Information processing device

Abstract

To add height information to road map data.SOLUTION: An information processing device is configured to: acquire road map data including one or more pieces of road location information; acquire point group data having coordinate information and height information about each of a plurality of points on a road within a range of the road map data; and add height information to one or more points corresponding to a road included in the road map data on the basis of the point group data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to collecting road information. [Background technology]

[0002] There is a technology that uses point cloud data obtained by laser surveying or the like to generate highly accurate map data. In this regard, for example, Patent Document 1 discloses an invention related to a system that identifies the coordinates of a road surface based on point cloud data. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-111060 A Summary of the Invention [Problem to be solved by the invention]

[0004] The present disclosure aims to add altitude information to road map data. [Means for solving the problem]

[0005] One aspect of the present disclosure is to The information processing device has a control unit that executes the following operations: acquiring road map data including position information of one or more roads; acquiring point cloud data having coordinate information and height information for each of a plurality of points on a road within the range of the road map data acquired by sensing; and assigning height information to one or more points corresponding to roads included in the road map data based on the point cloud data.

[0006] Further, other aspects include a method executed by the above-mentioned information processing device, a program for causing a computer to execute the method, or a computer-readable storage medium non-transiently storing the program. Effect of the Invention

[0007] According to the present disclosure, altitude information can be added to road map data. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram for explaining an overview of a system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating the configuration of the server device 1. [Diagram 3] FIG. 2 is a diagram for explaining point cloud data acquired by the server device 1. [Figure 4] FIG. 4 is a diagram for explaining the arrangement of evaluation points and measurement points. [Diagram 5] 5A and 5B are diagrams for explaining a process of determining an up-down relationship of a road. [Figure 6] 4 is a flowchart of a process executed by the server device 1. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] There is a technology to obtain point cloud data by aerial surveying and use it for generating maps, etc. In aerial surveying, for example, a device such as LiDAR is mounted on an aircraft, laser light is emitted to the ground surface, and the arrival time of the reflected wave is measured, making it possible to measure the unevenness of the ground surface.

[0010] The area on the ground that is covered by a laser beam emitted from an aircraft is called a footprint. In aerial surveying, the laser beam is emitted multiple times at different positions (measurement points) within the footprint. In other words, one footprint contains multiple measurement points. The coordinates and height of each measurement point can be calculated by performing calculations using the aircraft's position information, altitude information, and attitude information on the raw data obtained from the aircraft. A collection of information obtained at one or more measurement points is also called point cloud data. Point cloud data is composed of, for example, three-dimensional coordinate information of the measurement points. By using point cloud data obtained through aerial surveying, it is possible to generate highly accurate three-dimensional maps.

[0011] Generally, road map data used for car navigation and the like is expressed on a two-dimensional plane. At points where roads intersect, it may be indicated whether an intersection or a multi-level intersection exists, but such road map data does not include height information of the road surface. However, in anticipation of the future spread of autonomous driving, it is preferable to add height information to the road map data. The information processing device according to the present disclosure uses point cloud data to add elevation information to road map data.

[0012] An information processing device according to one embodiment has a control unit that executes the following operations: acquiring road map data including position information of one or more roads; acquiring point cloud data having coordinate information and height information for each of a plurality of points on a road within the range of the road map data acquired by sensing; and assigning height information to one or more points corresponding to roads included in the road map data based on the point cloud data.

[0013] Point cloud data is typically a set of three-dimensional coordinates obtained by measuring the earth's surface. The point cloud data may be generated based on data acquired by an air vehicle such as a manned aircraft or a drone. For example, by irradiating the earth's surface with laser light from the sky and measuring the reflected light, the coordinates of the earth's surface including height information can be generated. When the aircraft performs measurements using LiDAR, the control unit may generate the point cloud data based on a LiDAR image (range image).

[0014] The point cloud data may be generated based on data acquired by a moving object traveling on the ground. For example, if the moving object has a GPS receiver, it can acquire probe data including the coordinates and altitude of the vehicle. The control unit may generate the point cloud data based on such probe data.

[0015] The control unit assigns elevation information to points corresponding to roads included in the road map data, based on the point cloud data acquired within the range of the road map data.

[0016] Since a road has a certain width, it is preferable that the control unit sets a point (evaluation point) on the road to which height information is to be added, and it is also preferable that the control unit appropriately associates the set evaluation point with one or more measurement points, and calculates the height information based on the association.

[0017] For example, when a plurality of measurement points correspond to one evaluation point, the final height to be assigned to the evaluation point may be calculated from the height information indicated by the plurality of measurement points.

[0018] Furthermore, the control unit may determine the vertical relationship of two or more intersecting roads based on the height information added to the evaluation points on the roads. For example, when there is a point where two roads intersect, it can determine that "one road straddles the other road" by referring to the height information added to each road.

[0019] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The configurations of the following embodiments are merely examples, and the present disclosure is not limited to the configurations of the embodiments.

[0020] First Embodiment An overview of a road map system according to a first embodiment will be described. The road map system according to this embodiment includes a server device 1 that adds height information to roads included in road map data, and devices that provide data to the server device 1 (a map server 2 and a data server 3). The map server 2 is a device that provides road map data, and the data server 3 is a device that provides point cloud data obtained by aerial surveying.

[0021] An overview of the processing performed by the system will be described with reference to FIG. The server device 1 acquires point cloud data obtained by aerial surveying from the data server 3. The point cloud data is acquired in footprint units. A footprint is an area irradiated with a beam of laser light used in aerial surveying. The point cloud data includes values ​​(e.g., three-dimensional coordinates) calculated based on measurement results at measurement points. One footprint includes, for example, tens of thousands of point cloud data. The server device 1 stores the acquired point cloud data in a storage device. In the following description, the term "point cloud data" refers to a collection of coordinate information measured at a plurality of measurement points.

[0022] The server device 1 also acquires road map data to which the height information is to be added from the map server 2. The road map data is map data in which a road network in a certain area is defined. The road map data may be, for example, data in which the road network is expressed by links and nodes. It is preferable that the road map data defines a geographical area corresponding to the road. In this embodiment, the road map data is data in which a plurality of roads are defined by segments (hereinafter, road segments). A road segment is a unit section of a road, and may be, for example, a division of a road in the extension direction at intervals of 10 m.

[0023] The server device 1 acquires road map data corresponding to a predetermined range from the map server 2, and acquires point cloud data corresponding to the same range from the data server 3, based on an operation by an operator. Based on these data, the server device 1 assigns height information to points on the road included in the specified range. In this embodiment, the server device 1 sets points (hereinafter referred to as evaluation points) to which height information is assigned on the target road, and calculates the height for each of the set evaluation points. The height may be expressed by altitude or above sea level, or by height from a reference surface. In addition, the evaluation points may be set at a predetermined interval along the extension of the road, or may be set in a mesh pattern within the area corresponding to the road.

[0024] The server device 1 can output road map data to which altitude information has been added. For example, the server device 1 may provide the road map data to which altitude information has been added to an external device that manages a map for autonomous driving (or for electric vehicles). By using height information to operate a vehicle, it will be possible, for example, to improve the accuracy of autonomous driving and reduce the fuel consumption of electric vehicles.

[0025] [Device configuration] FIG. 2 is a diagram showing an example of the configuration of the server device 1. As shown in FIG. The server device 1 is, for example, a computer such as a personal computer, a smartphone, a mobile phone, a tablet computer, a personal digital assistant, etc. The server device 1 includes a control unit 11, a storage unit 12, a communication unit 13, and an input / output unit .

[0026] The server device 1 is configured to be able to acquire point cloud data acquired by aerial surveying using an aircraft from the data server 3. The server device 1 is also configured to be able to acquire road map data in which a road network is defined from the map server 2. The server device 1 assigns elevation information to points on roads included in the road map data based on the acquired point cloud data, and outputs the result.

[0027] The server device 1 can be configured as a computer having a processor (CPU, GPU, etc.), a main storage device (RAM, ROM, etc.), and an auxiliary storage device (EPROM, hard disk drive, removable media, etc.). The auxiliary storage device stores an operating system (OS), various programs, various tables, etc., and by executing the programs stored therein, various functions (software modules) that match a predetermined purpose, as described below, can be realized. However, some or all of the functions may be realized as hardware modules by hardware circuits such as ASICs and FPGAs.

[0028] The control unit 11 is a computing unit that executes a predetermined program to realize various functions of the server device 1. The control unit 11 can be realized by a hardware processor such as a CPU. The control unit 11 may also be configured to include a RAM, a ROM (Read Only Memory), a cache memory, and the like.

[0029] The control unit 11 is configured to have two software modules: an acquisition unit 111 and a generation unit 112. Each software module may be realized by causing the control unit 11 (such as a CPU) to execute a program stored in the storage unit 12, which will be described later.

[0030] The acquisition unit 111 acquires point cloud data obtained by aerial surveying from the data server 3 via a specified interface. Point cloud data is a set of coordinates (X coordinate, Y coordinate, Z coordinate) in a three-dimensional space. The coordinates may be, for example, a combination of latitude, longitude, and altitude expressed in a specified geodetic system. In aerial surveying, a laser pulse is irradiated from an aircraft to the ground surface, and the three-dimensional coordinates corresponding to a certain measurement point can be obtained based on the information obtained by the reflected pulse and the results of measuring the position and attitude of the aircraft. Note that the coordinates corresponding to the point cloud data may be corrected for the effects of buildings, trees, etc.

[0031] The point cloud data is associated with a footprint. A footprint is an area (laser spot) irradiated with a light beam of a laser pulse used in aerial surveying. In this embodiment, information identifying a geographical area of ​​the footprint and point cloud data acquired within the footprint are input to the server device 1 in an associated state.

[0032] The point cloud data acquired by the acquisition unit 111 is stored in a point cloud database provided in the storage unit 12, which will be described later.

[0033] Furthermore, the acquisition unit 111 acquires road map data of a predetermined range from the map server 2. For example, when an operator of the device designates an area to which height information is to be added, the acquisition unit 111 downloads road map data of the corresponding area from the map server 2. The area may be designated by a graphic form or by an administrative division or the like. The acquired road map data is stored in the storage unit 12.

[0034] The generating unit 112 executes a process of adding elevation information to road map data based on an instruction from an operator. Specifically, the generating unit 112 executes a process of extracting point cloud data acquired within a specified area from the storage unit 12, and a process of adding elevation information to roads included in the target area. The generating unit 112 performs a process of setting a point (evaluation point) to which height information is to be assigned. Then, the generating unit 112 associates the evaluation point with one or more point cloud data, and assigns height information to the evaluation point based on the association. A specific method will be described later.

[0035] Furthermore, the generating unit 112 updates the road map data based on the result of adding the altitude information, and provides the updated road map data to the outside.

[0036] The storage unit 12 is a means for storing information, and is configured with storage media such as RAM, a magnetic disk, a flash memory, etc. The storage unit 12 stores programs executed by the control unit 11, data used by the programs, etc.

[0037] The storage unit 12 stores a point cloud database, which is a database in which point cloud data is stored, and road map data.

[0038] 3 is an example of point cloud data. In this example, one record is assigned to one measurement point. The point cloud data includes an ID corresponding to the measurement point, an ID of a footprint including the measurement point, location information (e.g., latitude and longitude), and altitude information (e.g., elevation). The footprint ID may be used as an index for extracting a record from the point cloud data.

[0039] The communication unit 13 is a wireless communication interface for connecting the server device 1 to a network. The communication unit 13 is configured to be able to communicate with the map server 2 and the data server 3 via, for example, a wireless LAN or a mobile communication service such as 3G, 4G, or 5G.

[0040] The input / output unit 14 is a unit that receives input operations performed by an operator of the device and presents information to the operator. In this embodiment, it is made up of a single touch panel display. That is, it is made up of a liquid crystal display and its control means, and a touch panel and its control means.

[0041] The specific hardware configuration of the server device 1 may include omitted, replaced, or added components as appropriate depending on the embodiment. For example, the control unit 11 may include multiple hardware processors. The hardware processor may be configured with a microprocessor, FPGA, GPU, or the like. Input / output devices other than those illustrated (for example, an optical drive, etc.) may also be added. The server device 1 may be configured with multiple computers. In this case, the hardware configurations of the computers may or may not be the same.

[0042] The map server 2 is a device that provides road map data of a specified range in response to a request from the server device 1. The road map data may be, for example, data that represents a road network by links and nodes, or data that defines a geographical area corresponding to a road. In this embodiment, the road map data is data that defines a plurality of roads by segments.

[0043] The data server 3 is a device that stores point cloud data obtained by aerial surveying and provides it to the server device 1. The data server 3 extracts point cloud data acquired within a range specified by the server device 1 from a database and provides it.

[0044] The map server 2 and the data server 3 can also be configured by a computer having a processor and a storage device, similar to the server device 1.

[0045] [How to add height information] Next, a process in which the server device 1 adds altitude information to road map data based on a request from an operator will be described in detail.

[0046] The server device 1 receives a request including an area for which height information is to be added to roads from an operator of the device. In response to this, the server device receives road map data corresponding to the specified area from the map server 2. Roads included in the road map data are made up of multiple road segments. In other words, the server device 1 can specify multiple road segments of multiple roads included in the specified area as targets for processing.

[0047] In addition, the server device 1 acquires the point cloud data from the data server 3. It is noted that the acquisition of the point cloud data or the road map data does not matter which one comes first. If the point cloud data is acquired first, the server device 1 may extract the point cloud data corresponding to the range of the road map data from the storage unit and use it. If the road map data is acquired first, the server device 1 may acquire the point cloud data corresponding to the range of the road map data from the data server 3.

[0048] The server device 1 executes a process of assigning elevation information to each of a plurality of road segments to be processed. Specifically, the server device 1 sets an evaluation point for each of the plurality of road segments, and calculates the elevation corresponding to the evaluation point based on the point cloud data.

[0049] The method for setting the evaluation points will be described. Fig. 4(A) is a diagram showing an example of a method for setting evaluation points for road segments. In this example, three road segments 401 to 403 are shown. The road segments may be divided into predetermined distances, such as 5 meters, 10 meters, etc. For example, one evaluation point can be set for each road segment.

[0050] FIG. 4(B) is a diagram showing another example of a method for setting evaluation points for a road segment. As shown in the figure, a road segment may include multiple evaluation points. The multiple evaluation points may be set in a mesh shape at a predetermined interval, for example. In the example shown in the figure, four evaluation points are set for one road segment, but there is no limit to the number of evaluation points.

[0051] In this embodiment, the server device 1 calculates the height of each of the multiple evaluation points that have been set by using point cloud data. Fig. 4(C) is a diagram showing the positional relationship between the set evaluation points (black circles) and the measurement points (white circles) located near the evaluation points.

[0052] There are several methods for calculating the height of an evaluation point, including the following: (Method A) The height of the measurement point closest to the evaluation point is used as the height of the evaluation point. For example, in the illustrated example, the height of measurement point A3 is the height of evaluation point A. (Method B) The height of the evaluation point is determined by taking the average of the heights of the points within a specified area (shown by a dashed circle) centered on the evaluation point. For example, in the illustrated example, the average value of the heights of the measurement points A1 to A6 becomes the height of the evaluation point A. When calculating the average, weighting may be performed using, for example, a Gaussian filter. (Method C) A method in which the height of the evaluation point is determined as the height of the lowest measurement point among the points within a specified circle centered on the evaluation point. For example, in the illustrated example, the height of the lowest point among the measurement points A1 to A6 is the height of the evaluation point A.

[0053] The above-mentioned method is merely an example, and it is also possible to calculate the height information for the evaluation point using a method other than the above.

[0054] [Determining the hierarchical relationship of roads] However, in the above-mentioned method, there are cases where accurate height information cannot be obtained at locations where roads cross over each other. This will be described. 5A is a cross-sectional view of a first road extending in the left-right direction. Here, six evaluation points, A to F, are set as evaluation points. The first road intersects with another second road via an overpass at the point indicated by the dashed line.

[0055] In this situation, when the height is calculated for each evaluation point, the result shown in Figure 5(B) is obtained. That is, the height of the second road is determined for evaluation point C. In this case, the calculated height for evaluation point C should not be used as the height of the first road.

[0056] For this reason, in the process of calculating height information, if there is an evaluation point whose height is not consistent with the preceding and succeeding evaluation points, the server device 1 may execute a process of excluding the evaluation point from the calculation target. An example of a case where the height is not consistent is, for example, "a case where the height increment between the evaluation points exceeds a predetermined value." For example, if the distance between the evaluation points B and C is 10 meters but the height increment is 5 meters or more, it can be determined that the heights are not consistent. Another example of a case where the heights are not consistent is when the gradient between the evaluation points exceeds a predetermined value. For example, when the maximum expected road gradient is set to 10% and the gradient between the evaluation points exceeds 10%, it can be determined that the heights are not consistent.

[0057] In such a case, the height calculation process may be skipped if the target evaluation point overlaps with another road segment on the XY plane. Note that the skipped evaluation point is processed again when processing is performed for the second road.

[0058] [Processing flow] Next, a description will be given of the flow of the process executed by the server device 1. FIG 6 is a flow chart of the process executed by the server device 1. It is assumed that before the illustrated process starts, the server device 1 acquires and stores point cloud data from the data server 3.

[0059] First, in step S11, the acquisition unit 111 determines a road segment to be processed. In this step, for example, an operator of the device specifies an area for which height information is to be added to roads, and the acquisition unit 111 acquires this. The acquisition unit 111 acquires road map data corresponding to the specified area from the map server 2, and identifies multiple road segments of multiple roads included in the specified area as processing targets.

[0060] The processes in steps S12 to S16 are executed for each road segment to be processed.

[0061] In step S12, the generation unit 112 sets an evaluation point for the road segment to be processed. One evaluation point may be set for each road segment, or multiple evaluation points may be set. This may be done. The processes in steps S13 to S16 are executed for each of the set evaluation points.

[0062] In step S13, the generation unit 112 calculates the height for the evaluation point. Here, the generation unit 112 identifies measurement points corresponding to the evaluation point by the method described above, and determines the height corresponding to the evaluation point using the height information of each measurement point.

[0063] In step S14, the generation unit 112 determines whether the height determined in step S13 is consistent with the previous and next evaluation points. For example, if the height of the target evaluation point has increased (or decreased) by a predetermined value or more (or by a predetermined ratio or more) compared to the height of the previous evaluation point, it can be determined that the heights are not consistent. If the determination in this step is positive, the process proceeds to step S15. If the determination in this step is negative, the process proceeds to step S16.

[0064] In step S15, the generation unit 112 assigns the calculated height to the target evaluation point.

[0065] In step S16, the generation unit 112 determines whether the evaluation point determined to have a height inconsistency compared to the preceding and following evaluation points overlaps with another road (road segment). For example, if the target evaluation point overlaps with another road area on the road map, this step is determined to be positive. If this step is determined to be positive, no height information is assigned to the evaluation point determined to be inconsistent in step S14. This is because it can be assumed that the height of the other road has been acquired for the evaluation point (i.e., the road segment being processed passes under the other road).

[0066] If the target evaluation point does not overlap with other road areas on the road map, the result of this step is negative. If the result of this step is negative, the process may proceed to step S15, where elevation information may be added to the target evaluation point. In such a case, the elevation may not be calculated correctly due to other factors, and the operator of the device may be notified of this.

[0067] Although not shown in the flowchart, the server device 1 may execute a process of outputting the road map data to which the height information has been added to the outside after the addition of the height information to all road segments has been completed.

[0068] As described above, the server device 1 according to the first embodiment sets multiple evaluation points on roads included in road map data, and assigns elevation information to the evaluation points based on point cloud data acquired by aerial surveying. In addition, by checking whether the heights of evaluation points are consistent, it is possible to accurately detect points where roads intersect at different altitudes. According to this configuration, it becomes possible to generate road map data including height information, which makes it possible to improve the accuracy of autonomous driving and the fuel economy of electric vehicles.

[0069] (Modification 1 of the first embodiment) In the first embodiment, the data server 3 stores the point cloud and provides it to the server device 1. However, the point cloud data may be generated by the server device 1. For example, a LiDAR image generated by an aerial survey may be stored in the data server 3, and the acquisition unit 111 may acquire the LiDAR image. In this case, the acquisition unit 111 analyzes the acquired LiDAR image and generates the point cloud data. The data may be converted into

[0070] The point cloud data may be generated using a method other than laser surveying. For example, GPS data obtained by a probe car may be stored in the data server 3, and the acquisition unit 111 may acquire this data. The GPS data is data including position information (latitude, longitude, and altitude). In this case, the acquisition unit 111 may execute a process of converting the acquired GPS data into point cloud data.

[0071] (Modification 2 of the first embodiment) In the first embodiment, the server device 1 assigns height information represented by numerical values ​​such as sea level or altitude to evaluation points on roads. On the other hand, the server device 1 may generate road map data including only information related to the up-down relationship of roads. For example, when there are locations where roads intersect due to an overpass or underpass, road map data may be generated that includes information for each intersection, such as which road passes above the other. In this case, the generated road map data does not need to include numerical information such as the elevation of the road or above sea level.

[0072] For example, the server device 1 may extract mutually intersecting road segments from the road map data, and determine which road passes above by determining the change in height along the traveling direction, and reflect the determination result in the road map data. Fig. 4(D) shows an example of intersecting road segments. In this case, for example, by determining the change in height at evaluation points A→B→C and the change in height at evaluation points D→B→E, it is possible to determine which road segment passes above.

[0073] (Modification) The above-described embodiment is merely an example, and the present disclosure can be modified and implemented as appropriate without departing from the spirit and scope of the present disclosure. For example, the processes and means described in this disclosure can be freely combined and implemented as long as no technical contradiction occurs.

[0074] In the embodiment, the device providing the point cloud data and the device providing the road map data are separate devices, but they may be the same device. Also, the server device 1 may be provided with an interface for reading the point cloud data.

[0075] Furthermore, a process described as being performed by one device may be shared and executed by multiple devices. Alternatively, a process described as being performed by different devices may be executed by one device. In a computer system, the hardware configuration (server configuration) by which each function is realized can be flexibly changed.

[0076] The present disclosure can also be realized by supplying a computer program implementing the functions described in the above embodiments to a computer, and having one or more processors of the computer read and execute the program. Such a computer program may be provided to the computer by a non-transitory computer-readable storage medium connectable to the system bus of the computer, or may be provided to the computer via a network. Non-transitory computer-readable storage media include, for example, any type of disk, such as a magnetic disk (floppy disk, hard disk drive (HDD), etc.), an optical disk (CD-ROM, DVD disk, Blu-ray disk, etc.), a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic card, a flash memory, an optical card, and any type of medium suitable for storing electronic instructions. [Explanation of symbols]

[0077] 1. Server device 11. Control section 12...Storage section 13. Communications Department

Claims

1. obtaining road map data including location information for one or more roads; acquiring point cloud data having coordinate information and height information for each of a plurality of points on a road within a range of the road map data acquired by sensing; assigning elevation information to one or more points corresponding to roads included in the road map data based on the point cloud data; A control unit that executes Information processing device.

2. The control unit generates the point cloud data based on a LiDAR image acquired by a satellite or an aircraft. The information processing device according to claim 1 .

3. The point cloud data includes a plurality of measurement points having coordinate information and height information, the control unit sets an evaluation point within an area corresponding to a road included in the road map data, and associates the evaluation point with one or more of the measurement points. The information processing device according to claim 1 .

4. The control unit generates elevation information for the evaluation point based on a result of the association. The information processing device according to claim 3 .

5. The control unit determines an up-down relationship between two or more intersecting roads based on the elevation information assigned to the plurality of evaluation points. The information processing device according to claim 4.

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