amount of FVXL when receiving the SWLD, even if feature amount information is not added to each FVXL in the SWLD. In this case, the SWLD may include information for distinguishing whether each VXL is FVXL or VXL.

[0371] As described above, the three-dimensional data encoding device 400 extracts extracted three-dimensional data 412 (second three-dimensional data) whose features are greater than or equal to a threshold value from the input three-dimensional data 411 (first three-dimensional data), and generates encoded three-dimensional data 414 (first encoded three-dimensional data) by encoding the extracted three-dimensional data 412.

[0372] According to this, the three-dimensional data encoding device 400 generates encoded three-dimensional data 414 by encoding data whose feature amount is equal to or greater than a threshold value. This makes it possible to reduce the amount of data compared to when the input three-dimensional data 411 is encoded as is. Therefore, the three-dimensional data encoding device 400 can reduce the amount of data to be transmitted.

[0373] Moreover, the three-dimensional data encoding device 400 further encodes the input three-dimensional data 411 to generate encoded three-dimensional data 413 (second encoded three-dimensional data).

[0374] According to this, the three-dimensional data encoding device 400 can selectively transmit the encoded three-dimensional data 413 and the encoded three-dimensional data 414 depending on, for example, the intended use.

[0375] Moreover, the extracted three-dimensional data 412 is encoded by a first encoding method, and the input three-dimensional data 411 is encoded by a second encoding method different from the first encoding method.

[0376] This allows the three-dimensional data encoding device 400 to use an encoding method suitable for each of the input three-dimensional data 411 and the extracted three-dimensional data 412.

[0377] Furthermore, in the first encoding method, of intra prediction and inter prediction, inter prediction is given priority over the second encoding method.

[0378] This allows the 3D data encoding device 400 to increase the priority of inter prediction for the extracted 3D data 412 in which the correlation between adjacent data is likely to be low.

[0379] In addition, the first and second encoding methods differ in the way they represent three-dimensional positions. For example, the second encoding method represents three-dimensional positions using an octree, whereas the first encoding method represents three-dimensional positions using three-dimensional coordinates.

[0380] This allows the three-dimensional data encoding device 400 to use a more suitable three-dimensional position expression method for three-dimensional data having a different number of pieces of data (the number of VXLs or SVXLs).

[0381] Furthermore, at least one of the encoded three-dimensional data 413 and 414 includes an identifier indicating whether the encoded three-dimensional data is encoded three-dimensional data obtained by encoding the input three-dimensional data 411, or encoded three-dimensional data obtained by encoding a portion of the input three-dimensional data 411. In other words, the identifier indicates whether the encoded three-dimensional data is encoded three-dimensional data 413 of WLD or encoded three-dimensional data 414 of SWLD.

[0382] This allows the decoding device to easily determine whether the acquired encoded three-dimensional data is encoded three-dimensional data 413 or encoded three-dimensional data 414.

[0383] Furthermore, the three-dimensional data encoding device 400 encodes the extracted three-dimensional data 412 so that the amount of encoded three-dimensional data 414 is smaller than the amount of encoded three-dimensional data 413 .

[0384] According to this, the three-dimensional data encoding device 400 can make the amount of encoded three-dimensional data 414 smaller than the amount of encoded three-dimensional data 413 .

[0385] Moreover, the three-dimensional data encoding device 400 further extracts data corresponding to an object having a predetermined attribute from the input three-dimensional data 411 as extracted three-dimensional data 412. For example, the object having the predetermined attribute is an object necessary for self-location estimation, driving assistance, automatic driving, or the like, such as a traffic light or an intersection.

[0386] This allows the three-dimensional data encoding device 400 to generate encoded three-dimensional data 414 that includes data required by the decoding device.

[0387] Moreover, the three-dimensional data encoding device 400 (server) further transmits one of the encoded three-dimensional data 413 and 414 to the client depending on the state of the client.

[0388] This allows the three-dimensional data encoding device 400 to transmit appropriate data depending on the state of the client.

[0389] The state of the client also includes the communication status of the client (eg, network bandwidth) or the movement speed of the client.

[0390] Moreover, the three-dimensional data encoding device 400 further transmits one of the encoded three-dimensional data 413 and 414 to the client in response to a request from the client.

[0391] This allows the three-dimensional data encoding device 400 to transmit appropriate data in response to a request from a client.

[0392] Moreover, the three-dimensional data decoding device 500 according to this embodiment decodes the encoded three-dimensional data 413 or 414 generated by the three-dimensional data encoding device 400 described above.

[0393] That is, the three-dimensional data decoding device 500 decodes, by a first decoding method, the encoded three-dimensional data 414 obtained by encoding the extracted three-dimensional data 412, the feature amount of which is equal to or greater than a threshold value, extracted from the input three-dimensional data 411. Also, the three-dimensional data decoding device 500 decodes, by a second decoding method different from the first decoding method, the encoded three-dimensional data 413 obtained by encoding the input three-dimensional data 411.

[0394] According to this, the three-dimensional data decoding device 500 can selectively receive the encoded three-dimensional data 414, which is obtained by encoding data whose feature amount is equal to or greater than a threshold value, and the encoded three-dimensional data 413, depending on, for example, the intended use. This allows the three-dimensional data decoding device 500 to reduce the amount of data to be transmitted. Furthermore, the three-dimensional data decoding device 500 can use a decoding method suitable for each of the input three-dimensional data 411 and the extracted three-dimensional data 412.

[0395] Furthermore, in the first decoding method, of intra prediction and inter prediction, inter prediction is given priority over the second decoding method.

[0396] This allows the 3D data decoding device 500 to increase the priority of inter prediction for extracted 3D data in which the correlation between adjacent data is likely to be low.

[0397] In addition, the first and second decoding methods have different methods of expressing three-dimensional positions. For example, in the second decoding method, a three-dimensional position is expressed by an octree, whereas in the first decoding method, a three-dimensional position is expressed by three-dimensional coordinates.

[0398] This allows the three-dimensional data decoding device 500 to use a more suitable three-dimensional position expression method for three-dimensional data having a different number of pieces of data (the number of VXLs or SVXLs).

[0399] Furthermore, at least one of the encoded three-dimensional data 413 and 414 includes an identifier indicating whether the encoded three-dimensional data is encoded three-dimensional data obtained by encoding the input three-dimensional data 411, or encoded three-dimensional data obtained by encoding a portion of the input three-dimensional data 411. The three-dimensional data decoding device 500 identifies the encoded three-dimensional data 413 and 414 by referring to the identifier.

[0400] This allows the three-dimensional data decoding device 500 to easily determine whether the acquired encoded three-dimensional data is the encoded three-dimensional data 413 or the encoded three-dimensional data 414.

[0401] Furthermore, the three-dimensional data decoding device 500 further notifies the server of the state of the client (the three-dimensional data decoding device 500). The three-dimensional data decoding device 500 receives one of the encoded three-dimensional data 413 and 414 transmitted from the server depending on the state of the client.

[0402] This allows the three-dimensional data decoding device 500 to receive appropriate data depending on the state of the client.

[0403] The state of the client also includes the communication status of the client (eg, network bandwidth) or the movement speed of the client.

[0404] Moreover, the three-dimensional data decoding device 500 further requests one of the encoded three-dimensional data 413 and 414 from the server, and receives one of the encoded three-dimensional data 413 and 414 transmitted from the server in response to the request.

[0405] This allows the three-dimensional data decoding device 500 to receive appropriate data according to the application.

[0406] (Embodiment 3) In this embodiment, a method for transmitting and receiving three-dimensional data between vehicles will be described.

[0407] FIG. 24 is a schematic diagram showing the transmission and reception of three-dimensional data 607 between a vehicle 600 and a nearby vehicle 601.

[0408] When acquiring three-dimensional data using a sensor (such as a distance sensor such as a range finder, a stereo camera, or a combination of multiple monocular cameras) mounted on the vehicle 600, an area where three-dimensional data cannot be created (hereinafter, this area is referred to as an occlusion area 604) occurs, even though it is within the sensor detection range 602 of the vehicle 600, due to obstacles such as surrounding vehicles 601. Furthermore, the accuracy of autonomous operation increases as the space for acquiring three-dimensional data becomes larger, but the sensor detection range of the vehicle 600 alone is limited.

[0409] A sensor detection range 602 of the host vehicle 600 includes an area 603 from which three-dimensional data can be acquired and an occlusion area 604. The area from which the host vehicle 600 wishes to acquire three-dimensional data includes the sensor detection range 602 of the host vehicle 600 and other areas. In addition, a sensor detection range 605 of a nearby vehicle 601 includes the occlusion area 604 and an area 606 that is not included in the sensor detection range 602 of the host vehicle 600.

[0410] The surrounding vehicle 601 transmits information detected by the surrounding vehicle 601 to the host vehicle 600. The host vehicle 600 can acquire three-dimensional data 607 of an occlusion region 604 and a region 606 outside the sensor detection range 602 of the host vehicle 600 by acquiring information detected by the surrounding vehicle 601 such as a vehicle ahead. The host vehicle 600 uses the information acquired by the surrounding vehicle 601 to complement the three-dimensional data of the occlusion region 604 and the region 606 outside the sensor detection range.

[0411] The three-dimensional data in the autonomous operation of a vehicle or a robot is used for self-location estimation, detection of surrounding conditions, or both. For example, for self-location estimation, three-dimensional data generated by the vehicle 600 based on sensor information of the vehicle 600 is used. For detection of surrounding conditions, in addition to the three-dimensional data generated by the vehicle 600, three-dimensional data acquired from a surrounding vehicle 601 is also used.

[0412] The surrounding vehicle 601 that transmits the three-dimensional data 607 to the host vehicle 600 may be determined according to the state of the host vehicle 600. For example, the surrounding vehicle 601 is a vehicle ahead when the host vehicle 600 travels straight, an oncoming vehicle when the host vehicle 600 turns right, and a vehicle behind when the host vehicle 600 reverses. Also, the driver of the host vehicle 600 may directly specify the surrounding vehicle 601 that transmits the three-dimensional data 607 to the host vehicle 600.

[0413] Furthermore, the vehicle 600 may search for a surrounding vehicle 601 that possesses three-dimensional data of an area that is included in the space in which the three-dimensional data 607 is to be acquired but cannot be acquired by the vehicle 600. The area that the vehicle 600 cannot acquire is an occlusion area 604 or an area 606 outside the sensor detection range 602, etc.

[0414] Furthermore, the host vehicle 600 may identify the occlusion region 604 based on sensor information of the host vehicle 600. For example, the host vehicle 600 identifies a region included in the sensor detection range 602 of the host vehicle 600, for which three-dimensional data cannot be created, as the occlusion region 604.

[0415] An example of operation will be described below when it is the vehicle ahead that transmits the three-dimensional data 607. Figure 25 is a diagram showing an example of the three-dimensional data transmitted in this case.

[0416] 25, the three-dimensional data 607 transmitted from the vehicle in front is, for example, a sparse world of point cloud (SWLD). That is, the vehicle in front creates three-dimensional data (point cloud) of the WLD from information detected by the sensor of the vehicle in front, and creates three-dimensional data of the SWLD (point cloud) by extracting data whose feature amount is equal to or greater than a threshold value from the three-dimensional data of the WLD. Then, the vehicle in front transmits the created three-dimensional data of the SWLD to the vehicle 600.

[0417] The host vehicle 600 receives the SWLD and merges the received SWLD with the point cloud created by the host vehicle 600.

[0418] The transmitted SWLD has information on absolute coordinates (the position of the SWLD in the coordinate system of the three-dimensional map). The vehicle 600 can realize the merging process by overwriting the point cloud generated by the vehicle 600 based on the absolute coordinates.

[0419] The SWLD transmitted from the nearby vehicle 601 may be the SWLD of an area 606 outside the sensor detection range 602 of the host vehicle 600 and within the sensor detection range 605 of the nearby vehicle 601, or the SWLD of an occlusion area 604 for the host vehicle 600, or both. In addition, the transmitted SWLD may be the SWLD of an area used by the nearby vehicle 601 to detect the surrounding situation among the above SWLDs.

[0420] Furthermore, the surrounding vehicle 601 may change the density of the transmitted point cloud according to the available communication time based on the speed difference between the vehicle itself 600 and the surrounding vehicle 601. For example, when the speed difference is large and the available communication time is short, the surrounding vehicle 601 may lower the density (amount of data) of the point cloud by extracting three-dimensional points with large feature values ​​from the SWLD.

[0421] In addition, detecting the surrounding conditions means determining the presence or absence of people, vehicles, road construction equipment, etc., identifying their types, and detecting their positions, movement direction, movement speed, etc.

[0422] Furthermore, the host vehicle 600 may acquire braking information of the surrounding vehicle 601 instead of or in addition to the three-dimensional data 607 generated by the surrounding vehicle 601. Here, the braking information of the surrounding vehicle 601 is, for example, information indicating that the accelerator or brake of the surrounding vehicle 601 has been depressed or the degree of depression.

[0423] In addition, in the point cloud generated by each vehicle, the three-dimensional space is subdivided into random access units in consideration of low-latency communication between vehicles. On the other hand, in the case of three-dimensional maps, which are map data downloaded from a server, the three-dimensional space is divided into larger random access units compared to the case of vehicle-to-vehicle communication.

[0424] Data for areas that are likely to become occlusion areas, such as the area in front of a leading vehicle or the area behind a trailing vehicle, is divided into small random access units as data for low latency.

[0425] Since the importance of the view in front increases when driving at high speeds, each vehicle creates SWLDs with a narrower field of view in fine random access units when driving at high speeds.

[0426] If the SWLD created by the vehicle in front for transmission includes an area from which the vehicle 600 can acquire point clouds, the vehicle in front may reduce the amount of transmission by removing the point clouds from that area.

[0427] Next, the configuration and operation of a three-dimensional data creation device 620, which is a three-dimensional data receiving device according to this embodiment, will be described.

[0428] 26 is a block diagram of a three-dimensional data creation device 620 according to this embodiment. The three-dimensional data creation device 620 is included in the above-mentioned vehicle 600, for example, and creates a more detailed third three-dimensional data 636 by synthesizing the first three-dimensional data 632 created by the three-dimensional data creation device 620 with the received second three-dimensional data 635.

[0429] This three-dimensional data creation device 620 includes a three-dimensional data creation unit 621, a requested range determination unit 622, a search unit 623, a reception unit 624, a decoding unit 625, and a synthesis unit 626. FIG.

[0430] First, the three-dimensional data creation unit 621 creates first three-dimensional data 632 using sensor information 631 detected by a sensor equipped in the vehicle 600 (S621). Next, the required range determination unit 622 determines a required range, which is a three-dimensional spatial range for which data is insufficient, in the created first three-dimensional data 632 (S622).

[0431] Next, the search unit 623 searches for nearby vehicles 601 that have three-dimensional data in the requested range, and transmits requested range information 633 indicating the requested range to the nearby vehicles 601 identified by the search (S623). Next, the reception unit 624 receives encoded three-dimensional data 634, which is an encoded stream of the requested range, from the nearby vehicles 601 (S624). Note that the search unit 623 may indiscriminately issue a request to all vehicles present in a specific range, and receive the encoded three-dimensional data 634 from those that respond. Also, the search unit 623 may issue a request to objects such as traffic lights or signs, not limited to vehicles, and receive the encoded three-dimensional data 634 from the objects.

[0432] Next, the decoding unit 625 obtains second three-dimensional data 635 by decoding the received encoded three-dimensional data 634 (S625). Next, the synthesis unit 626 creates denser third three-dimensional data 636 by synthesizing the first three-dimensional data 632 and the second three-dimensional data 635 (S626).

[0433] Next, a configuration and operation of three-dimensional data transmission device 640 according to this embodiment will be described.

[0434] The three-dimensional data transmission device 640 is, for example, included in the surrounding vehicle 601 described above, processes the fifth three-dimensional data 652 created by the surrounding vehicle 601 into sixth three-dimensional data 654 requested by the host vehicle 600, encodes the sixth three-dimensional data 654 to generate encoded three-dimensional data 634, and transmits the encoded three-dimensional data 634 to the host vehicle 600.

[0435] The three-dimensional data transmission device 640 includes a three-dimensional data creation unit 641, a receiving unit 642, an extracting unit 643, an encoding unit 644, and a transmitting unit 645. FIG.

[0436] First, the three-dimensional data creation unit 641 creates fifth three-dimensional data 652 using sensor information 651 detected by a sensor equipped in the surrounding vehicle 601 (S641). Next, the receiving unit 642 receives the requested range information 633 transmitted from the host vehicle 600 (S642).

[0437] Next, the extraction unit 643 processes the fifth three-dimensional data 652 into sixth three-dimensional data 654 by extracting three-dimensional data of the requested range indicated by the requested range information 633 from the fifth three-dimensional data 652 (S643). Next, the encoding unit 644 generates encoded three-dimensional data 634, which is an encoded stream, by encoding the sixth three-dimensional data 654 (S644). Then, the transmission unit 645 transmits the encoded three-dimensional data 634 to the host vehicle 600 (S645).

[0438] Here, an example is described in which the vehicle itself 600 is equipped with a three-dimensional data creation device 620 and the surrounding vehicle 601 is equipped with a three-dimensional data transmission device 640, but each vehicle may have the functions of both the three-dimensional data creation device 620 and the three-dimensional data transmission device 640.

[0439] Hereinafter, a configuration and operation will be described in a case where the three-dimensional data creation device 620 is a surrounding situation detection device that realizes detection processing of the surrounding situation of the vehicle 600. FIG. 30 is a block diagram showing the configuration of the three-dimensional data creation device 620A in this case. The three-dimensional data creation device 620A shown in FIG. 30 further includes a detection region determination unit 627, a surrounding situation detection unit 628, and an autonomous operation control unit 629 in addition to the configuration of the three-dimensional data creation device 620 shown in FIG. 26. The three-dimensional data creation device 620A is included in the vehicle 600.

[0440] FIG. 31 is a flowchart of the process of detecting the surrounding conditions of the vehicle 600 by the three-dimensional data creation device 620A.

[0441] First, the three-dimensional data creation unit 621 creates first three-dimensional data 632, which is a point cloud, using sensor information 631 of the detection range of the vehicle 600 detected by a sensor equipped in the vehicle 600 (S661). The three-dimensional data creation device 620A may further perform self-position estimation using the sensor information 631.

[0442] Next, the detection area determination unit 627 determines a detection target range, which is a spatial area in which the surrounding situation is to be detected (S662). For example, the detection area determination unit 627 calculates an area necessary for detecting the surrounding situation for safely performing the autonomous operation according to the autonomous operation (automatic driving) situation such as the traveling direction and speed of the vehicle 600, and determines the area as the detection target range.

[0443] Next, the required range determination unit 622 determines the occlusion region 604 and a spatial region that is outside the detection range of the sensor of the host vehicle 600 but is necessary for detecting the surrounding conditions as a required range (S663).

[0444] If the requested range determined in step S663 exists (Yes in S664), the search unit 623 searches for nearby vehicles that have information about the requested range. For example, the search unit 623 may inquire of the nearby vehicles whether they have information about the requested range, or may determine whether the nearby vehicles have information about the requested range based on the positions of the requested range and the nearby vehicles. Next, the search unit 623 transmits a request signal 637 to the nearby vehicles 601 identified by the search, requesting transmission of three-dimensional data. Then, after receiving a permission signal transmitted from the nearby vehicles 601 indicating that the request of the request signal 637 is accepted, the search unit 623 transmits requested range information 633 indicating the requested range to the nearby vehicles 601 (S665).

[0445] Next, the receiving unit 624 detects a transmission notification of the transmission data 638, which is information related to the requested range, and receives the transmission data 638 (S666).

[0446] The three-dimensional data creation device 620A may indiscriminately send a request to all vehicles present within a specific range without searching for a party to send the request to, and receive the transmission data 638 from the party that responds that it has information about the requested range. The search unit 623 may also send a request to an object, such as a traffic light or a sign, and receive the transmission data 638 from the object, in addition to a vehicle.

[0447] The transmission data 638 also includes at least one of the encoded three-dimensional data 634 generated by the nearby vehicle 601 and obtained by encoding the three-dimensional data of the requested range, and the surrounding condition detection result 639 of the requested range. The surrounding condition detection result 639 indicates the positions, moving direction, moving speed, etc. of people and vehicles detected by the nearby vehicle 601. The transmission data 638 may also include information indicating the position, movement, etc. of the nearby vehicle 601. For example, the transmission data 638 may include braking information of the nearby vehicle 601.

[0448] When the received transmission data 638 includes the encoded three-dimensional data 634 (Yes in S667), the decoding unit 625 obtains the second three-dimensional data 635 of the SWLD by decoding the encoded three-dimensional data 634 (S668). In other words, the second three-dimensional data 635 is three-dimensional data (SWLD) generated by extracting data whose feature amount is equal to or greater than a threshold value from the fourth three-dimensional data (WLD).

[0449] Next, the synthesis unit 626 generates third three-dimensional data 636 by synthesizing the first three-dimensional data 632 and the second three-dimensional data 635 (S669).

[0450] Next, the surrounding condition detection unit 628 detects the surrounding condition of the host vehicle 600 by using the third three-dimensional data 636, which is a point cloud of a spatial region required for the surrounding condition detection (S670). When the received transmission data 638 includes a surrounding condition detection result 639, the surrounding condition detection unit 628 detects the surrounding condition of the host vehicle 600 by using the surrounding condition detection result 639 in addition to the third three-dimensional data 636. When the received transmission data 638 includes braking information of the surrounding vehicle 601, the surrounding condition detection unit 628 detects the surrounding condition of the host vehicle 600 by using the braking information in addition to the third three-dimensional data 636.

[0451] Next, the autonomous operation control unit 629 controls the autonomous operation (automatic driving) of the vehicle 600 based on the surrounding situation detection result by the surrounding situation detection unit 628 (S671). Note that the surrounding situation detection result may be presented to the driver through a UI (user interface) or the like.

[0452] On the other hand, if the requested range does not exist in step S663 (No in S664), that is, if information on all spatial regions necessary for surrounding condition detection has been created based on the sensor information 631, the surrounding condition detection unit 628 detects the surrounding conditions of the host vehicle 600 using first three-dimensional data 632, which is a point cloud of the spatial regions necessary for surrounding condition detection (S672). Then, the autonomous operation control unit 629 controls the autonomous operation (automatic driving) of the host vehicle 600 based on the surrounding condition detection result by the surrounding condition detection unit 628 (S671).

[0453] Furthermore, if the received transmission data 638 does not include the encoded three-dimensional data 634 (No in S667), that is, if the transmission data 638 includes only the surrounding conditions detection result 639 or braking information of the surrounding vehicle 601, the surrounding conditions detection unit 628 detects the surrounding conditions of the host vehicle 600 using the first three-dimensional data 632 and the surrounding conditions detection result 639 or braking information (S673). Then, the autonomous operation control unit 629 controls the autonomous operation (automatic driving) of the host vehicle 600 based on the surrounding conditions detection result by the surrounding conditions detection unit 628 (S671).

[0454] Next, a description will be given of three-dimensional data transmission device 640A which transmits transmission data 638 to three-dimensional data creation device 620A. Fig. 32 is a block diagram of this three-dimensional data transmission device 640A.

[0455] Three-dimensional data transmission device 640A shown in Fig. 32 further includes a transmission possibility determination unit 646 in addition to the configuration of three-dimensional data transmission device 640 shown in Fig. 28. Furthermore, three-dimensional data transmission device 640A is included in nearby vehicle 601.

[0456] 33 is a flowchart showing an example of the operation of three-dimensional data transmission device 640A. First, three-dimensional data creation unit 641 creates fifth three-dimensional data 652 using sensor information 651 detected by a sensor equipped in surrounding vehicle 601 (S681).

[0457] Next, the receiving unit 642 receives a request signal 637 from the vehicle 600 requesting transmission of three-dimensional data (S682). Next, the transmission feasibility determination unit 646 determines whether to comply with the request indicated by the request signal 637 (S683). For example, the transmission feasibility determination unit 646 determines whether to comply with the request based on the contents preset by the user. Note that the receiving unit 642 may first receive a request from the other party, such as a requested range, and the transmission feasibility determination unit 646 may determine whether to comply with the request based on the contents. For example, the transmission feasibility determination unit 646 may determine to comply with the request when it has three-dimensional data in the requested range, and may determine not to comply with the request when it does not have three-dimensional data in the requested range.

[0458] If the request is accepted (Yes in S683), the three-dimensional data transmission device 640A transmits a permission signal to the vehicle 600, and the receiver 642 receives requested range information 633 indicating the requested range (S684). Next, the extractor 643 extracts a point cloud of the requested range from the fifth three-dimensional data 652, which is a point cloud, and creates transmission data 638 including sixth three-dimensional data 654, which is the SWLD of the extracted point cloud (S685).

[0459] That is, the three-dimensional data transmission device 640A creates seventh three-dimensional data (WLD) from the sensor information 651, and creates fifth three-dimensional data 652 (SWLD) by extracting data whose feature amount is equal to or greater than a threshold value from the seventh three-dimensional data (WLD). Note that the three-dimensional data creation unit 641 may create three-dimensional data of SWLD in advance, and the extraction unit 643 may extract three-dimensional data of SWLD in the requested range from the three-dimensional data of SWLD, or the extraction unit 643 may generate three-dimensional data of SWLD in the requested range from the three-dimensional data of WLD in the requested range.

[0460] Furthermore, the transmission data 638 may include surrounding condition detection result 639 of the requested range by the surrounding vehicle 601 and braking information of the surrounding vehicle 601. Furthermore, the transmission data 638 may not include the sixth three-dimensional data 654, and may include only at least one of the surrounding condition detection result 639 of the requested range by the surrounding vehicle 601 and the braking information of the surrounding vehicle 601.

[0461] If the transmission data 638 includes the sixth three-dimensional data 654 (Yes in S686), the encoding unit 644 generates the encoded three-dimensional data 634 by encoding the sixth three-dimensional data 654 (S687).

[0462] Then, the transmitting unit 645 transmits the transmission data 638 including the encoded three-dimensional data 634 to the host vehicle 600 (S688).

[0463] On the other hand, if the transmission data 638 does not include the sixth three-dimensional data 654 (No in S686), the transmission unit 645 transmits the transmission data 638 including at least one of the surrounding condition detection result 639 of the requested range by the surrounding vehicle 601 and braking information of the surrounding vehicle 601 to the host vehicle 600 (S688).

[0464] A modification of this embodiment will now be described.

[0465] For example, the information transmitted from the surrounding vehicle 601 does not have to be three-dimensional data or surrounding situation detection results created by the surrounding vehicle, but may be accurate feature point information of the surrounding vehicle 601 itself. The host vehicle 600 uses the feature point information of the surrounding vehicle 601 to correct the feature point information of the leading vehicle in the point cloud acquired by the host vehicle 600. This allows the host vehicle 600 to improve the matching accuracy when estimating its own position.

[0466] The feature point information of the vehicle ahead is, for example, three-dimensional point information consisting of color information and coordinate information. This allows the feature point information of the vehicle ahead to be used regardless of the type of sensor of the host vehicle 600, whether it is a laser sensor or a stereo camera.

[0467] The vehicle 600 may use the point cloud of the SWLD not only during transmission but also when calculating the accuracy of the self-location estimation. For example, when the sensor of the vehicle 600 is an imaging device such as a stereo camera, the vehicle 600 detects two-dimensional points on an image captured by the camera and estimates the self-location using the two-dimensional points. The vehicle 600 also creates a point cloud of surrounding objects at the same time as the vehicle 600 detects the self-location. The vehicle 600 reprojects the three-dimensional points of the SWLD in the point cloud onto the two-dimensional image and evaluates the accuracy of the self-location estimation based on the error between the detected points and the reprojected points on the two-dimensional image.

[0468] In addition, if the sensor of the vehicle 600 is a laser sensor such as LIDAR, the vehicle 600 evaluates the accuracy of its own position estimation based on the error calculated by Iterative Closest Point using the SWLD of the created point cloud and the SWLD of the three-dimensional map.

[0469] In addition, when communication conditions via a base station or server such as 5G are poor, the vehicle 600 may acquire a three-dimensional map from a nearby vehicle 601.

[0470] Further, the vehicle 600 may obtain information about distant locations that cannot be obtained from vehicles surrounding the vehicle 600 by vehicle-to-vehicle communication. For example, the vehicle 600 may obtain information about traffic accidents that occur immediately after they occur several hundred meters or kilometers away from an oncoming vehicle by passing by another vehicle, or by a relay method in which information is transmitted to surrounding vehicles in sequence. At this time, the data format of the transmitted data is transmitted as meta information of the upper layer of the dynamic three-dimensional map.

[0471] Furthermore, the detection result of the surrounding situation and the information detected by the vehicle 600 may be presented to the user through a user interface. For example, the information is presented on the screen of a car navigation system or by being superimposed on the front window.

[0472] In addition, a vehicle that does not support autonomous driving and has cruise control may discover nearby vehicles that are driving in autonomous driving mode and follow those nearby vehicles.

[0473] Furthermore, when the vehicle 600 is unable to estimate its own position because it is unable to acquire a three-dimensional map or there are too many occlusion areas, the vehicle 600 may switch its operation mode from an autonomous driving mode to a surrounding vehicle tracking mode.

[0474] In addition, the vehicle being tracked may be equipped with a user interface that warns the user that the vehicle is being tracked and allows the user to specify whether or not to allow the tracking. In this case, a mechanism may be provided in which advertisements are displayed on the tracking vehicle and incentives are paid to the vehicle being tracked.

[0475] The information to be transmitted is based on SWLD, which is three-dimensional data, but may be information according to a request setting set in the vehicle 600 or a public setting of the vehicle ahead. For example, the information to be transmitted may be WLD, which is a dense point cloud, the detection result of the surrounding situation by the vehicle ahead, or braking information of the vehicle ahead.

[0476] Furthermore, the vehicle 600 may receive the WLD, visualize the three-dimensional data of the WLD, and present the visualized three-dimensional data to the driver using a GUI. In this case, the vehicle 600 may present information by applying color coding or the like to enable the user to distinguish between the point cloud created by the vehicle 600 and the received point cloud.

[0477] In addition, when the vehicle 600 presents the information detected by the vehicle 600 and the detection results of the surrounding vehicle 601 to the driver via a GUI, the information may be color-coded or the like so that the user can distinguish between the information detected by the vehicle 600 and the received detection results.

[0478] As described above, in the three-dimensional data creation device 620 according to this embodiment, the three-dimensional data creation unit 621 creates first three-dimensional data 632 from sensor information 631 detected by a sensor. The receiving unit 624 receives encoded three-dimensional data 634 in which second three-dimensional data 635 is encoded. The decoding unit 625 obtains second three-dimensional data 635 by decoding the received encoded three-dimensional data 634. The combining unit 626 creates third three-dimensional data 636 by combining the first three-dimensional data 632 and the second three-dimensional data 635.

[0479] According to this, the three-dimensional data creation device 620 can create detailed third three-dimensional data 636 using the created first three-dimensional data 632 and the received second three-dimensional data 635.

[0480] Furthermore, the synthesis unit 626 synthesizes the first three-dimensional data 632 and the second three-dimensional data 635 to generate third three-dimensional data 636 having a higher density than the first three-dimensional data 632 and the second three-dimensional data 635.

[0481] Also, the second three-dimensional data 635 (for example, SWLD) is three-dimensional data generated by extracting data whose feature amount is equal to or greater than a threshold value from the fourth three-dimensional data (for example, WLD).

[0482] This allows the three-dimensional data creation device 620 to reduce the amount of three-dimensional data to be transmitted.

[0483] Moreover, the three-dimensional data creation device 620 further includes a search unit 623 that searches for a transmission device that is the transmission source of the encoded three-dimensional data 634. The reception unit 624 receives the encoded three-dimensional data 634 from the searched transmission device.

[0484] According to this, the three-dimensional data creation device 620 can, for example, identify a transmission device that has the required three-dimensional data by searching.

[0485] The three-dimensional data creation device further includes a requested range determination unit 622 that determines a requested range, which is a range of the three-dimensional space for which three-dimensional data is requested. The search unit 623 transmits requested range information 633 indicating the requested range to the transmitting device. The second three-dimensional data 635 includes the three-dimensional data of the requested range.

[0486] This allows the three-dimensional data creation device 620 to receive necessary three-dimensional data, while reducing the amount of three-dimensional data to be transmitted.

[0487] Furthermore, the required range determination unit 622 determines a spatial range including an occlusion region 604 that cannot be detected by the sensor as the required range.

[0488] Furthermore, in the three-dimensional data transmission device 640 according to this embodiment, the three-dimensional data creation unit 641 creates fifth three-dimensional data 652 from sensor information 651 detected by a sensor. The extraction unit 643 creates sixth three-dimensional data 654 by extracting a part of the fifth three-dimensional data 652. The encoding unit 644 generates encoded three-dimensional data 634 by encoding the sixth three-dimensional data 654. The transmission unit 645 transmits the encoded three-dimensional data 634.

[0489] This allows the three-dimensional data transmission device 640 to transmit the three-dimensional data it has created to other devices, and also allows the amount of three-dimensional data to be transmitted to be reduced.

[0490] In addition, the three-dimensional data creation unit 641 creates seventh three-dimensional data (e.g., WLD) from sensor information 651 detected by the sensor, and creates fifth three-dimensional data 652 (e.g., SWLD) by extracting data whose features are greater than or equal to a threshold value from the seventh three-dimensional data.

[0491] This allows the three-dimensional data transmission device 640 to reduce the amount of three-dimensional data to be transmitted.

[0492] The three-dimensional data transmitting device 640 further includes a receiving unit 642 that receives, from the receiving device, requested range information 633 indicating a requested range, which is a range of three-dimensional space for which three-dimensional data is requested. The extracting unit 643 creates sixth three-dimensional data 654 by extracting three-dimensional data of the requested range from the fifth three-dimensional data 652. The transmitting unit 645 transmits the encoded three-dimensional data 634 to the receiving device.

[0493] This allows the three-dimensional data transmission device 640 to reduce the amount of three-dimensional data to be transmitted.

[0494] (Embodiment 4) In this embodiment, the operation of an abnormality system in self-location estimation based on a three-dimensional map will be described.

[0495] It is expected that applications such as self-driving cars, or autonomous movement of mobile objects such as robots or flying objects such as drones will expand in the future. One example of a means for realizing such autonomous movement is a method in which a mobile object estimates its own position within a three-dimensional map (self-location estimation) and travels according to the map.

[0496] Self-location estimation can be achieved by matching a 3D map with 3D information about the surroundings of the vehicle (hereinafter referred to as vehicle-detected 3D data) obtained by sensors such as a range finder (such as LiDAR) or a stereo camera mounted on the vehicle, and estimating the vehicle's position within the 3D map.

[0497] A 3D map, such as the HD map proposed by HERE, may include not only a 3D point cloud, but also 2D map data such as shape information of roads and intersections, or information that changes in real time such as traffic jams and accidents. A 3D map is made up of multiple layers such as 3D data, 2D data, and metadata that changes in real time, and a device can obtain or refer to only the necessary data.

[0498] The point cloud data may be the above-mentioned SWLD, or may include point group data other than feature points. Furthermore, the transmission and reception of the point cloud data is performed on a basis of one or multiple random access units.

[0499] The following methods can be used as a method for matching the 3D map with the vehicle-detected 3D data. For example, the device compares the shapes of the point groups in each point cloud, and determines that parts with high similarity between feature points are in the same position. In addition, when the 3D map is composed of SWLDs, the device performs matching by comparing the feature points that compose the SWLDs with the 3D feature points extracted from the vehicle-detected 3D data.

[0500] Here, to estimate the vehicle's position with high accuracy, (A) it is necessary to acquire a 3D map and 3D vehicle detection data, and (B) the accuracy of these must satisfy a predetermined standard. However, in the following abnormal cases, (A) or (B) cannot be satisfied.

[0501] (1) 3D maps cannot be obtained via communication.

[0502] (2) The 3D map does not exist, or the 3D map has been acquired but is corrupted.

[0503] (3) The vehicle's sensor is out of order or the weather is bad, so the accuracy of generating the vehicle-detected 3D data is insufficient.

[0504] The operation for dealing with these abnormal cases will be described below. Although the operation will be described below using a car as an example, the following method can be applied to any autonomously moving animal, such as a robot or a drone.

[0505] The configuration and operation of a three-dimensional information processing device according to this embodiment for dealing with abnormal cases in a three-dimensional map or vehicle-detected three-dimensional data will be described below. Fig. 34 is a block diagram showing an example of the configuration of a three-dimensional information processing device 700 according to this embodiment. Fig. 35 is a flowchart of a three-dimensional information processing method by the three-dimensional information processing device 700.

[0506] The three-dimensional information processing device 700 is mounted on a moving object such as an automobile. As shown in FIG. 34 , the three-dimensional information processing device 700 includes a three-dimensional map acquisition unit 701, a host vehicle detection data acquisition unit 702, an abnormality case determination unit 703, a countermeasure operation decision unit 704, and an operation control unit 705.

[0507] The three-dimensional information processing device 700 may include a two-dimensional or one-dimensional sensor (not shown) for detecting structures or animals around the vehicle, such as a camera for acquiring a two-dimensional image, or a sensor for one-dimensional data using ultrasonic waves or a laser. The three-dimensional information processing device 700 may also include a communication unit (not shown) for acquiring a three-dimensional map through a mobile communication network such as 4G or 5G, or through vehicle-to-vehicle communication or road-to-vehicle communication.

[0508] 35, the three-dimensional map acquisition unit 701 acquires a three-dimensional map 711 of the vicinity of the travel route (S701). For example, the three-dimensional map acquisition unit 701 acquires the three-dimensional map 711 through a mobile communication network, vehicle-to-vehicle communication, or road-to-vehicle communication.

[0509] Next, the vehicle detection data acquisition unit 702 acquires the vehicle detection three-dimensional data 712 based on the sensor information (S702). For example, the vehicle detection data acquisition unit 702 generates the vehicle detection three-dimensional data 712 based on sensor information acquired by a sensor equipped in the vehicle.

[0510] Next, the abnormality case determination unit 703 detects an abnormality case by performing a predetermined check on at least one of the acquired three-dimensional map 711 and the host vehicle detection three-dimensional data 712 (S703). In other words, the abnormality case determination unit 703 determines whether at least one of the acquired three-dimensional map 711 and the host vehicle detection three-dimensional data 712 is abnormal.

[0511] In step S703, if an abnormal case is detected (Yes in S704), the countermeasure operation determination unit 704 determines a countermeasure operation for the abnormal case (S705). Next, the operation control unit 705 controls the operation of each processing unit required for carrying out the countermeasure operation, such as the three-dimensional map acquisition unit 701 (S706).

[0512] On the other hand, if no abnormal case is detected in step S703 (No in S704), the three-dimensional information processing apparatus 700 ends the process.

[0513] Furthermore, the three-dimensional information processing device 700 uses the three-dimensional map 711 and the vehicle-detected three-dimensional data 712 to estimate the self-position of the vehicle having the three-dimensional information processing device 700. Next, the three-dimensional information processing device 700 automatically drives the vehicle using the result of the self-position estimation.

[0514] In this way, the three-dimensional information processing device 700 acquires map data (three-dimensional map 711) including the first three-dimensional position information via a communication path. For example, the first three-dimensional position information is encoded in units of subspaces having three-dimensional coordinate information, and each is a collection of one or more subspaces, and includes a plurality of random access units that can be independently decoded. For example, the first three-dimensional position information is data (SWLD) in which feature points whose three-dimensional feature amount is equal to or greater than a predetermined threshold value are encoded.

[0515] Furthermore, the three-dimensional information processing device 700 generates second three-dimensional position information (vehicle-detected three-dimensional data 712) from information detected by the sensor. Next, the three-dimensional information processing device 700 performs an abnormality determination process on the first three-dimensional position information or the second three-dimensional position information to determine whether the first three-dimensional position information or the second three-dimensional position information is abnormal.

[0516] When the first three-dimensional position information or the second three-dimensional position information is determined to be abnormal, the three-dimensional information processing apparatus 700 determines a countermeasure action for the abnormality. Next, the three-dimensional information processing apparatus 700 performs control required for carrying out the countermeasure action.

[0517] This allows the three-dimensional information processing apparatus 700 to detect an abnormality in the first three-dimensional position information or the second three-dimensional position information, and to take appropriate action.

[0518] The following describes an abnormality case 1, which is a countermeasure operation for when the three-dimensional map 711 cannot be acquired via communication.

[0519] A three-dimensional map 711 is necessary for self-location estimation, and if the vehicle does not previously acquire the three-dimensional map 711 corresponding to the route to the destination, the vehicle must acquire the three-dimensional map 711 through communication. However, due to congestion on the communication path or deterioration of radio wave reception, the vehicle may not be able to acquire the three-dimensional map 711 of the traveling route.

[0520] The abnormality case determination unit 703 checks whether three-dimensional maps 711 have been acquired for all sections on the route to the destination or for sections within a predetermined range from the current position, and if they have not been acquired, determines that the abnormality case is 1. In other words, the abnormality case determination unit 703 determines whether the three-dimensional map 711 (first three-dimensional position information) can be acquired via a communication path, and if the three-dimensional map 711 cannot be acquired via the communication path, determines that the three-dimensional map 711 is abnormal.

[0521] If it is determined to be abnormal case 1, the countermeasure action determination section 704 selects one of two types of countermeasure action: (1) continuing self-location estimation, and (2) stopping self-location estimation.

[0522] First, a specific example of (1) a countermeasure operation when continuing self-location estimation will be described. When continuing self-location estimation, a three-dimensional map 711 on the route to the destination is required.

[0523] For example, the vehicle determines a location where a communication path is available within a range where the three-dimensional map 711 has already been acquired, moves to that location, and acquires the three-dimensional map 711. At this time, the vehicle may acquire all three-dimensional maps 711 up to the destination, or may acquire the three-dimensional map 711 for each random access unit within the upper limit size that can be stored in a recording unit such as the memory or HDD of the vehicle.

[0524] The vehicle may separately acquire the communication state on the route, and when it is predicted that the communication state on the route will be poor, it may operate to acquire the three-dimensional map 711 of the section in advance before reaching the section where the communication state is poor, or to acquire the three-dimensional map 711 of the maximum range that can be acquired. In other words, the three-dimensional information processing device 700 predicts whether the vehicle will enter an area where the communication state is poor. When it is predicted that the vehicle will enter an area where the communication state is poor, the three-dimensional information processing device 700 acquires the three-dimensional map 711 before the vehicle enters the area.

[0525] Furthermore, the vehicle may identify a random access unit constituting a minimum three-dimensional map 711 necessary for estimating the vehicle's position on the route, which is a range narrower than usual, and may receive the identified random access unit. In other words, when the three-dimensional information processing device 700 cannot acquire the three-dimensional map 711 (first three-dimensional position information) via a communication path, the three-dimensional information processing device 700 may acquire third three-dimensional position information having a narrower range than the first three-dimensional position information via the communication path.

[0526] In addition, when the vehicle is unable to access a distribution server for the three-dimensional map 711, the vehicle may obtain the three-dimensional map 711 from a moving object that has already obtained the three-dimensional map 711 on the route to the destination, such as another vehicle traveling around the vehicle, and that can communicate with the vehicle.

[0527] Next, a specific example of the countermeasure operation when (2) self-location estimation is stopped will be described. In this case, the three-dimensional map 711 on the route to the destination is not required.

[0528] For example, the vehicle notifies the driver that functions such as autonomous driving based on self-location estimation cannot be continued, and transitions the operating mode to a manual mode in which the driver drives the vehicle.

[0529] Usually, when self-location estimation is performed, autonomous driving is performed, although the level varies depending on the degree of human intervention. On the other hand, the result of self-location estimation can also be used as navigation when a person is driving. Therefore, the result of self-location estimation does not necessarily have to be used for autonomous driving.

[0530] In addition, when a normally used communication path, such as a mobile communication network such as 4G or 5G, is unavailable, the vehicle may check whether the three-dimensional map 711 can be obtained via another communication path, such as road-to-vehicle Wi-Fi (registered trademark) or millimeter wave communication, or vehicle-to-vehicle communication, and switch the communication path to be used to a communication path that can obtain the three-dimensional map 711.

[0531] Furthermore, when the three-dimensional map 711 cannot be acquired, the vehicle may acquire a two-dimensional map and continue autonomous driving using the two-dimensional map and the vehicle-detected three-dimensional data 712. In other words, when the three-dimensional information processing device 700 cannot acquire the three-dimensional map 711 via a communication path, the three-dimensional information processing device 700 may acquire map data including two-dimensional position information (two-dimensional map) via a communication path and estimate the vehicle's own position using the two-dimensional position information and the vehicle-detected three-dimensional data 712.

[0532] Specifically, the vehicle uses a two-dimensional map and vehicle-detected three-dimensional data 712 for self-location estimation, and uses the vehicle-detected three-dimensional data 712 for detection of surrounding vehicles, pedestrians, obstacles, and the like.

[0533] Here, map data such as an HD map can include, in addition to a three-dimensional map 711 consisting of a three-dimensional point cloud, two-dimensional map data (two-dimensional map), simplified map data in which characteristic information such as road shapes or intersections is extracted from the two-dimensional map data, and metadata representing real-time information such as traffic congestion, accidents, construction, etc. For example, the map data has a layer structure in which, from the lowest layer, three-dimensional data (three-dimensional map 711), two-dimensional data (two-dimensional map), and metadata are arranged.

[0534] Here, the data size of two-dimensional data is smaller than that of three-dimensional data. Therefore, even if the communication state is poor, the vehicle may be able to acquire a two-dimensional map. Alternatively, the vehicle may acquire a wide range of two-dimensional maps collectively in a section where the communication state is good. Therefore, when the communication path state is poor and it is difficult to acquire the three-dimensional map 711, the vehicle may receive a layer including the two-dimensional map without receiving the three-dimensional map 711. Note that since the data size of the metadata is small, for example, the vehicle always receives the metadata regardless of the communication state.

[0535] There are, for example, the following two methods for estimating the vehicle's position using a two-dimensional map and the vehicle-detected three-dimensional data 712.

[0536] The first method is a method of matching two-dimensional features. Specifically, the vehicle extracts two-dimensional features from the vehicle-detected three-dimensional data 712 and matches the extracted two-dimensional features with a two-dimensional map.

[0537] For example, the vehicle projects the vehicle-detected three-dimensional data 712 onto the same plane as the two-dimensional map, and matches the obtained two-dimensional data with the two-dimensional map using two-dimensional image features extracted from both.

[0538] When the three-dimensional map 711 includes the SWLD, the three-dimensional map 711 may store two-dimensional features in the same plane as the two-dimensional map together with three-dimensional features at feature points in the three-dimensional space. For example, identification information is assigned to the two-dimensional features. Alternatively, the two-dimensional features are stored in a layer separate from the three-dimensional data and the two-dimensional map, and the vehicle acquires data of the two-dimensional features together with the two-dimensional map.

[0539] When a two-dimensional map shows information on locations that are at different heights from the ground (not on the same plane), such as white lines on a road, guardrails, and buildings, on the same map, the vehicle extracts features from multiple height data in the vehicle-detected three-dimensional data 712.

[0540] Furthermore, information indicating the correspondence between feature points in the two-dimensional map and feature points in the three-dimensional map 711 may be stored as meta-information of the map data.

[0541] The second method is a method of matching three-dimensional feature amounts. Specifically, the vehicle acquires three-dimensional feature amounts corresponding to feature points in the two-dimensional map, and matches the acquired three-dimensional feature amounts with the three-dimensional feature amounts of the vehicle-detected three-dimensional data 712.

[0542] Specifically, three-dimensional feature values ​​corresponding to feature points in the two-dimensional map are stored in the map data. When acquiring the two-dimensional map, the vehicle also acquires the three-dimensional feature values. If the three-dimensional map 711 includes an SWLD, by adding information for identifying feature points in the SWLD that correspond to feature points in the two-dimensional map, the vehicle can determine the three-dimensional feature values ​​to be acquired together with the two-dimensional map based on the identification information. In this case, since it is sufficient to represent a two-dimensional position, the amount of data can be reduced compared to the case of representing a three-dimensional position.

[0543] Furthermore, when estimating the self-location using a two-dimensional map, the accuracy of the self-location estimation is lower than that of the three-dimensional map 711. Therefore, the vehicle may determine whether or not autonomous driving can be continued even if the estimation accuracy is lowered, and continue autonomous driving only when it is determined that autonomous driving can be continued.

[0544] Whether autonomous driving can continue is also affected by the driving environment, such as whether the road on which the vehicle is traveling is an urban area or a road with few other vehicles or pedestrians, such as an expressway, and the road width or road congestion (vehicle or pedestrian density). Furthermore, markers for recognition by sensors such as cameras can be placed on the grounds of business establishments, in towns, or inside buildings. In these specific areas, markers can be recognized with high accuracy by two-dimensional sensors, so that self-location estimation can be performed with high accuracy by, for example, including the position information of the markers in a two-dimensional map.

[0545] In addition, by including identification information in the map indicating whether each area is a specific area, the vehicle can determine whether the vehicle is in the specific area. If the vehicle is in the specific area, the vehicle determines to continue autonomous driving. In this way, the vehicle may determine whether to continue autonomous driving based on the accuracy of self-location estimation when using the two-dimensional map or the driving environment of the vehicle.

[0546] In this way, the three-dimensional information processing device 700 determines whether or not to perform automatic driving of the vehicle using the results of estimating the vehicle's self-position using the two-dimensional map and the vehicle-detected three-dimensional data 712, based on the vehicle's driving environment (the moving environment of the moving body).

[0547] Furthermore, the vehicle may switch the level (mode) of autonomous driving depending on the accuracy of self-location estimation or the driving environment of the vehicle, rather than on whether autonomous driving can be continued. Switching the level (mode) of autonomous driving here means, for example, limiting the speed, increasing the amount of driver operation (lowering the level of autonomous driving), switching to a mode in which driving information of a vehicle traveling ahead is obtained and used as a reference for driving, switching to a mode in which driving information of a vehicle that has the same destination set is obtained and used for autonomous driving, etc.

[0548] The map may also include information indicating a recommended level of autonomous driving when estimating a self-location using a two-dimensional map, which is associated with the location information. The recommended level may be metadata that changes dynamically depending on traffic volume, etc. This allows the vehicle to determine the level by simply acquiring information in the map, without having to determine the level successively depending on the surrounding environment, etc. Furthermore, by having multiple vehicles refer to the same map, the autonomous driving level of each vehicle can be kept constant. Note that the recommended level may not be a recommendation, but a level that must be observed.

[0549] The vehicle may also switch the level of autonomous driving depending on whether a driver is present (whether the vehicle is manned or unmanned). For example, the vehicle may lower the level of autonomous driving if a driver is present, and stop the vehicle if the driver is unmanned. The vehicle may determine a location where it can safely stop by recognizing nearby pedestrians, vehicles, and traffic signs. Alternatively, the map may include location information indicating a location where the vehicle can safely stop, and the vehicle may determine a location where it can safely stop by referring to the location information.

[0550] Next, a description will be given of an abnormality case 2, in which the three-dimensional map 711 does not exist or the three-dimensional map 711 has been acquired but is damaged.

[0551] The abnormal case determination unit 703 checks whether either (1) the three-dimensional map 711 for some or all sections on the route to the destination does not exist in the distribution server to be accessed and cannot be acquired, or (2) the acquired three-dimensional map 711 is partially or entirely corrupted, and if so, determines that the case is abnormal case 2. In other words, the abnormal case determination unit 703 determines whether the data of the three-dimensional map 711 is complete, and if the data of the three-dimensional map 711 is not complete, determines that the three-dimensional map 711 is abnormal.

[0552] If it is determined to be abnormal case 2, the following countermeasures are taken. First, (1) an example of the countermeasures taken when the three-dimensional map 711 cannot be acquired will be described.

[0553] For example, the vehicle sets a route that does not pass through any section where the three-dimensional map 711 does not exist.

[0554] Furthermore, if an alternative route cannot be set because there is no alternative route, or there is an alternative route but the distance is significantly increased, the vehicle sets a route including a section that does not have the three-dimensional map 711. Furthermore, in that section, the vehicle notifies the driver that the driving mode will be switched, and switches the driving mode to manual mode.

[0555] (2) If the acquired three-dimensional map 711 is partially or entirely corrupted, the following corrective action is taken.

[0556] The vehicle identifies the damaged portion in the three-dimensional map 711, requests data on the damaged portion through communication, acquires the data on the damaged portion, and uses the acquired data to update the three-dimensional map 711. At this time, the vehicle may specify the damaged portion by position information such as absolute coordinates or relative coordinates in the three-dimensional map 711, or may specify the damaged portion by an index number of a random access unit that constitutes the damaged portion. In this case, the vehicle replaces the random access unit that includes the damaged portion with the acquired random access unit.

[0557] Next, a description will be given of a countermeasure operation for abnormal case 3, which is a case where the vehicle-detected three-dimensional data 712 cannot be generated due to a malfunction of the vehicle's sensor or bad weather.

[0558] The abnormal case determination unit 703 checks whether the generation error of the own vehicle detected three-dimensional data 712 is within an allowable range, and if it is not within the allowable range, determines that it is an abnormal case 3. In other words, the abnormal case determination unit 703 determines whether the generation accuracy of the own vehicle detected three-dimensional data 712 is equal to or higher than a reference value, and if the generation accuracy of the own vehicle detected three-dimensional data 712 is not equal to or higher than the reference value, determines that the own vehicle detected three-dimensional data 712 is abnormal.

[0559] As a method for checking whether the generation error of the vehicle-detected three-dimensional data 712 is within an allowable range, the following method can be used.

[0560] The spatial resolution of the vehicle-detected three-dimensional data 712 during normal operation is determined in advance based on the resolution in the depth direction and the scanning direction of a three-dimensional sensor of the vehicle, such as a range finder or a stereo camera, or the density of a point cloud that can be generated. In addition, the vehicle acquires the spatial resolution of the three-dimensional map 711 from meta information included in the three-dimensional map 711, etc.

[0561] The vehicle estimates a reference value of the matching error when matching the vehicle-detected three-dimensional data 712 and the three-dimensional map 711 based on three-dimensional feature amounts, etc., using the spatial resolution of both. As the matching error, a statistical quantity such as the error of the three-dimensional feature amount for each feature point, the average value of the errors of the three-dimensional feature amounts between a plurality of feature points, or the error of the spatial distance between a plurality of feature points, etc., can be used. The allowable range of deviation from the reference value is set in advance.

[0562] If the matching error between the vehicle-detected three-dimensional data 712 generated before or during driving and the three-dimensional map 711 is not within the allowable range, the vehicle determines that it is an abnormal case 3.

[0563] Alternatively, the vehicle may use a test pattern having a known three-dimensional shape for accuracy checking, obtain vehicle-detected three-dimensional data 712 for the test pattern before starting to drive, and determine whether it is abnormal case 3 based on whether the shape error is within the acceptable range.

[0564] For example, the vehicle performs the above determination every time before starting to travel. Alternatively, the vehicle obtains a time-series change in the matching error by performing the above determination at regular time intervals while traveling. When the matching error is on the rise, the vehicle may determine that the error is abnormal case 3 even if the error is within an acceptable range. Furthermore, when the vehicle can predict an abnormality based on the time-series change, the vehicle may notify the user that an abnormality is predicted, for example, by displaying a message encouraging inspection or repair. Furthermore, the vehicle may determine an abnormality based on a transient factor such as bad weather and an abnormality based on a sensor failure based on the time-series change, and notify the user of only the abnormality based on the sensor failure.

[0565] In addition, if the vehicle is determined to be in abnormality case 3, it will selectively take one of three types of response actions: (1) activating an emergency alternative sensor (rescue mode), (2) switching the driving mode, or (3) correcting the operation of the three-dimensional sensor.

[0566] First, (1) the case where an alternative sensor for emergency use is activated will be described. The vehicle activates an alternative sensor for emergency use that is different from the three-dimensional sensor used during normal driving. In other words, when the generation accuracy of the own-vehicle-detected three-dimensional data 712 is not equal to or higher than a reference value, the three-dimensional information processing device 700 generates the own-vehicle-detected three-dimensional data 712 (fourth three-dimensional position information) from information detected by the alternative sensor that is different from the normal sensor.

[0567] Specifically, when the vehicle acquires the vehicle-detected three-dimensional data 712 by using multiple cameras or LiDAR in combination, the vehicle identifies the malfunctioning sensor based on the direction in which the matching error of the vehicle-detected three-dimensional data 712 exceeds the allowable range, and then the vehicle activates an alternative sensor corresponding to the malfunctioning sensor.

[0568] The alternative sensor may be a three-dimensional sensor, a camera capable of acquiring two-dimensional images, a one-dimensional sensor such as ultrasonic waves, etc. If the alternative sensor is a sensor other than a three-dimensional sensor, the accuracy of self-location estimation may decrease or self-location estimation may not be possible, so the vehicle may switch the autonomous driving mode depending on the type of the alternative sensor.

[0569] For example, the vehicle continues the autonomous driving mode when the alternative sensor is a three-dimensional sensor, changes the driving mode from fully autonomous to a semi-autonomous driving mode that assumes human driving operation when the alternative sensor is a two-dimensional sensor, and switches the driving mode to a manual mode that does not perform automatic braking control when the alternative sensor is a one-dimensional sensor.

[0570] The vehicle may also switch the autonomous driving mode based on the driving environment. For example, if the alternative sensor is a two-dimensional sensor, the vehicle may continue in the fully autonomous driving mode when driving on a highway, and switch the driving mode to the semi-autonomous driving mode when driving in an urban area.

[0571] Even if there is no alternative sensor, the vehicle may continue estimating its own position if a sufficient number of feature points can be acquired using only the normally operating sensors. However, since detection in a specific direction becomes impossible, the vehicle switches the driving mode to semi-automated driving or manual mode.

[0572] Next, (2) a countermeasure operation for switching the driving mode will be described. The vehicle switches the driving mode from the autonomous driving mode to the manual mode. Alternatively, the vehicle may continue the autonomous driving until it reaches a place where it can be stopped safely, such as a roadside, and then stop. The vehicle may also switch the driving mode to the manual mode after stopping. In this way, the three-dimensional information processing device 700 switches the autonomous driving mode when the generation accuracy of the vehicle-detected three-dimensional data 712 is not equal to or greater than the reference value.

[0573] Next, (3) a countermeasure operation for correcting the operation of the three-dimensional sensor will be described. The vehicle identifies the malfunctioning three-dimensional sensor from the direction in which the matching error occurs, and performs calibration of the identified sensor. Specifically, when multiple LiDARs or cameras are used as sensors, a part of the three-dimensional space reconstructed by each sensor overlaps. That is, data of the overlapping part is acquired by the multiple sensors. The three-dimensional point cloud data acquired for the overlapping part differs between a normal sensor and a malfunctioning sensor. Therefore, the vehicle performs origin correction of the LiDAR, or adjusts the operation of a predetermined part, such as the exposure or focus of the camera, so that the malfunctioning sensor can acquire three-dimensional point cloud data equivalent to that of the normal sensor.

[0574] If the matching error falls within the allowable range after the adjustment, the vehicle continues the previous driving mode. On the other hand, if the matching accuracy does not fall within the allowable range after the adjustment, the vehicle takes the above-mentioned (1) countermeasure action of activating an emergency alternative sensor, or (2) countermeasure action of switching the driving mode.

[0575] In this manner, the three-dimensional information processing device 700 corrects the operation of the sensor when the generation accuracy of the host vehicle detected three-dimensional data 712 is not equal to or greater than the reference value.

[0576] A method for selecting a countermeasure action will be described below. The countermeasure action may be selected by a user such as a driver, or may be automatically selected by the vehicle without the intervention of the user.

[0577] The vehicle may also switch control depending on whether or not a driver is on board. For example, if a driver is on board, the vehicle may prioritize switching to manual mode. On the other hand, if no driver is on board, the vehicle may prioritize a mode in which the vehicle moves to a safe location and stops.

[0578] The information indicating the stop location may be included as meta information in the three-dimensional map 711. Alternatively, the vehicle may issue a request for a response regarding the stop location to a service that manages operation information of the autonomous driver, and obtain the information indicating the stop location.

[0579] In addition, when the vehicle is traveling on a predetermined route, the driving mode of the vehicle may be shifted to a mode in which the operator manages the operation of the vehicle via a communication channel. In particular, an abnormality in the self-location estimation function of a vehicle traveling in a fully automated driving mode is highly dangerous. Therefore, when the vehicle detects an abnormality case or cannot correct the detected abnormality, the vehicle notifies the service that manages the operation information via the communication channel of the occurrence of the abnormality. The service may notify vehicles traveling around the vehicle of the presence of the abnormal vehicle, or instruct them to clear a nearby stopping place.

[0580] Furthermore, the vehicle may travel at a slower speed than normal when an abnormality is detected.

[0581] If the vehicle is an autonomous vehicle that provides a dispatch service such as a taxi, and an abnormality occurs in the vehicle, the vehicle will contact an operation control center and stop in a safe place. The dispatch service will dispatch a replacement vehicle. Alternatively, the user of the dispatch service may drive the vehicle. In these cases, a discount on the fare or the provision of bonus points may be provided in combination.

[0582] In addition, in the method for dealing with the abnormal case 1, the method of performing self-location estimation based on a two-dimensional map has been described, but the self-location estimation may also be performed using a two-dimensional map in normal times. Fig. 36 is a flowchart of the self-location estimation process in this case.

[0583] First, the vehicle acquires a three-dimensional map 711 of the vicinity of the travel route (S711), and then acquires three-dimensional data 712 detected by the vehicle itself based on sensor information (S712).

[0584] Next, the vehicle determines whether the three-dimensional map 711 is necessary for self-location estimation (S713). Specifically, the vehicle determines whether the three-dimensional map 711 is necessary based on the accuracy of self-location estimation when the two-dimensional map is used and the driving environment. For example, a method similar to the method for dealing with the abnormality case 1 described above is used.

[0585] If it is determined that the three-dimensional map 711 is not necessary (No in S714), the vehicle acquires a two-dimensional map (S715). At this time, the vehicle may also acquire additional information as described in the method for dealing with abnormality case 1. The vehicle may also generate a two-dimensional map from the three-dimensional map 711. For example, the vehicle may generate a two-dimensional map by cutting out an arbitrary plane from the three-dimensional map 711.

[0586] Next, the vehicle estimates its own position using the vehicle-detected three-dimensional data 712 and the two-dimensional map (S716). Note that the method of estimating the own position using the two-dimensional map is, for example, the same as the method described in the method for dealing with the abnormality case 1 described above.

[0587] On the other hand, if it is determined that the three-dimensional map 711 is necessary (Yes in S714), the vehicle acquires the three-dimensional map 711 (S717). Next, the vehicle performs self-location estimation using the vehicle-detected three-dimensional data 712 and the three-dimensional map 711 (S718).

[0588] The vehicle may switch between using the two-dimensional map as a base and using the three-dimensional map 711 as a base, depending on the speed supported by the communication device of the vehicle or the state of the communication path. For example, a communication speed required when traveling while receiving the three-dimensional map 711 may be set in advance, and the vehicle may use the two-dimensional map as a base when the communication speed during traveling is equal to or lower than the set value, and may use the three-dimensional map 711 as a base when the communication speed during traveling is higher than the set value. The vehicle may use the two-dimensional map as a base without determining whether to use the two-dimensional map or the three-dimensional map.

[0589] (Embodiment 5) In this embodiment, a method of transmitting three-dimensional data to a following vehicle etc. will be described. Fig. 37 is a diagram showing an example of a target space of three-dimensional data to be transmitted to a following vehicle etc.

[0590] Vehicle 801 transmits three-dimensional data such as a point cloud (group of points) contained in a rectangular space 802 of width W, height H, and depth D at a distance L from the vehicle 801 in front of the vehicle 801 to a traffic monitoring cloud that monitors road conditions or a following vehicle at time intervals of Δt.

[0591] If a change occurs in the three-dimensional data contained in the space 802 that has been previously transmitted, such as when a vehicle or person enters the space 802 from the outside, the vehicle 801 also transmits the three-dimensional data of the space where the change has occurred.

[0592] Note that, although FIG. 37 shows an example in which the shape of the space 802 is a rectangular parallelepiped, the space 802 does not necessarily have to be a rectangular parallelepiped as long as it includes the space on the road ahead that is in a blind spot for following vehicles.

[0593] It is desirable to set the distance L to a distance at which the following vehicle that has received the three-dimensional data can safely stop. For example, the distance L is set to the sum of the distance the following vehicle travels while it takes to receive the three-dimensional data, the distance the following vehicle travels before it starts to decelerate in response to the received data, and the distance the following vehicle requires to safely stop after starting to decelerate. Since these distances change depending on the speed, the distance L may change depending on the speed V of the vehicle, such as L = a x V + b (a and b are constants).

[0594] The width W is set to a value at least larger than the width of the lane in which the vehicle 801 is traveling. More desirably, the width W is set to a size that includes adjacent spaces such as left and right lanes or side strips.

[0595] The depth D may be a fixed value, or may vary according to the vehicle speed V, such as D=c×V+d (c and d are constants). By setting D so that D>V×Δt, the space to be transmitted can overlap with the space that has already been transmitted in the past. This allows the vehicle 801 to more reliably transmit the space on the road to the following vehicles, etc. without omissions.

[0596] In this way, by limiting the three-dimensional data transmitted by vehicle 801 to a space that is useful for following vehicles, the volume of three-dimensional data to be transmitted can be effectively reduced, thereby achieving low communication latency and low cost.

[0597] Next, a configuration of a three-dimensional data creation device 810 according to this embodiment will be described. Fig. 38 is a block diagram showing an example of the configuration of a three-dimensional data creation device 810 according to this embodiment. This three-dimensional data creation device 810 is mounted on a vehicle 801, for example. The three-dimensional data creation device 810 transmits and receives three-dimensional data to and from an external traffic monitoring cloud, a leading vehicle, or a following vehicle, and creates and stores three-dimensional data.

[0598] The three-dimensional data creation device 810 includes a data receiving unit 811, a communication unit 812, a receiving control unit 813, a format conversion unit 814, multiple sensors 815, a three-dimensional data creation unit 816, a three-dimensional data synthesis unit 817, a three-dimensional data storage unit 818, a communication unit 819, a transmission control unit 820, a format conversion unit 821, and a data transmission unit 822.

[0599] The data receiving unit 811 receives three-dimensional data 831 from a traffic monitoring cloud or a preceding vehicle. The three-dimensional data 831 includes information such as a point cloud, a visible light image, depth information, sensor position information, or speed information, including an area that cannot be detected by the sensor 815 of the vehicle itself.

[0600] The communication unit 812 communicates with the traffic monitoring cloud or the vehicle ahead, and transmits data transmission requests, etc. to the traffic monitoring cloud or the vehicle ahead.

[0601] The reception control unit 813 exchanges information such as compatible formats with the communication destination via the communication unit 812, and establishes communication with the communication destination.

[0602] The format conversion unit 814 generates three-dimensional data 832 by performing format conversion or the like on the three-dimensional data 831 received by the data receiving unit 811. Furthermore, when the three-dimensional data 831 is compressed or encoded, the format conversion unit 814 performs decompression or decoding processing.

[0603] The multiple sensors 815 are a group of sensors such as LIDAR, a visible light camera, or an infrared camera that acquires information about the outside of the vehicle 801, and generate sensor information 833. For example, when the sensor 815 is a laser sensor such as LIDAR, the sensor information 833 is three-dimensional data such as a point cloud (point cloud data). Note that the number of sensors 815 does not need to be multiple.

[0604] The three-dimensional data creation unit 816 generates three-dimensional data 834 from the sensor information 833. The three-dimensional data 834 includes information such as a point cloud, a visible light image, depth information, sensor position information, or velocity information.

[0605] The three-dimensional data synthesis unit 817 synthesizes three-dimensional data 834 created based on the host vehicle's sensor information 833 with three-dimensional data 832 created by a traffic monitoring cloud or a preceding vehicle, etc., to construct three-dimensional data 835 that includes the space in front of the preceding vehicle that cannot be detected by the host vehicle's sensor 815.

[0606] The three-dimensional data storage unit 818 stores the generated three-dimensional data 835 and the like.

[0607] The communication unit 819 communicates with the traffic monitoring cloud or the following vehicle, and transmits data transmission requests, etc. to the traffic monitoring cloud or the following vehicle.

[0608] The transmission control unit 820 exchanges information such as compatible formats with the communication destination and establishes communication with the communication destination via the communication unit 819. In addition, the transmission control unit 820 determines a transmission region, which is the space of the three-dimensional data to be transmitted, based on three-dimensional data construction information of the three-dimensional data 832 generated by the three-dimensional data synthesis unit 817 and a data transmission request from the communication destination.

[0609] Specifically, the transmission control unit 820 determines a transmission region including a space in front of the vehicle that cannot be detected by the sensor of the following vehicle in response to a data transmission request from the traffic monitoring cloud or the following vehicle. The transmission control unit 820 also determines the transmission region by judging whether or not a transmittable space or a transmitted space has been updated based on the three-dimensional data construction information. For example, the transmission control unit 820 determines the region specified in the data transmission request and in which the corresponding three-dimensional data 835 exists as the transmission region. Then, the transmission control unit 820 notifies the format conversion unit 821 of the format supported by the communication destination and the transmission region.

[0610] The format conversion unit 821 converts three-dimensional data 836 of the transmission region, among the three-dimensional data 835 stored in the three-dimensional data storage unit 818, into a format supported by the receiving side, thereby generating three-dimensional data 837. Note that the format conversion unit 821 may reduce the amount of data by compressing or encoding the three-dimensional data 837.

[0611] The data transmission unit 822 transmits the three-dimensional data 837 to the traffic monitoring cloud or the following vehicle. The three-dimensional data 837 includes information such as a point cloud, visible light image, depth information, or sensor position information in front of the vehicle, including blind spots of the following vehicle.

[0612] In the above description, the format conversion units 814 and 821 perform format conversion, but the format conversion does not necessarily have to be performed.

[0613] With this configuration, the three-dimensional data creation device 810 externally acquires three-dimensional data 831 of an area that cannot be detected by the sensor 815 of the host vehicle, and generates three-dimensional data 835 by synthesizing the three-dimensional data 831 with three-dimensional data 834 based on sensor information 833 detected by the sensor 815 of the host vehicle. In this way, the three-dimensional data creation device 810 can generate three-dimensional data of an area that cannot be detected by the sensor 815 of the host vehicle.

[0614] In addition, in response to a data transmission request from a traffic monitoring cloud or a following vehicle, the three-dimensional data creation device 810 can transmit three-dimensional data including the space in front of the vehicle that cannot be detected by the sensors of the following vehicle to the traffic monitoring cloud or the following vehicle, etc.

[0615] Next, there will be described a procedure for transmitting three-dimensional data to a following vehicle in the three-dimensional data creation device 810. Fig. 39 is a flowchart showing an example of a procedure for transmitting three-dimensional data to a traffic monitoring cloud or a following vehicle by the three-dimensional data creation device 810.

[0616] First, the three-dimensional data creation device 810 generates and updates three-dimensional data 835 of a space including a space 802 on the road ahead of the vehicle 801 (S801). Specifically, the three-dimensional data creation device 810 constructs three-dimensional data 835 including the space ahead of the vehicle ahead that cannot be detected by the sensor 815 of the vehicle ahead, for example, by synthesizing three-dimensional data 834 created based on sensor information 833 of the vehicle ahead 801 with three-dimensional data 831 created by a traffic monitoring cloud or a vehicle ahead.

[0617] Next, the three-dimensional data creation device 810 determines whether the three-dimensional data 835 included in the transmitted space has changed (S802).

[0618] If a change occurs in the three-dimensional data 835 contained in the space that has already been transmitted, such as when a vehicle or person enters the space from outside (Yes in S802), the three-dimensional data creation device 810 transmits three-dimensional data including the three-dimensional data 835 of the space where the change has occurred to the traffic monitoring cloud or a following vehicle (S803).

[0619] The three-dimensional data creation device 810 may transmit the three-dimensional data of the space where a change has occurred in accordance with the transmission timing of the three-dimensional data transmitted at a predetermined interval, or may transmit the three-dimensional data immediately after detecting the change. In other words, the three-dimensional data creation device 810 may transmit the three-dimensional data of the space where a change has occurred in priority over the three-dimensional data transmitted at a predetermined interval.

[0620] In addition, the three-dimensional data creation device 810 may transmit all of the three-dimensional data of the space in which a change has occurred as the three-dimensional data of the space in which a change has occurred, or may transmit only the differences in the three-dimensional data (for example, information on three-dimensional points that have appeared or disappeared, or displacement information of three-dimensional points, etc.).

[0621] Furthermore, the three-dimensional data creation device 810 may transmit metadata regarding the danger avoidance operation of the vehicle, such as a sudden braking warning, to the following vehicle prior to the three-dimensional data of the space where a change has occurred. This allows the following vehicle to quickly recognize the sudden braking of the vehicle ahead, and to start danger avoidance operations, such as deceleration, earlier.

[0622] If there is no change in the three-dimensional data 835 contained in the transmitted space (No in S802), or after step S803, the three-dimensional data creation device 810 transmits the three-dimensional data contained in a space of a specified shape at a distance L ahead of the vehicle 801 to the traffic monitoring cloud or a following vehicle (S804).

[0623] Furthermore, for example, the processes in steps S801 to S804 are repeatedly performed at predetermined time intervals.

[0624] Furthermore, when there is no difference between the three-dimensional data 835 of the space 802 currently being transmitted and the three-dimensional map, the three-dimensional data creation device 810 does not need to transmit the three-dimensional data 837 of the space 802 .

[0625] FIG. 40 is a flow chart showing the operation of the three-dimensional data creation device 810 in this case.

[0626] First, the three-dimensional data creation device 810 generates and updates three-dimensional data 835 of a space including a space 802 on a road ahead of the vehicle 801 (S811).

[0627] Next, the three-dimensional data creation device 810 determines whether the three-dimensional data 835 of the generated space 802 has been updated from the three-dimensional map (S812). That is, the three-dimensional data creation device 810 determines whether there is a difference between the three-dimensional data 835 of the generated space 802 and the three-dimensional map. Here, the three-dimensional map is three-dimensional map information managed by an infrastructure device such as a traffic monitoring cloud. For example, this three-dimensional map is acquired as three-dimensional data 831.

[0628] If there is an update (Yes in S812), the three-dimensional data creation device 810 transmits the three-dimensional data contained in the space 802 to the traffic monitoring cloud or the following vehicle in the same manner as described above (S813).

[0629] On the other hand, if there is no update (No in S812), the three-dimensional data creation device 810 does not transmit the three-dimensional data included in the space 802 to the traffic monitoring cloud and the following vehicle (S814). The three-dimensional data creation device 810 may set the volume of the space 802 to zero, thereby controlling so that the three-dimensional data of the space 802 is not transmitted. The three-dimensional data creation device 810 may also transmit information indicating that there is no update to the space 802 to the traffic monitoring cloud or the following vehicle.

[0630] As a result, for example, if there are no obstacles on the road, there is no difference between the generated 3D data 835 and the 3D map on the infrastructure side, and no data is transmitted. In this way, the transmission of unnecessary data can be suppressed.

[0631] In the above description, an example has been given in which the three-dimensional data creation device 810 is mounted on a vehicle, but the three-dimensional data creation device 810 is not limited to being mounted on a vehicle, and may be mounted on any moving object.

[0632] As described above, three-dimensional data creation device 810 according to this embodiment is mounted on a mobile body including sensor 815 and a communication unit (data receiving unit 811 or data transmitting unit 822, etc.) that transmits and receives three-dimensional data to and from the outside. Three-dimensional data creation device 810 creates three-dimensional data 835 (second three-dimensional data) based on sensor information 833 detected by sensor 815 and three-dimensional data 831 (first three-dimensional data) received by data receiving unit 811. Three-dimensional data creation device 810 transmits three-dimensional data 837, which is a part of three-dimensional data 835, to the outside.

[0633] This allows the three-dimensional data creation device 810 to generate three-dimensional data of a range that cannot be detected by the vehicle itself. Also, the three-dimensional data creation device 810 can transmit three-dimensional data of a range that cannot be detected by other vehicles to the other vehicles.

[0634] Furthermore, the three-dimensional data creation device 810 repeatedly creates three-dimensional data 835 and transmits three-dimensional data 837 at predetermined intervals. The three-dimensional data 837 is three-dimensional data of a small space 802 of a predetermined size located a predetermined distance L forward in the moving direction of the vehicle 801 from the current position of the vehicle 801.

[0635] This limits the range of the three-dimensional data 837 to be transmitted, thereby reducing the amount of the three-dimensional data 837 to be transmitted.

[0636] Furthermore, the predetermined distance L changes according to the moving speed V of the vehicle 801. For example, the higher the moving speed V, the longer the predetermined distance L. This allows the vehicle 801 to set an appropriate small space 802 according to the moving speed V of the vehicle 801, and transmit three-dimensional data 837 of the small space 802 to a following vehicle, etc.

[0637] The predetermined size also changes according to the moving speed V of the vehicle 801. For example, the higher the moving speed V, the larger the predetermined size. For example, the higher the moving speed V, the larger the depth D, which is the length of the small space 802 in the moving direction of the vehicle. This allows the vehicle 801 to set an appropriate small space 802 according to the moving speed V of the vehicle 801, and transmit three-dimensional data 837 of the small space 802 to a following vehicle, etc.

[0638] Furthermore, the three-dimensional data creation device 810 determines whether there is a change in the three-dimensional data 835 of the small space 802 corresponding to the transmitted three-dimensional data 837. When the three-dimensional data creation device 810 determines that there is a change, it transmits three-dimensional data 837 (fourth three-dimensional data) that is at least a part of the three-dimensional data 835 that has the change to an external following vehicle or the like.

[0639] This allows the vehicle 801 to transmit three-dimensional data 837 of the changed space to following vehicles, etc.

[0640] Furthermore, the three-dimensional data creation device 810 transmits the three-dimensional data 837 (fourth three-dimensional data) that has changed in priority over the normal three-dimensional data 837 (third three-dimensional data) that is periodically transmitted. Specifically, the three-dimensional data creation device 810 transmits the three-dimensional data 837 (fourth three-dimensional data) that has changed before transmitting the normal three-dimensional data 837 (third three-dimensional data) that is periodically transmitted. In other words, the three-dimensional data creation device 810 transmits the three-dimensional data 837 (fourth three-dimensional data) that has changed non-periodically, without waiting for the transmission of the normal three-dimensional data 837 that is periodically transmitted.

[0641] This allows the vehicle 801 to preferentially transmit the three-dimensional data 837 of the space where a change has occurred to the following vehicles, etc., so that the following vehicles, etc. can quickly make decisions based on the three-dimensional data.

[0642] Moreover, the changed three-dimensional data 837 (fourth three-dimensional data) indicates the difference between the three-dimensional data 835 of the small space 802 corresponding to the transmitted three-dimensional data 837 and the changed three-dimensional data 835. This makes it possible to reduce the amount of the three-dimensional data 837 to be transmitted.

[0643] Furthermore, when there is no difference between the three-dimensional data 837 of the small space 802 and the three-dimensional data 831 of the small space 802, the three-dimensional data creation device 810 does not transmit the three-dimensional data 837 of the small space 802. Furthermore, the three-dimensional data creation device 810 may transmit information indicating that there is no difference between the three-dimensional data 837 of the small space 802 and the three-dimensional data 831 of the small space 802 to the outside.

[0644] This makes it possible to prevent unnecessary three-dimensional data 837 from being transmitted, thereby reducing the amount of three-dimensional data 837 to be transmitted.

[0645] (Embodiment 6) In this embodiment, a display device and a display method for displaying information obtained from a three-dimensional map or the like, and a storage device and a storage method for a three-dimensional map or the like will be described.

[0646] For automatic driving of a car or autonomous movement of a robot, a moving body such as a car or a robot utilizes a 3D map obtained by communication with a server or other cars, and a 2D image or a 3D data detected by the vehicle obtained from a sensor mounted on the vehicle. Of these data, the data that a user wants to view or save may differ depending on the situation. Below, a display device that switches the display depending on the situation will be described.

[0647] 41 is a flowchart showing an outline of a display method using a display device. The display device is mounted on a moving body such as a car or a robot. In the following, an example in which the moving body is a vehicle (automobile) will be described.

[0648] First, the display device determines whether to display two-dimensional surrounding information or three-dimensional surrounding information according to the driving situation of the vehicle (S901). The two-dimensional surrounding information corresponds to the first surrounding information in the claims, and the three-dimensional surrounding information corresponds to the second surrounding information in the claims. Here, the surrounding information is information showing the surroundings of the moving object, such as an image seen in a specified direction from the vehicle, or a map of the surroundings of the vehicle.

[0649] The two-dimensional surrounding information is information generated using two-dimensional data. Here, the two-dimensional data is two-dimensional map information or image. For example, the two-dimensional surrounding information is a map of the surroundings of the vehicle obtained from a two-dimensional map, or an image obtained by a camera mounted on the vehicle. In addition, the two-dimensional surrounding information does not include, for example, three-dimensional information. In other words, if the two-dimensional surrounding information is a map of the surroundings of the vehicle, the map does not include information in the height direction. In addition, if the two-dimensional surrounding information is an image obtained by a camera, the image does not include information in the depth direction.

[0650] The three-dimensional surrounding information is information generated using three-dimensional data. Here, the three-dimensional data is, for example, a three-dimensional map. The three-dimensional data may be information indicating the three-dimensional position or three-dimensional shape of an object around the vehicle acquired from another vehicle or a server, or detected by the vehicle itself. For example, the three-dimensional surrounding information is a two-dimensional or three-dimensional image or map of the vehicle's surroundings generated using a three-dimensional map. The three-dimensional surrounding information includes, for example, three-dimensional information. For example, when the three-dimensional surrounding information is an image in front of the vehicle, the image includes information indicating the distance to the object in the image. Or, for example, a pedestrian or the like present at the back of the vehicle in front is displayed in the image. The three-dimensional surrounding information may be information indicating the distance or the pedestrian or the like superimposed on an image obtained from a sensor mounted on the vehicle. The three-dimensional surrounding information may be information indicating the height direction superimposed on a two-dimensional map.

[0651] Furthermore, the three-dimensional data may be displayed three-dimensionally, and a two-dimensional image or a two-dimensional map obtained from the three-dimensional data may be displayed on a two-dimensional display or the like.

[0652] If it is determined in step S901 that three-dimensional peripheral information is to be displayed (Yes in S902), the display device displays the three-dimensional peripheral information (S903). On the other hand, if it is determined in step S901 that two-dimensional peripheral information is to be displayed (No in S902), the display device displays the two-dimensional peripheral information (S904). In this manner, the display device displays the three-dimensional peripheral information or the two-dimensional peripheral information determined to be displayed in step S901.

[0653] Specific examples will be described below. In a first example, the display device switches the surrounding information to be displayed depending on whether the vehicle is being driven automatically or manually. Specifically, during automatic driving, the driver does not need to know detailed surrounding road information, so the display device displays two-dimensional surrounding information (e.g., a two-dimensional map). On the other hand, during manual driving, three-dimensional surrounding information (e.g., a three-dimensional map) is displayed so that the driver can know detailed surrounding road information for safe driving.

[0654] During autonomous driving, the display device may display information that has influenced the driving operation (e.g., SWLD used for self-location estimation, lanes, road signs, surrounding situation detection results, etc.) in order to show the user what information the vehicle is based on for driving. For example, the display device may display this information in addition to a two-dimensional map.

[0655] The peripheral information displayed during the above-mentioned automatic driving and manual driving is merely an example, and the display device may display three-dimensional peripheral information during automatic driving and two-dimensional peripheral information during manual driving. The display device may display metadata or peripheral situation detection results in addition to a two-dimensional or three-dimensional map or image during at least one of automatic driving and manual driving, or may display metadata or peripheral situation detection results instead of a two-dimensional or three-dimensional map or image. Here, metadata is information indicating a three-dimensional position or three-dimensional shape of an object acquired from a server or another vehicle. The peripheral situation detection result is information indicating a three-dimensional position or three-dimensional shape of an object detected by the vehicle itself.

[0656] In a second example, the display device switches the peripheral information to be displayed depending on the driving environment. For example, the display device switches the peripheral information to be displayed depending on the brightness of the outside world. Specifically, when the surroundings of the vehicle are bright, the display device displays a two-dimensional image obtained by a camera mounted on the vehicle, or three-dimensional peripheral information created using the two-dimensional image. On the other hand, when the surroundings of the vehicle are dark, the display device displays three-dimensional peripheral information created using a lidar or millimeter-wave radar, since the two-dimensional image obtained by the camera mounted on the vehicle is dark and difficult to view.

[0657] The display device may also switch the displayed surrounding information depending on the driving area, which is the area the vehicle is currently in. For example, the display device displays three-dimensional surrounding information in tourist spots, urban areas, or near the destination, so as to provide the user with information on surrounding buildings, etc. On the other hand, the display device displays two-dimensional surrounding information in mountainous areas or suburban areas, etc., since it is considered that detailed surrounding information is often not required.

[0658] The display device may also switch the displayed surrounding information based on weather conditions. For example, the display device displays three-dimensional surrounding information created using a camera or LIDAR when the weather is fine. On the other hand, when it is raining or foggy, the display device displays three-dimensional surrounding information created using a millimeter wave radar because the three-dimensional surrounding information created using a camera or LIDAR is more likely to contain noise.

[0659] Furthermore, the display switching may be performed automatically by the system or manually by the user.

[0660] In addition, the three-dimensional surrounding information is generated from one or more of the following data: dense point cloud data generated based on WLD, mesh data generated based on MWLD, sparse data generated based on SWLD, lane data generated based on lane world, two-dimensional map data including three-dimensional shape information of roads and intersections, and metadata including three-dimensional position or three-dimensional shape information that changes in real time or vehicle detection results.

[0661] As described above, the WLD is three-dimensional point cloud data, and the SWLD is data obtained by extracting a point cloud whose feature amount is equal to or greater than a threshold value from the WLD. The MWLD is data having a mesh structure generated from the WLD. The lane world is data obtained by extracting a point cloud whose feature amount is equal to or greater than a threshold value and is necessary for self-location estimation, driving assistance, or autonomous driving from the WLD.

[0662] Here, MWLD and SWLD have smaller data volumes than WLD. Therefore, when more detailed data is required, WLD is used, and when not, MWLD or SWLD is used, thereby appropriately reducing the amount of communication data and the amount of processing. Also, Lane World has smaller data volumes than SWLD. Therefore, by using Lane World, the amount of communication data and the amount of processing can be further reduced.

[0663] In addition, although an example of switching between two-dimensional peripheral information and three-dimensional peripheral information has been described above, the display device may switch the type of data (WLD, SWLD, etc.) used to generate the three-dimensional peripheral information based on the above conditions. That is, in the above description, the display device may display three-dimensional peripheral information generated from first data (e.g., WLD or SWLD) having a larger amount of data when displaying three-dimensional peripheral information, and may display three-dimensional peripheral information generated from second data (e.g., SWLD or lane world) having a smaller amount of data than the first data instead of the two-dimensional peripheral information when displaying two-dimensional peripheral information.

[0664] The display device displays the two-dimensional or three-dimensional peripheral information on, for example, a two-dimensional display, a head-up display, or a head-mounted display mounted on the vehicle. Alternatively, the display device may transmit the two-dimensional or three-dimensional peripheral information to a mobile terminal such as a smartphone by wireless communication and display the information. In other words, the display device is not limited to a display device mounted on a moving body, but may be a display device that operates in cooperation with the moving body. For example, when a user carrying a display device such as a smartphone boards a moving body or drives a moving body, information on the moving body such as the position of the moving body based on the self-location estimation of the moving body is displayed on the display device, or this information is displayed on the display device together with the peripheral information.

[0665] Furthermore, when displaying a three-dimensional map, the display device may render the three-dimensional map and display it as two-dimensional data, or may display it as three-dimensional data using a three-dimensional display or a three-dimensional hologram.

[0666] Next, a method for saving a three-dimensional map will be described. For automatic driving of a car or autonomous movement of a robot, a moving body such as a car or a robot utilizes a three-dimensional map obtained by communication with a server or other cars, and two-dimensional images obtained from a sensor mounted on the vehicle, or three-dimensional data detected by the vehicle. Of these data, the data that a user wants to view or save is considered to differ depending on the situation. Below, a method for saving data according to the situation will be described.

[0667] The storage device is mounted on a moving body such as a car or a robot. In the following, an example in which the moving body is a vehicle (automobile) will be described. The storage device may be included in the display device described above.

[0668] In the first example, the storage device determines whether to store the 3D map based on the region. Here, by storing the 3D map in the storage medium of the vehicle, autonomous driving becomes possible within the stored space without communication with the server. However, since the storage capacity is limited, only limited data can be stored. Therefore, the storage device limits the region to be stored as shown below.

[0669] For example, the storage device preferentially stores three-dimensional maps of areas that are frequently passed through, such as a commute route or around one's home. This eliminates the need to obtain data for frequently used areas each time, and effectively reduces the amount of communication data. Note that preferential storage means storing data with a higher priority within a predetermined storage capacity. For example, if new data cannot be stored within the storage capacity, data with a lower priority than the new data is deleted.

[0670] Alternatively, the storage device may preferentially store 3D maps of areas with poor communication environments, which eliminates the need to acquire data through communication in areas with poor communication environments, thereby reducing the occurrence of cases where the 3D map cannot be acquired due to poor communication.

[0671] Alternatively, the storage device preferentially stores 3D maps of areas with heavy traffic. This allows the storage of 3D maps of areas with a high incidence of accidents to be preferentially stored. This makes it possible to prevent a decrease in the accuracy of automated driving or driving assistance in such areas due to poor communication, which makes it impossible to obtain 3D maps.

[0672] Alternatively, the storage device preferentially stores three-dimensional maps of areas with low traffic volume. Here, in areas with low traffic volume, there is a high possibility that the autonomous driving mode that automatically follows the vehicle ahead cannot be used. This may result in a need for more detailed surrounding information. Therefore, by preferentially storing three-dimensional maps of areas with low traffic volume, the accuracy of autonomous driving or driving assistance in such areas can be improved.

[0673] The above-mentioned storage methods may be combined. The area in which these three-dimensional maps are to be preferentially stored may be automatically determined by the system or may be designated by the user.

[0674] The storage device may delete a 3D map that has been stored for a predetermined period of time or may update it to the latest data, thereby preventing old map data from being used. When updating map data, the storage device may compare the old map with the new map to detect a difference area, which is a spatial area where there is a difference, and add data of the difference area of ​​the new map to the old map or remove data of the difference area from the old map to update only data of areas where there is a change.

[0675] In this example, the stored three-dimensional map is used for autonomous driving. Therefore, by using SWLD as this three-dimensional map, the amount of communication data can be reduced. Note that the three-dimensional map is not limited to SWLD, and may be other types of data such as WLD.

[0676] In a second example, a storage device stores a three-dimensional map based on an event.

[0677] For example, the storage device stores special events encountered during driving as a 3D map. This allows the user to later view details of the event. Examples of events stored as 3D maps are shown below. The storage device may also store 3D surrounding information generated from the 3D map.

[0678] For example, the storage device stores the 3D map before and after a collision accident, or when a danger is detected.

[0679] Or, the storage device may store three-dimensional maps of characteristic scenes, such as beautiful landscapes, crowded places, or tourist attractions.

[0680] The events to be stored may be automatically determined by the system or may be specified in advance by the user. For example, machine learning may be used as a method for determining the events to be stored.

[0681] In this example, the stored three-dimensional map is used for viewing. Therefore, by using the WLD as the three-dimensional map, high-quality images can be provided. Note that the three-dimensional map is not limited to the WLD, and may be other types of data such as SWLD.

[0682] Hereinafter, a method of controlling the display in response to a user will be described. When the display device superimposes and displays the surrounding situation detection result obtained by vehicle-to-vehicle communication on a map, the display device makes the detected object behind the surrounding vehicle visible by expressing the surrounding vehicle in a wire frame or by expressing the surrounding vehicle with transparency. Alternatively, the display device may display an image from an aerial viewpoint to provide an overhead view of the vehicle, the surrounding vehicles, and the surrounding situation detection result.

[0683] When using a head-up display to superimpose the surrounding situation detection results or point cloud data on the surrounding environment seen through the windshield as shown in Fig. 42, the position at which the information is superimposed may shift depending on the user's posture, body type, or eye position. Fig. 43 is a diagram showing an example of the head-up display when the position is shifted.

[0684] To correct such misalignment, the display device detects the user's posture, body type, or eye position using information from an in-car camera or a sensor mounted on the seat. The display device adjusts the position at which information is superimposed according to the detected posture, body type, or eye position of the user. Figure 44 is a diagram showing an example of the display of the head-up display after adjustment.

[0685] The user may manually adjust the superimposition position using a control device mounted on the vehicle.

[0686] The display device may display safe locations on a map in the event of a disaster and present the location to the user. Alternatively, the vehicle may inform the user of the details of the disaster and that the user is heading to a safe location, and automatically drive to the safe location.

[0687] For example, the vehicle may set its destination to an area with a high altitude above sea level so as not to be swept away by a tsunami when an earthquake occurs. At this time, the vehicle may acquire information on roads that have become impassable due to the earthquake by communicating with a server, and may perform processing according to the nature of the disaster, such as taking a route that avoids those roads.

[0688] In addition, the autonomous driving may include multiple modes, such as a travel mode and a drive mode.

[0689] In the travel mode, the vehicle determines a route to the destination, taking into consideration factors such as fast arrival time, low fare, short driving distance, and low energy consumption, and then drives automatically along the determined route.

[0690] In Drive mode, the vehicle automatically determines the route to arrive at the destination at the time specified by the user. For example, when the user sets the destination and arrival time, the vehicle determines a route to visit nearby tourist spots and arrive at the destination at the set time, and automatically drives according to the determined route.

[0691] (Embodiment 7) In the fifth embodiment, an example has been described in which a client device such as a vehicle transmits three-dimensional data to another vehicle or a server such as a traffic monitoring cloud. In the present embodiment, the client device transmits sensor information obtained by a sensor to the server or another client device.

[0692] First, the configuration of the system according to this embodiment will be described. Fig. 45 is a diagram showing the configuration of a transmission / reception system for a 3D map and sensor information according to this embodiment. This system includes a server 901 and client devices 902A and 902B. When there is no particular need to distinguish between the client devices 902A and 902B, they are also referred to as client devices 902.

[0693] The client device 902 is, for example, an in-vehicle device mounted on a moving object such as a vehicle. The server 901 is, for example, a traffic monitoring cloud or the like, and is capable of communicating with a plurality of client devices 902.

[0694] The server 901 transmits a three-dimensional map composed of a point cloud to the client device 902. Note that the composition of the three-dimensional map is not limited to a point cloud, and may represent other three-dimensional data such as a mesh structure.

[0695] The client device 902 transmits sensor information acquired by the client device 902 to the server 901. The sensor information includes, for example, at least one of LIDAR acquisition information, a visible light image, an infrared image, a depth image, sensor position information, and speed information.

[0696] Data transmitted between the server 901 and the client device 902 may be compressed to reduce data, or may be left uncompressed to maintain data accuracy. When compressing data, a three-dimensional compression method based on an octree structure, for example, can be used for the point cloud. Also, a two-dimensional image compression method can be used for the visible light image, the infrared image, and the depth image. The two-dimensional image compression method is, for example, MPEG-4 AVC or HEVC standardized by MPEG.

[0697] Furthermore, the server 901 transmits the three-dimensional map managed by the server 901 to the client device 902 in response to a transmission request for the three-dimensional map from the client device 902. Note that the server 901 may transmit the three-dimensional map without waiting for a transmission request for the three-dimensional map from the client device 902. For example, the server 901 may broadcast the three-dimensional map to one or more client devices 902 in a predetermined space. Furthermore, the server 901 may transmit a three-dimensional map suitable for the position of the client device 902 at regular intervals to the client device 902 that has received a transmission request once. Furthermore, the server 901 may transmit the three-dimensional map to the client device 902 every time the three-dimensional map managed by the server 901 is updated.

[0698] The client device 902 issues a request for transmitting a three-dimensional map to the server 901. For example, when the client device 902 wants to estimate its own position while driving, the client device 902 transmits a request for transmitting a three-dimensional map to the server 901.

[0699] In the following cases, the client device 902 may issue a transmission request for a three-dimensional map to the server 901. If the three-dimensional map held by the client device 902 is old, the client device 902 may issue a transmission request for a three-dimensional map to the server 901. For example, if a certain period of time has passed since the client device 902 acquired the three-dimensional map, the client device 902 may issue a transmission request for a three-dimensional map to the server 901.

[0700] The client device 902 may issue a request to send a three-dimensional map to the server 901 a certain time before the client device 902 leaves the space shown in the three-dimensional map held by the client device 902. For example, when the client device 902 is within a predetermined distance from the boundary of the space shown in the three-dimensional map held by the client device 902, the client device 902 may issue a request to send a three-dimensional map to the server 901. In addition, when the movement route and movement speed of the client device 902 are known, the time when the client device 902 will leave the space shown in the three-dimensional map held by the client device 902 may be predicted based on these.

[0701] If the error in aligning the three-dimensional data created by the client device 902 from sensor information with the three-dimensional map is equal to or greater than a certain level, the client device 902 may issue a request to the server 901 to transmit the three-dimensional map.

[0702] The client device 902 transmits the sensor information to the server 901 in response to a request to transmit the sensor information transmitted from the server 901. The client device 902 may transmit the sensor information to the server 901 without waiting for a request to transmit the sensor information from the server 901. For example, once the client device 902 receives a request to transmit the sensor information from the server 901, the client device 902 may transmit the sensor information to the server 901 periodically for a certain period of time. In addition, when an error occurs in aligning three-dimensional data created by the client device 902 based on the sensor information with the three-dimensional map obtained from the server 901, the client device 902 may determine that a change may have occurred in the three-dimensional map around the client device 902 and transmit a message to that effect along with the sensor information to the server 901.

[0703] The server 901 issues a transmission request for sensor information to the client device 902. For example, the server 901 receives location information of the client device 902, such as a GPS, from the client device 902. When the server 901 determines, based on the location information of the client device 902, that the client device 902 is approaching a space with little information in the three-dimensional map managed by the server 901, it issues a transmission request for sensor information to the client device 902 in order to generate a new three-dimensional map. The server 901 may also issue a transmission request for sensor information when it is desired to update the three-dimensional map, when it is desired to check road conditions such as during snowfall or a disaster, when it is desired to check traffic congestion conditions, or when it is desired to check incident and accident conditions, etc.

[0704] Furthermore, the client device 902 may set the amount of data of the sensor information to be transmitted to the server 901 depending on the communication state or bandwidth at the time of receiving a request to transmit the sensor information from the server 901. Setting the amount of data of the sensor information to be transmitted to the server 901 means, for example, increasing or decreasing the amount of the data itself or appropriately selecting a compression method.

[0705] 46 is a block diagram showing an example of the configuration of a client device 902. The client device 902 receives a three-dimensional map composed of a point cloud or the like from the server 901, and estimates the self-position of the client device 902 from three-dimensional data created based on sensor information of the client device 902. In addition, the client device 902 transmits the acquired sensor information to the server 901.

[0706] The client device 902 includes a data receiving unit 1011, a communication unit 1012, a reception control unit 1013, a format conversion unit 1014, multiple sensors 1015, a three-dimensional data creation unit 1016, a three-dimensional image processing unit 1017, a three-dimensional data storage unit 1018, a format conversion unit 1019, a communication unit 1020, a transmission control unit 1021, and a data transmission unit 1022.

[0707] The data receiving unit 1011 receives a three-dimensional map 1031 from the server 901. The three-dimensional map 1031 is data including a point cloud such as a WLD or a SWLD. The three-dimensional map 1031 may include either compressed data or uncompressed data.

[0708] The communication unit 1012 communicates with the server 901, and transmits data transmission requests (for example, requests to transmit a three-dimensional map) to the server 901.

[0709] The reception control unit 1013 exchanges information such as compatible formats with the communication destination via the communication unit 1012, and establishes communication with the communication destination.

[0710] The format conversion unit 1014 generates a three-dimensional map 1032 by performing format conversion and the like on the three-dimensional map 1031 received by the data receiving unit 1011. Furthermore, if the three-dimensional map 1031 is compressed or encoded, the format conversion unit 1014 performs decompression or decoding processing. Note that if the three-dimensional map 1031 is uncompressed data, the format conversion unit 1014 does not perform decompression or decoding processing.

[0711] The multiple sensors 1015 are a group of sensors, such as LIDAR, a visible light camera, an infrared camera, or a depth sensor, that acquire information about the outside of the vehicle in which the client device 902 is mounted, and generate sensor information 1033. For example, when the sensor 1015 is a laser sensor such as LIDAR, the sensor information 1033 is three-dimensional data such as a point cloud (point cloud data). Note that the number of sensors 1015 does not need to be multiple.

[0712] The three-dimensional data creation unit 1016 creates three-dimensional data 1034 of the surroundings of the host vehicle based on the sensor information 1033. For example, the three-dimensional data creation unit 1016 creates point cloud data with color information of the surroundings of the host vehicle using information acquired by the LIDAR and a visible light image acquired by a visible light camera.

[0713] The three-dimensional image processing unit 1017 performs self-position estimation processing of the vehicle using a three-dimensional map 1032 such as a received point cloud and three-dimensional data 1034 of the surroundings of the vehicle generated from the sensor information 1033. The three-dimensional image processing unit 1017 may generate three-dimensional data 1035 of the surroundings of the vehicle by combining the three-dimensional map 1032 and the three-dimensional data 1034, and perform self-position estimation processing using the generated three-dimensional data 1035.

[0714] The three-dimensional data storage unit 1018 stores a three-dimensional map 1032, three-dimensional data 1034, and three-dimensional data 1035, and the like.

[0715] The format conversion unit 1019 generates sensor information 1037 by converting the sensor information 1033 into a format supported by the receiving side. The format conversion unit 1019 may reduce the amount of data by compressing or encoding the sensor information 1037. Furthermore, the format conversion unit 1019 may omit processing when format conversion is not necessary. Furthermore, the format conversion unit 1019 may control the amount of data to be transmitted in accordance with a designated transmission range.

[0716] The communication unit 1020 communicates with the server 901, and receives data transmission requests (sensor information transmission requests) and the like from the server 901.

[0717] The transmission control unit 1021 exchanges information such as compatible formats with the communication destination via the communication unit 1020, and establishes communication.

[0718] The data transmission unit 1022 transmits the sensor information 1037 to the server 901. The sensor information 1037 includes information acquired by a plurality of sensors 1015, such as information acquired by a LIDAR, a luminance image acquired by a visible light camera, an infrared image acquired by an infrared camera, a depth image acquired by a depth sensor, sensor position information, and speed information.

[0719] Next, the configuration of the server 901 will be described. Fig. 47 is a block diagram showing an example of the configuration of the server 901. The server 901 receives sensor information transmitted from the client device 902, and creates three-dimensional data based on the received sensor information. The server 901 uses the created three-dimensional data to update a three-dimensional map managed by the server 901. In addition, the server 901 transmits the updated three-dimensional map to the client device 902 in response to a transmission request for the three-dimensional map from the client device 902.

[0720] The server 901 includes a data receiving unit 1111, a communication unit 1112, a receiving control unit 1113, a format conversion unit 1114, a three-dimensional data creation unit 1116, a three-dimensional data synthesis unit 1117, a three-dimensional data storage unit 1118, a format conversion unit 1119, a communication unit 1120, a transmission control unit 1121, and a data transmission unit 1122.

[0721] The data receiving unit 1111 receives sensor information 1037 from the client device 902. The sensor information 1037 includes, for example, information acquired by a LIDAR, a luminance image acquired by a visible light camera, an infrared image acquired by an infrared camera, a depth image acquired by a depth sensor, sensor position information, and speed information.

[0722] The communication unit 1112 communicates with the client device 902 and transmits a data transmission request (for example, a request to transmit sensor information) to the client device 902 .

[0723] The reception control unit 1113 exchanges information such as compatible formats with the communication destination via the communication unit 1112, and establishes communication.

[0724] When the received sensor information 1037 is compressed or encoded, the format conversion unit 1114 performs decompression or decoding processing to generate the sensor information 1132. Note that, when the sensor information 1037 is non-compressed data, the format conversion unit 1114 does not perform decompression or decoding processing.

[0725] The three-dimensional data creation unit 1116 creates three-dimensional data 1134 of the periphery of the client device 902 based on the sensor information 1132. For example, the three-dimensional data creation unit 1116 creates point cloud data with color information of the periphery of the client device 902 using information acquired by the LIDAR and visible light images acquired by a visible light camera.

[0726] A three-dimensional data synthesis unit 1117 synthesizes three-dimensional data 1134 created based on the sensor information 1132 with a three-dimensional map 1135 managed by the server 901, thereby updating the three-dimensional map 1135.

[0727] The three-dimensional data storage unit 1118 stores a three-dimensional map 1135 and the like.

[0728] The format conversion unit 1119 generates the three-dimensional map 1031 by converting the three-dimensional map 1135 into a format supported by the receiving side. The format conversion unit 1119 may reduce the amount of data by compressing or encoding the three-dimensional map 1135. Furthermore, the format conversion unit 1119 may omit processing when format conversion is not necessary. Furthermore, the format conversion unit 1119 may control the amount of data to be transmitted in accordance with a designated transmission range.

[0729] The communication unit 1120 communicates with the client device 902 and receives a data transmission request (a request to transmit a three-dimensional map) or the like from the client device 902 .

[0730] A transmission control unit 1121 exchanges information such as compatible formats with a communication destination via a communication unit 1120, and establishes communication.

[0731] The data transmission unit 1122 transmits the three-dimensional map 1031 to the client device 902. The three-dimensional map 1031 is data including a point cloud such as a WLD or a SWLD. The three-dimensional map 1031 may include either compressed data or uncompressed data.

[0732] Next, a description will be given of the operation flow of the client device 902. Fig. 48 is a flowchart showing the operation of the client device 902 when acquiring a three-dimensional map.

[0733] First, the client device 902 requests the server 901 to transmit a three-dimensional map (such as a point cloud) (S1001). At this time, the client device 902 may also transmit position information of the client device 902 obtained by GPS or the like, thereby requesting the server 901 to transmit a three-dimensional map related to the position information.

[0734] Next, the client device 902 receives the three-dimensional map from the server 901 (S1002). If the received three-dimensional map is compressed data, the client device 902 decodes the received three-dimensional map to generate an uncompressed three-dimensional map (S1003).

[0735] Next, the client device 902 creates three-dimensional data 1034 of the periphery of the client device 902 from sensor information 1033 obtained by the multiple sensors 1015 (S1004). Next, the client device 902 estimates its own position using the three-dimensional map 1032 received from the server 901 and the three-dimensional data 1034 created from the sensor information 1033 (S1005).

[0736] 49 is a flowchart showing an operation of the client device 902 when transmitting sensor information. First, the client device 902 receives a request to transmit sensor information from the server 901 (S1011). The client device 902 that has received the transmission request transmits the sensor information 1037 to the server 901 (S1012). Note that, when the sensor information 1033 includes a plurality of pieces of information obtained by a plurality of sensors 1015, the client device 902 may generate the sensor information 1037 by compressing each piece of information using a compression method suitable for each piece of information.

[0737] Next, the operation flow of the server 901 will be described. Fig. 50 is a flowchart showing the operation when the server 901 acquires sensor information. First, the server 901 requests the client device 902 to transmit sensor information (S1021). Next, the server 901 receives the sensor information 1037 transmitted from the client device 902 in response to the request (S1022). Next, the server 901 creates three-dimensional data 1134 using the received sensor information 1037 (S1023). Next, the server 901 reflects the created three-dimensional data 1134 in the three-dimensional map 1135 (S1024).

[0738] Fig. 51 is a flowchart showing the operation of the server 901 when transmitting a three-dimensional map. First, the server 901 receives a request to transmit a three-dimensional map from the client device 902 (S1031). The server 901 that has received the request to transmit the three-dimensional map transmits a three-dimensional map 1031 to the client device 902 (S1032). At this time, the server 901 may extract a three-dimensional map of the vicinity according to the position information of the client device 902, and transmit the extracted three-dimensional map. The server 901 may also compress the three-dimensional map composed of a point cloud using, for example, a compression method based on an octet structure, and transmit the compressed three-dimensional map.

[0739] A modification of this embodiment will now be described.

[0740] The server 901 creates three-dimensional data 1134 of the vicinity of the position of the client device 902 using the sensor information 1037 received from the client device 902. Next, the server 901 calculates the difference between the three-dimensional data 1134 and the three-dimensional map 1135 by matching the created three-dimensional data 1134 with a three-dimensional map 1135 of the same area managed by the server 901. If the difference is equal to or greater than a predetermined threshold, the server 901 determines that some abnormality has occurred in the vicinity of the client device 902. For example, when ground subsidence or the like occurs due to a natural disaster such as an earthquake, it is considered that a large difference occurs between the three-dimensional map 1135 managed by the server 901 and the three-dimensional data 1134 created based on the sensor information 1037.

[0741] The sensor information 1037 may include information indicating at least one of the type of sensor, the performance of the sensor, and the model number of the sensor. In addition, a class ID or the like according to the performance of the sensor may be added to the sensor information 1037. For example, when the sensor information 1037 is information acquired by LIDAR, it is possible to assign an identifier to the performance of the sensor, such as class 1 for a sensor that can acquire information with an accuracy of several millimeters, class 2 for a sensor that can acquire information with an accuracy of several centimeters, and class 3 for a sensor that can acquire information with an accuracy of several meters. In addition, the server 901 may estimate the performance information of the sensor from the model number of the client device 902. For example, when the client device 902 is mounted on a vehicle, the server 901 may determine the spec information of the sensor from the model of the vehicle. In this case, the server 901 may acquire information on the model of the vehicle in advance, or the information may be included in the sensor information. In addition, the server 901 may use the acquired sensor information 1037 to switch the degree of correction for the three-dimensional data 1134 created using the sensor information 1037. For example, when the sensor performance is high accuracy (class 1), the server 901 does not perform correction on the three-dimensional data 1134. When the sensor performance is low accuracy (class 3), the server 901 applies correction according to the accuracy of the sensor to the three-dimensional data 1134. For example, the server 901 increases the degree (strength) of correction as the accuracy of the sensor decreases.

[0742] The server 901 may simultaneously issue requests to send sensor information to multiple client devices 902 in a certain space. When the server 901 receives multiple pieces of sensor information from multiple client devices 902, the server 901 does not need to use all of the sensor information to create the three-dimensional data 1134, and may select the sensor information to be used according to the performance of the sensor, for example. For example, when updating the three-dimensional map 1135, the server 901 may select high-precision sensor information (class 1) from the multiple pieces of sensor information received, and create the three-dimensional data 1134 using the selected sensor information.

[0743] The server 901 is not limited to a server such as a traffic monitoring cloud, but may be another client device (mounted in a vehicle). Figure 52 is a diagram showing the system configuration in this case.

[0744] For example, client device 902C issues a request to send sensor information to nearby client device 902A and acquires the sensor information from client device 902A. Client device 902C then creates three-dimensional data using the acquired sensor information of client device 902A and updates the three-dimensional map of client device 902C. This allows client device 902C to generate a three-dimensional map of the space that can be acquired from client device 902A by taking advantage of the performance of client device 902C. For example, it is considered that such a case occurs when client device 902C has high performance.

[0745] In this case, the client device 902A that provided the sensor information is given the right to obtain the high-precision 3D map generated by the client device 902C. The client device 902A receives the high-precision 3D map from the client device 902C in accordance with the right.

[0746] In addition, the client device 902C may issue a request to transmit sensor information to multiple nearby client devices 902 (client device 902A and client device 902B). If the sensor of the client device 902A or the client device 902B is high performance, the client device 902C can create three-dimensional data using the sensor information obtained by the high performance sensor.

[0747] 53 is a block diagram showing the functional configuration of a server 901 and a client device 902. The server 901 includes, for example, a 3D map compression / decoding processing unit 1201 that compresses and decodes a 3D map, and a sensor information compression / decoding processing unit 1202 that compresses and decodes sensor information.

[0748] The client device 902 includes a three-dimensional map decoding processing unit 1211 and a sensor information compression processing unit 1212. The three-dimensional map decoding processing unit 1211 receives encoded data of the compressed three-dimensional map and decodes the encoded data to obtain the three-dimensional map. The sensor information compression processing unit 1212 compresses the sensor information itself instead of the three-dimensional data created from the acquired sensor information, and transmits the encoded data of the compressed sensor information to the server 901. With this configuration, the client device 902 only needs to internally hold a processing unit (device or LSI) that performs processing to decode the three-dimensional map (point cloud, etc.), and does not need to internally hold a processing unit that performs processing to compress the three-dimensional data of the three-dimensional map (point cloud, etc.). This makes it possible to reduce the cost and power consumption of the client device 902.

[0749] As described above, the client device 902 according to this embodiment is mounted on a moving body, and creates three-dimensional data 1034 of the surroundings of the moving body from sensor information 1033 indicating the surrounding conditions of the moving body, obtained by a sensor 1015 mounted on the moving body. The client device 902 estimates the self-position of the moving body using the created three-dimensional data 1034. The client device 902 transmits the acquired sensor information 1033 to the server 901 or another moving body 902.

[0750] According to this, the client device 902 transmits the sensor information 1033 to the server 901 or the like. This may reduce the amount of data to be transmitted compared to the case of transmitting three-dimensional data. Also, since the client device 902 does not need to perform processing such as compression or encoding of the three-dimensional data, the amount of processing by the client device 902 can be reduced. Therefore, the client device 902 can reduce the amount of data to be transmitted or simplify the device configuration.

[0751] Moreover, the client device 902 further transmits a request to the server 901 to transmit a three-dimensional map, and receives a three-dimensional map 1031 from the server 901. The client device 902 estimates its own location using the three-dimensional data 1034 and the three-dimensional map 1032.

[0752] The sensor information 1033 includes at least one of information obtained by a laser sensor, a luminance image, an infrared image, a depth image, sensor position information, and sensor speed information.

[0753] Furthermore, the sensor information 1033 includes information indicating the performance of the sensor.

[0754] Furthermore, the client device 902 encodes or compresses the sensor information 1033, and transmits the encoded or compressed sensor information 1037 to the server 901 or another mobile body 902. This allows the client device 902 to reduce the amount of data to be transmitted.

[0755] For example, the client device 902 includes a processor and a memory, and the processor uses the memory to perform the above-mentioned processing.

[0756] Furthermore, the server 901 according to this embodiment is capable of communicating with a client device 902 mounted on the mobile object, and receives sensor information 1037 indicating the surrounding conditions of the mobile object, obtained by a sensor 1015 mounted on the mobile object, from the client device 902. The server 901 creates three-dimensional data 1134 of the surroundings of the mobile object from the received sensor information 1037.

[0757] According to this, the server 901 creates three-dimensional data 1134 using the sensor information 1037 transmitted from the client device 902. This may reduce the amount of data transmitted compared to when the client device 902 transmits three-dimensional data. In addition, since the client device 902 does not need to perform processing such as compression or encoding of the three-dimensional data, the amount of processing by the client device 902 can be reduced. Therefore, the server 901 can reduce the amount of data transmitted or simplify the device configuration.

[0758] Moreover, the server 901 further transmits a request to the client device 902 to transmit the sensor information.

[0759] Furthermore, the server 901 further updates a three-dimensional map 1135 using the created three-dimensional data 1134 , and transmits the three-dimensional map 1135 to the client device 902 in response to a transmission request for the three-dimensional map 1135 from the client device 902 .

[0760] The sensor information 1037 includes at least one of information obtained by a laser sensor, a luminance image, an infrared image, a depth image, sensor position information, and sensor speed information.

[0761] Additionally, the sensor information 1037 includes information indicating the performance of the sensor.

[0762] Moreover, the server 901 further corrects the three-dimensional data in accordance with the performance of the sensor, thereby enabling the three-dimensional data creation method to improve the quality of the three-dimensional data.

[0763] Furthermore, in receiving the sensor information, the server 901 receives a plurality of pieces of sensor information 1037 from a plurality of client devices 902, and selects the sensor information 1037 to be used for creating the three-dimensional data 1134 based on a plurality of pieces of information indicating the performance of the sensors included in the plurality of pieces of sensor information 1037. This allows the server 901 to improve the quality of the three-dimensional data 1134.

[0764] Furthermore, the server 901 decodes or expands the received sensor information 1037, and creates three-dimensional data 1134 from the decoded or expanded sensor information 1132. This allows the server 901 to reduce the amount of data to be transmitted.

[0765] For example, the server 901 includes a processor and a memory, and the processor uses the memory to perform the above-mentioned processing.

[0766] Although the server and client device according to the embodiment of the present disclosure have been described above, the present disclosure is not limited to this embodiment.

[0767] Furthermore, each processing unit included in the server and client devices according to the above-described embodiments is typically realized as an LSI, which is an integrated circuit. These may be implemented individually as single chips, or may be implemented as a single chip that includes some or all of the components.

[0768] The integrated circuit is not limited to an LSI, but may be realized by a dedicated circuit or a general-purpose processor. A field programmable gate array (FPGA) that can be programmed after the LSI is manufactured, or a reconfigurable processor that can reconfigure the connections and settings of the circuit cells inside the LSI may also be used.

[0769] In each of the above embodiments, each component may be implemented by dedicated hardware or by executing a software program suitable for each component. Each component may be implemented by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0770] Furthermore, the present disclosure may be realized as a three-dimensional data creation method executed by a server and a client device, etc.

[0771] In addition, the division of functional blocks in the block diagram is an example, and multiple functional blocks may be realized as one functional block, one functional block may be divided into multiple blocks, or some functions may be transferred to another functional block. Furthermore, the functions of multiple functional blocks having similar functions may be processed in parallel or in a time-sharing manner by a single piece of hardware or software.

[0772] In addition, the order in which each step is performed in the flowchart is merely an example for specifically explaining the present disclosure, and an order other than the above may be used. In addition, some of the steps may be performed simultaneously (in parallel) with other steps.

[0773] Although the server and client devices according to one or more aspects have been described based on the embodiments, the present disclosure is not limited to these embodiments. As long as it does not deviate from the spirit of the present disclosure, various modifications conceived by a person skilled in the art to the present embodiment and forms constructed by combining components in different embodiments may also be included within the scope of one or more aspects. [Industrial Applicability]

[0774] The present disclosure is applicable to client devices and servers that create three-dimensional data. [Explanation of symbols]

[0775] 100, 400 3D data encoding device 101, 201, 401, 501 Acquisition Department 102, 402 Coding area determination unit 103 Split part 104, 644 encoder 111,607 3D data 112, 211, 413, 414, 511, 634 Encoded three-dimensional data 200, 500 Three-dimensional data decoding device 202 Decoding start GOS determination unit 203 Decoding SPC Determination Unit 204, 625 Decoding section 212, 512, 513 Decoded 3D data 403 SWLD extraction part 404 WLD encoder 405 SWLD encoding section 411 Input 3D data 412 Extracted 3D data 502 Header parser 503 WLD Decoding Unit 504 SWLD Decryption Unit 600 Vehicle 601 Nearby vehicles 602, 605 Sensor detection range 603, 606 area 604 Occlusion Area 620, 620A 3D data creation device 621, 641 3D Data Creation Department 622 Request Range Determination Unit 623 Search Department 624, 642 Receiver 626 Synthesis Section 627 Detection Area Determination Unit 628 Surrounding Condition Detection Unit 629 Autonomous operation control unit 631, 651 Sensor information 632 1st 3D Data 633 Request Scope Information 635 2nd 3D data 636 3rd Dimensional Data 637 Request Signal 638 Send Data 639 Surrounding situation detection results 640, 640A 3D data transmission device 643 Extraction part 645 Transmitter 646 Transmission Possibility Judgment Unit 652 5th 3D data 654 6th 3D Data 700 Three-dimensional information processing device 701 3D map acquisition unit 702 Vehicle detection data acquisition unit 703 Abnormal Case Judgment Unit 704 Countermeasure action decision unit 705 Motion control section 711 3D Map 712 Vehicle detection 3D data 801 vehicles 802 Space 810 Three-dimensional data creation device 811 Data receiving unit 812, 819 Communications Department 813 Reception control section 814, 821 Format conversion unit 815 Sensors 816 3D Data Creation Department 817 3D Data Synthesis Department 818 Three-dimensional data storage unit 820 Transmission control section 822 Data transmission unit 831, 832, 834, 835, 836, 837 3D data 833 Sensor Information 901 Server 902, 902A, 902B, 902C Client devices 1011, 1111 Data receiving unit 1012, 1020, 1112, 1120 Communications Department 1013, 1113 Reception control section 1014, 1019, 1114, 1119 format conversion unit 1015 Sensor 1016, 1116 3D Data Creation Department 1017 Three-dimensional image processing unit 1018, 1118 3D Data Storage Unit 1021, 1121 Transmission control section 1022, 1122 Data transmission unit 1031, 1032, 1135 3D Map 1033, 1037, 1132 Sensor information 1034, 1035, 1134 3D data 1117 3D Data Synthesis Department 1201 3D map compression / decoding processing unit 1202 Sensor information compression / decoding processing unit 1211 3D map decoding processing unit 1212 Sensor information compression processing unit

Claims

1. 1. A method implemented by a client device having a first sensor and a second sensor, comprising: acquiring first sensor data using the first sensor; acquiring second sensor data using the second sensor; Create combined data including three-dimensional coordinate values ​​and color information of multiple points, the three-dimensional coordinate values ​​are obtained from the first sensor data, and the color information is obtained from the second sensor data; transmitting sensor information including the first sensor data and the second sensor data to a server when a difference between the combined data and the three-dimensional map is greater than a predetermined threshold; method.

2. 2. The method of claim 1, further comprising: estimating a location of the client device using the combined data and the three-dimensional map; method.

3. 10. The method of claim 1 further comprising: acquiring third sensor data using a third sensor; The sensor information further includes the third sensor data, The third sensor data is not used to generate the combined data. method.

4. 2. The method of claim 1 , The sensor information includes information indicating positions of the first sensor and the second sensor. method.

5. 2. The method of claim 1 , The sensor information further includes information indicating an estimation accuracy of the positions of the plurality of points acquired by the first sensor. method.

6. A client device, a first sensor for acquiring first sensor data; a second sensor for acquiring second sensor data; a processor for generating combined data including three-dimensional coordinate values ​​and color information of a plurality of points; the three-dimensional coordinate values ​​are obtained from the first sensor data, and the color information is obtained from the second sensor data; transmitting sensor information including the first sensor data and the second sensor data to a server when a difference between the combined data and the three-dimensional map is greater than a predetermined threshold; Client device.

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