Information Processing Apparatus, Control Method, Program, and Storage Medium

Abstract

To provide an information processing device capable of suitably reducing the amount of data to be uploaded.SOLUTION: A controller 13 of an information processing device 1 obtains measurement data taken by an external sensor 3; and performs processing related to the detection of an object based on the measurement data. In addition, the controller 13 extracts object detection data that is data corresponding to the detected object from the measurement data; and transmits the extracted object detection data to a data collection device 5.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present disclosure relates to the processing of measured data.

Background Art

[0002] Conventionally, a lidar device that irradiates a pulse of laser light onto a detection space and detects an object in the detection space based on the level of the reflected light has been known. For example, Patent Document 1 discloses a lidar that scans a surrounding space by appropriately controlling the emission direction (scanning direction) of repeatedly emitted light pulses and observes the return light to generate point cloud data representing information such as the distance and reflectivity, which are information regarding objects existing in the surroundings. Further, Patent Document 2 discloses a technique for recognizing an object based on the point cloud data output by a lidar.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] When measurement data generated by a measurement device such as a lidar according to a predetermined measurement cycle is uploaded and collected and managed by a server device, since the capacity of the generated measurement data is large, if all the measurement data is to be the transmission target, the communication load, the processing load of the server device, etc. will become excessive.

[0005] The present disclosure has been made to solve the above-described problems, and a main object thereof is to provide an information processing device capable of suitably reducing the data amount of measured data.

Means for Solving the Problems

[0006] The invention according to the claims is mounted on a vehicle acquisition means for acquiring measurement data by a measuring device, based on the measurement data and of a predetermined type other than roads object to object detection means for detecting, extraction means for extracting object detection data, which is data corresponding to the detected object, from the measurement data, determination means for determining whether the detection result and the prior information match based on a comparison result between the detection result of the object by the object detection means and the prior information regarding the object, transmission means for transmitting the object detection data to a data collection device when the detection result and the prior information do not match, and is an information processing apparatus having the above.

[0007] Also, the invention according to the claims is a control method executed by a computer, mounted on a vehicle acquiring measurement data by a measuring device, based on the measurement data and of a predetermined type other than roads object to detecting perform , extracting object detection data, which is data corresponding to the detected object, from the measurement data, determining whether the detection result and the prior information match based on a comparison result between the detection result of the object and the prior information regarding the object, and transmitting the object detection data to a data collection device when the detection result and the prior information do not match, which is a control method.

[0008] Also, the invention according to the claims is mounted on a vehicle acquiring measurement data by a measuring device, based on the measurement data and of a predetermined type other than roads object to detecting perform , Extract object detection data, which is data corresponding to the detected object, from the measurement data. Based on the comparison result between the detection result of the object and the prior information regarding the object, determine whether the detection result matches the prior information. When the detection result does not match the prior information, it is a program that causes a computer to execute a process of transmitting the object detection data to a data collection device.

Brief Description of the Drawings

[0009]

Figure 1

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Modes for Carrying Out the Invention

[0010] According to a preferred embodiment of the present invention, an information processing device includes an acquisition unit that acquires measurement data from a measurement device, an object detection unit that performs processing related to the detection of an object based on the measurement data, an extraction unit that extracts object detection data, which is data corresponding to the detected object, from the measurement data, and a transmission unit that transmits the object detection data to a data collection device. In this manner, the information processing device can limit the data transmitted to the data collection device to data corresponding to the detected object, and can suitably reduce the amount of transmitted data.

[0011] In one aspect of the above information processing apparatus, the measurement device includes a first measurement device and a second measurement device, the acquisition means acquires first measurement data by the first measurement device and second measurement data by the second measurement device, the object detection means respectively executes detection of the object based on the first measurement data and detection of the object based on the second measurement data, and when the detection result of the object based on the first measurement data and the detection result of the object based on the second measurement data conflict, the transmission means transmits the object detection data to the data collection device. According to this aspect, the information processing apparatus can limit the data transmitted to the data collection device to the data in which a conflict occurs in the detection result of the object, and can suitably reduce the amount of transmitted data.

[0012] In another aspect of the above information processing apparatus, the first measurement device and the second measurement device have a common measurement range, and the information processing apparatus further has a conflict determination means for determining whether there is a conflict between the detection result of the object based on the first measurement data in the measurement range and the detection result of the object based on the second measurement data in the measurement range. According to this aspect, the information processing apparatus can suitably determine whether there is a conflict in the detection result of the object when using a plurality of measurement sensors.

[0013] In another aspect of the above information processing apparatus, the information processing apparatus further has a false detection determination means for determining whether there is a false detection of the object by the object detection means based on the comparison result between the detection result of the object by the object detection means and the prior information regarding the object, and the extraction means extracts the data when it is determined that there is such a false detection. According to this aspect, the information processing apparatus can limit the data transmitted to the data collection device to the data in which a false detection of the object occurs, and can suitably reduce the amount of transmitted data.

[0014] In another aspect of the above information processing apparatus, the prior information is map information including information regarding the object, information regarding the model of the object, or information regarding the constraint conditions of the object. By using such prior information, the information processing apparatus can suitably determine whether there is a false detection of the object.

[0015] In a preferred example of the information processing apparatus, the measurement device is mounted on a vehicle, and the object detection means performs processing related to detection of the object for an object other than a road. In another preferred example of the information processing apparatus, the object detection means performs processing related to detection of the object for an object specified from the data collection device.

[0016] According to another preferred embodiment of the present invention, there is provided a control method executed by a computer, the method including: acquiring measurement data by a measurement device; performing processing related to detection of an object based on the measurement data; extracting, from the measurement data, object detection data that is data corresponding to the detected object; and transmitting the object detection data to a data collection device. By executing this control method, the computer can limit the data transmitted to the data collection device to data corresponding to the detected object, and suitably reduce the amount of transmitted data.

[0017] According to another preferred embodiment of the present invention, a program causes a computer to execute processing of acquiring measurement data by a measurement device, performing processing related to detection of an object based on the measurement data, extracting, from the measurement data, object detection data that is data corresponding to the detected object, and transmitting the object detection data to a data collection device. By executing this program, the computer can limit the data transmitted to the data collection device to data corresponding to the detected object, and suitably reduce the amount of transmitted data. Preferably, the program is stored in a storage medium.

Example

[0018] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[0019] (1) Overview of the data collection system FIG. 1 shows a schematic configuration of a data collection system according to the first embodiment. The data collection system includes an information processing device 1 that processes data generated by a sensor group 2, and a data collection device 5 that is a server device for collecting and managing data.

[0020] The information processing device 1 is electrically connected to the sensor group 2, compresses (including data selection) the data output by the sensor group 2, and transmits the compressed data to the data collection device 5 as upload information "Iu". The information processing device 1 is, for example, a moving body such as a vehicle, a ship, a self-propelled robot, a drone, or a computer that controls the moving body. The information processing device 1 may be, for example, a navigation device mounted on a moving body such as a vehicle or a ship, or an electronic control device built into the moving body.

[0021] The sensor group 2 includes an external sensor 3 and an internal sensor 4. The external sensor 3 is one or more sensors that sense the external environment of the information processing device 1 or the moving body on which the information processing device 1 is mounted. The external sensor 3 is, for example, a ranging sensor such as a lidar, a camera, an ultrasonic sensor, or the like. The internal sensor 4 is one or more sensors that sense the internal environment of the information processing device 1 or the moving body on which the information processing device 1 is mounted. The internal sensor 4 is, for example, an angular velocity sensor, a GNSS (Global Navigation Satellite System) receiver, an acceleration sensor, an IMU (Inertial Measurement Unit), or other autonomous positioning devices. Thus, the sensor group 2 includes various sensors used for self-position estimation, obstacle detection, person detection, and the like. Note that at least some of the sensors in the sensor group 2 may be sensors built into the information processing device 1.

[0022] The data collection device 5 is a device that collects measurement data by a lidar, receives the upload information Iu from the information processing device 1, and stores the received upload information Iu. In FIG. 1, only one set of the information processing device 1 and the sensor group 2 is shown, but instead, a plurality of sets of the information processing device 1 and the sensor group 2 may exist. In this case, the data collection device 5 receives the upload information Iu from each information processing device 1. The data collection device 5 uses, for example, the upload information Iu received from the information processing device 1 as training data for an object recognition model based on machine learning such as deep learning. Note that the upload information Iu may include, in addition to the measurement data output by the external sensor 3, information on the self-position (i.e., the measurement position) at the time of measurement estimated by the information processing device 1 and information on the measurement time.

[0023] (2) Configuration of the information processing device FIG. 2 is a block diagram showing an example of the hardware configuration of the information processing device 1. The information processing device 1 mainly includes an interface 11, a memory 12, and a controller 13. These elements are interconnected via a bus line.

[0024] Interface 11 performs interface operations related to data transfer between the information processing device 1 and an external device. In this embodiment, interface 11 acquires output data from the sensor group 2 and supplies it to the controller 13. Further, interface 11 transmits the upload information Iu generated by the controller 13 to the data collection device 5 based on the control of the controller 13. Also, when the information processing device 1 is mounted on a moving body such as a vehicle, interface 11 may supply a signal related to the control of the moving body generated by the controller 13 to the electronic control unit (ECU) of the moving body. Interface 11 may be a wireless interface such as a network adapter for performing wireless communication, or a hardware interface for connecting to an external device via a cable or the like. Also, interface 11 may perform interface operations with various peripheral devices such as an input device, a display device, and a sound output device.

[0025] Memory 12 is composed of various volatile memories and non-volatile memories such as RAM (Random Access Memory), ROM (Read Only Memory), hard disk drive, and flash memory. Memory 12 stores a program for the controller 13 to execute a predetermined process. Note that the program executed by the controller 13 may be stored in a storage medium other than memory 12.

[0026] Also, various information related to the processes executed by the controller 13 is stored in memory 12. For example, memory 12 stores object recognition information I1.

[0027] The object recognition information I1 is information necessary for recognizing (detecting) an object based on the measurement data output by the external sensor 3. For example, the object recognition information I1 may be the parameters of an inference model that infers the presence or absence (and the type of the object) of an object included in the measurement data when the measurement data output by the external sensor 3 is input. Such an inference model may be any machine learning model such as a deep learning model used in recognition techniques such as semantic segmentation and instance segmentation when, for example, an image of a camera is used as input data. The data input to the above inference model is not limited to the image output by the camera, and may be the point cloud data for one measurement cycle output by the lidar, or the data output by other external sensors. Note that since the point cloud data for one measurement cycle of the lidar can be regarded as image data when the measurement direction is the pixel position and the data for each measurement direction is the pixel data, it is possible to perform learning of the inference model in the same manner as the image of the camera. Also, the inference model may be provided for each type of external sensor. In this case, the inference model is pre-learned using the data output by the target external sensor as training data (learning data), and the parameters of each inference model obtained by the learning are stored as the object recognition information I1.

[0028] The controller 13 includes one or more processors such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and a TPU (Tensor Processing Unit), and controls the entire information processing apparatus 1. In this case, the controller 13 executes various processes described later by executing a program stored in the memory 12 or the like.

[0029] Also, the controller 13 functionally has a self-position estimation unit 14, an object detection unit 15, and an upload unit 16.

[0030] The self-position estimation unit 14 performs self-position estimation based on the data generated by the sensor group 2, and generates position information indicating the position of the information processing apparatus 1 (including postures such as Yaw, Roll, and Pitch; the same applies hereinafter). In this case, the self-position estimation unit 14 may generate the position information by any self-position estimation method. For example, the self-position estimation unit 14 may generate the position information based on the output of a GNSS receiver or the like included in the sensor group 2. In another example, the self-position estimation unit 14 may generate the position information by executing a self-position estimation method using the measurement data of the external sensor 3 and the map data. As such self-position estimation methods, for example, there are a self-position estimation method based on the collation result between the measurement data of landmarks and the map data of landmarks, a self-position estimation method based on NDT (Normal Distribution Transform) matching using voxel data, and the like. And, its own

[0031] The object detection unit 15 detects an object existing within the measurement range of the external sensor 3 based on the measurement data output by the external sensor 3 and the object recognition information I1. In this case, the object to be detected (also referred to as the "object to be detected") is an object of a predetermined type. For example, when the external sensor 3 is mounted on a vehicle, it is an object other than the road (which may be limited to stationary objects). Note that the object detection unit 15 may receive information specifying the object to be detected from the data collection device 5, and determine the object to be detected based on the information. Then, when the object detection unit 15 detects the object to be detected, it extracts the measurement data corresponding to the object to be detected (also referred to as "object detection data") from the measurement data used for object detection, and supplies the extracted object detection data to the upload unit 16. The object detection data is, for example, data representing the measured position of the object to be detected when the object to be detected is detected using point cloud data obtained from a lidar. Also, the object detection data is an image of the entire image including the object to be detected, or an image obtained by cutting out the smallest region (e.g., a bounding box) including the object to be detected when the object to be detected is detected using an image obtained from a camera or the like.

[0032] The upload unit 16 transmits upload information Iu including object detection data to the data collection device 5 via the interface 11. In this case, for example, the upload unit 16 may sequentially transmit the object detection data generated according to the measurement period to the data collection device 5, or may transmit the data to the data collection device 5 in batches at predetermined time intervals. Further, the upload unit 16 may preferably include, in the upload information Iu, information on the measurement position generated by the self-position estimation unit 14 and information indicating the type of the corresponding external sensor 3 together with the object detection data. Further, the upload unit 16 may compress the upload information Iu by any reversible compression or irreversible compression and transmit the compressed upload information Iu to the data collection device 5.

[0033] Then, the controller 13 functions as an "acquisition means", "object detection means", "conflict determination means", "false detection determination means", "extraction means", "transmission means", a computer that executes a program, and the like.

[0034] Note that the processing executed by the controller 13 is not limited to being realized by software by a program, and may be realized by any combination of hardware, firmware, and software. Further, the processing executed by the controller 13 may be realized using a user-programmable integrated circuit such as an FPGA (Field-Programmable Gate Array) or a microcomputer. In this case, the program executed by the controller 13 in this embodiment may be realized using this integrated circuit.

[0035] (3) Processing flow FIG. 3 is an example of a flowchart executed by the information processing apparatus 1 in the first embodiment. The information processing apparatus 1 repeatedly executes the processing of the flowchart in FIG. 3.

[0036] First, the object detection unit 15 of the information processing apparatus 1 acquires measurement data generated by the external sensor 3 via the interface 11 (step S11). In this case, when the external sensor 3 to be used performs scanning or the like, the object detection unit 15 acquires data obtained by measurement for one cycle.

[0037] Next, the object detection unit 15 detects an object based on the measurement data acquired in step S11 (step S12). In this case, for example, the object detection unit 15 inputs the measurement data to an inference device configured by referring to the object recognition information I1 to obtain a detection result of the object to be detected.

[0038] Then, the object detection unit 15 determines whether or not the object to be detected has been detected (step S13). If the object to be detected has been detected (step S13; Yes), the object detection data corresponding to the detected object is extracted from the measurement data acquired in step S11. Then, the upload unit 16 transmits upload information Iu including the object detection data to the data collection device 5 (step S14). The upload information Iu transmitted to the data collection device 5 is suitably used, for example, as training data for an object recognition model based on machine learning such as deep learning. Note that instead of sequentially transmitting the object detection data of the object to be detected detected in step S13, the upload unit 16 may transmit the object detection data of the object to be detected detected at a plurality of measurement timings collectively.

[0039] On the other hand, if the object detection unit 15 does not detect the object to be detected in step S13 (step S13; No), the measurement data acquired in step S11 is discarded (step S15).

[0040] As described above, the information processing apparatus 1 according to the first embodiment can efficiently transmit useful data for the data collection device 5 to the data collection device 5.

[0041] (4) Specific example FIG. 4 is a diagram showing the light beam of the pulsed laser emitted by the lidar which is the external sensor 3. In the example of FIG. 4, the lidar emits a pulsed laser with a predetermined angular resolution determined by the pulse period for a predetermined angular range (about 210° in this example) including the forward direction of the vehicle. Note that the lidar irradiates the road surface by emitting a pulsed laser for a predetermined angular range also in the vertical direction in addition to the horizontal direction, or by tilting the scanning surface with respect to the horizontal direction.

[0042] In this case, the pulsed laser emitted by the lidar is irradiated onto each object including the white lines 51a to 51c, the road sign 52, the utility pole 53, the building 54, and the vehicle 55 ahead, and the reflected light is received by the lidar. In this case, the information processing device 1 receives the point cloud data generated based on the received light signal of the reflected light from the lidar 30 (see step S11 in FIG. 3) and performs detection of the object to be detected (see step S12 in FIG. 3). Here, for example, it is assumed that the object to be detected is all objects other than the road (including the white lines). Then, the information processing device 1 detects the road sign 52, the utility pole 53, the building 54, and the vehicle 55 ahead as the objects to be detected (see step S13), and extracts the data determined to belong to the road sign 52, the utility pole 53, the building 54, and the vehicle 55 ahead, respectively, as the object detection data. Then, the information processing device 1 transmits the upload information Iu including the extracted object detection data to the data collection device 5 (see step S14). In this case, preferably, the information processing device 1 transmits the upload information Iu in which the object detection data for each detected object is associated with the information on the type of the detected object to the data collection device 5.

[0043] (5) Modification example The information processing apparatus 1 may determine the contradiction of the object detection results for each external sensor 3 based on the measurement data output by the plurality of external sensors 3, and transmit the object detection data related to the measurement data with contradiction to the data collection apparatus 5. In addition to, or instead of, this, the information processing apparatus 1 may determine whether there is a false detection of an object by comparing the object detection result with the prior information regarding the object, and transmit the object detection data related to the measurement data with false detection to the data collection apparatus 5. According to these aspects, the information processing apparatus 1 can suitably supply important data as an analysis target for improving the accuracy of the object detection process to the data collection apparatus 5.

[0044] FIG. 5 is an overhead view of a road on which a vehicle equipped with the external sensors 3A and 3B travels. In FIG. 5, the measurement range “FOV1” of the external sensor 3A, the measurement range “FOV2” of the external sensor 3B, and the common measurement range “FOV12” (overlapping) common to the external sensors 3A and 3B are respectively shown. There is a preceding vehicle 56 in the common measurement range FOV12. The external sensors 3A and 3B may be a combination of different types of external sensors (for example, a lidar and a camera), or may be the same type of external sensors (for example, both lidars). Here, the object to be detected includes a vehicle.

[0045] In this case, the information processing device 1 detects a detection target object based on the measurement data of the external sensors 3A and 3B belonging to the common measurement range FOV12. Then, the information processing device 1 determines whether there is a contradiction between the detection result of the detection target object based on the measurement data within the common measurement range FOV12 of the external sensor 3A (also referred to as "first measurement data") and the detection result of the detection target object based on the data within the common measurement range FOV12 of the external sensor 3B (also referred to as "second measurement data"). And when these detection results are different, the information processing device 1 transmits upload information Iu including object detection data respectively extracted from the first measurement data and the second measurement data to the data collection device 5. In this case, for example, when the type and number of the detection target objects detected based on the first measurement data do not match the type and number of the detection target objects detected based on the second measurement data, the information processing device 1 determines that the detection results are contradictory. For example, when the information processing device 1 detects the preceding vehicle 56 based on the first measurement data but cannot detect the preceding vehicle 56 based on the second measurement data, it determines that these detection results are contradictory and transmits the upload information Iu based on the first measurement data and the second measurement data used for the detection to the data collection device 5. In this case, the information processing device 1 extracts, from the first measurement data and the second measurement data respectively, object detection data corresponding to the detected detection target objects (or all data if the detection target object cannot be detected), and transmits the upload information Iu including the extracted data to the data collection device 5.

[0046] FIG. 6 is a view observing the road on which the vehicle equipped with the external sensor 3 travels from the side. In the example of FIG. 6, the information processing device 1 detects the guide object 57, the traffic signal 58, and the preceding vehicle 59 as detection target objects based on the measurement data output by the external sensor 3. In this case, the information processing device 1 determines whether there is an error in the detection result based on the prior information regarding the detection target object pre-stored in the memory 12. The prior information may be model information modeling the detection target object, may be a constraint condition regarding the detection target object, or may be map information including information (position information, type information, appearance information, etc.) regarding the detection target object.

[0047] For example, when the information processing device 1 includes, as pre-information, a vehicle constraint condition that the vehicle is in contact with a road, it determines whether or not the position of the preceding vehicle 59 detected based on the measurement data of the external sensor 3 is in contact with the road. In this case, for example, the information processing device 1 identifies the road data and the data of the preceding vehicle 59 from the measurement data of the external sensor 3, and determines whether or not the distance between the identified data (for example, the distance between the respective center-of-gravity positions in the height direction) is within a predetermined distance. Then, when the distance between the above-mentioned data is longer than the predetermined distance, the external sensor 3 determines that it violates the above-mentioned constraint condition and determines that a false detection has occurred. Therefore, in this case, the external sensor 3 transmits the upload information Iu including the object detection data corresponding to the preceding vehicle 59 to the data collection device 5. The constraint condition is not limited to the condition that the vehicle is in contact with the road surface, and may be various conditions such as the size of the vehicle. Note that appropriate constraint conditions are registered in the pre-information for each type of detection target object.

[0048] In another example, when the information processing apparatus 1 stores map information including information about the guide object 57 and the traffic signal 58 in the memory 12, it determines whether the positions, sizes, etc. of the guide object 57 and the traffic signal 58 detected based on the measurement data of the external sensor 3 match the positions, sizes, etc. of the guide object 57 and the traffic signal 58 recorded in the map information. In this case, the information processing apparatus 1 may perform the above-described estimation by applying any object recognition technology for estimating the position, size, etc. of an object based on the output of a camera, a lidar, or the like. For example, the information processing apparatus 1 estimates the position of each of the guide object 57 and the traffic signal 58 on the map based on the position on the map based on the self-position estimation result and the relative position with respect to the information processing apparatus 1 indicated by the measurement data of the external sensor 3. Further, the information processing apparatus 1 estimates the size, etc. of each of the guide object 57 and the traffic signal 58 based on the measurement data corresponding to each of the guide object 57 and the traffic signal 58. Then, when the detection results of the guide object 57 and the traffic signal 58 based on the measurement data do not match the prior information of the guide object 57 and the traffic signal 58 included in the map information previously stored in the memory 12, the information processing apparatus 1 determines that a false detection has occurred. Therefore, in this case, the information processing apparatus 1 transmits upload information Iu including object detection data corresponding to the guide object 57 and the traffic signal 58 to the data collection apparatus 5.

[0049] In yet another example, when model information of a detection target object is stored in the memory 12 or the like as prior information, the information processing apparatus 1 performs three-dimensional matching (collation) processing between the three-dimensional shape of the detection target object indicated by the model information and the three-dimensional shape based on the detection result. Then, when the degree of matching by the three-dimensional matching is less than a predetermined threshold value, the information processing apparatus 1 determines that a false detection has occurred, and transmits upload information Iu including corresponding object detection data to the data collection apparatus 5.

[0050] FIG. 7 is an example of a flowchart showing the processing procedure of the information processing apparatus 1 in the modified example. The information processing apparatus 1 repeatedly executes the processing of the flowchart shown in FIG. 7.

[0051] First, the object detection unit 15 of the information processing apparatus 1 acquires measurement data generated by the external sensor 3 via the interface 11 (step S21). Next, the object detection unit 15 detects an object based on the measurement data acquired in step S21 (step S22). Then, the object detection unit 15 determines whether or not the detection target object has been detected (step S23).

[0052] And, when the detection target object has been detected (step S23; Yes), it is determined whether or not there is a contradiction or false detection in the detection result (step S24). In this case, when there is a common measurement range among the plurality of external sensors 3, the object detection unit 15 determines whether or not there is a contradiction in the detection results based on the measurement data of each external sensor 3. Further, when prior information regarding the detection target object is stored in the memory 12 or the like, the object detection unit 15 compares the detection result with the prior information to determine whether or not there is a false detection.

[0053] And, when there is a contradiction or false detection in the detection result (step S24; Yes), the upload unit 16 transmits upload information Iu including the measurement data regarding the contradiction or false detection to the data collection apparatus 5 (step S25). On the other hand, when there is no contradiction or false detection in the detection result (step S24; No), the upload unit 16 discards the target measurement data (step S26).

[0054] As described above, the information processing apparatus 1 according to the modification example can efficiently supply the data collection apparatus 5 with the upload information Iu that limitedly includes important data as an analysis target for improving the accuracy of the object detection process, and can suitably reduce the amount of data to be transmitted.

[0055] As described above, the controller 13 of the information processing apparatus 1 according to the embodiment acquires measurement data from the external sensor 3 and performs processing related to detection of an object based on the measurement data. Then, the controller 13 extracts object detection data, which is data corresponding to the detected object, from the measurement data, and transmits the extracted object detection data to the data collection apparatus 5. Thereby, the information processing apparatus 1 can efficiently transmit useful data for the data collection apparatus 5 to the data collection apparatus 5.

[0056] Note that, in the above-described embodiment, the program can be stored using various types of non-transitory computer readable media and supplied to a controller or the like that is a computer. The non-transitory computer readable media include various types of tangible storage media. Examples of the non-transitory computer readable media include magnetic storage media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical storage media (e.g., magneto-optical disks), CD-ROM (Read Only Memory), CD-R, CD-R / W, and semiconductor memories (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)).

[0057] Although the invention of the present application has been described with reference to the embodiments above, the invention of the present application is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the invention of the present application within the scope of the invention of the present application. That is, the invention of the present application naturally includes various modifications and corrections that those skilled in the art could make in accordance with the entire disclosure including the claims and the technical idea. In addition, each disclosure of the above-cited patent documents and the like is incorporated herein by reference.

Description of Reference Numerals

[0058] 1 Information processing apparatus 2 Sensor group 3 External sensor 4 Internal sensor 5 Data collection device

Claims

An acquisition means for acquiring measurement data by a measurement device mounted on a vehicle; An object detection means for detecting a predetermined type of object other than a road based on the measurement data; An extraction means for extracting object detection data, which is data corresponding to the detected object, from the measurement data; A determination means for determining whether or not the detection result and the prior information match based on a comparison result between the detection result of the object by the object detection means and the prior information regarding the object; A transmission means for transmitting the object detection data to a data collection device when the detection result and the prior information do not match; An information processing apparatus having the above.

2. The measurement device includes a first measurement device and a second measurement device, The acquisition means acquires first measurement data by the first measurement device and second measurement data by the second measurement device, The object detection means respectively performs detection of the object based on the first measurement data and detection of the object based on the second measurement data, The transmission means transmits the object detection data to the data collection device when the detection result of the object based on the first measurement data and the detection result of the object based on the second measurement data are contradictory. The information processing apparatus according to claim 1.

3. The first measurement device and the second measurement device have a common measurement range, The information processing apparatus according to claim 2, further comprising a contradiction determination means for determining the presence or absence of a contradiction between the detection result of the object based on the first measurement data in the measurement range and the detection result of the object based on the second measurement data in the measurement range.

4. The determination means determines the presence or absence of false detection of the object by the object detection means based on the comparison result, The transmission means transmits the object detection data to the data collection device when it is determined that there is false detection. The information processing apparatus according to any one of claims 1 to 3.

5. The prior information is map information indicating at least the position and size of each of the predetermined types of objects, information regarding the model of the object, or information regarding the constraint conditions of the object. The information processing apparatus according to any one of claims 1 to 4.

6. The object detection means detects the object designated from the data collection device. The information processing apparatus according to any one of claims 1 to 5.

7. A control method executed by a computer, Obtain measurement data by a measuring device mounted on a vehicle, Based on the measurement data, detect predetermined types of objects other than roads, Extract object detection data, which is data corresponding to the detected object, from the measurement data, Based on the comparison result between the detection result of the object and the prior information regarding the object, determine whether the detection result and the prior information match, When the detection result and the prior information do not match, transmit the object detection data to a data collection device, Control method.

8. Obtain measurement data by a measuring device mounted on a vehicle, Based on the measurement data, detect predetermined types of objects other than roads, Extract object detection data, which is data corresponding to the detected object, from the measurement data, Based on the comparison result between the detection result of the object and the prior information regarding the object, determine whether the detection result and the prior information match, A program that causes a computer to execute a process of transmitting the object detection data to a data collection device when the detection result and the prior information do not match.

9. A storage medium storing the program according to Claim 8.

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