Vehicle control device and on-vehicle program

Abstract

A vehicle control device (10) comprises: a characteristic setting unit (15) that acquires at least one of information relating to a vehicle itself, information relating to an owner of the vehicle, information relating to conditions under which the vehicle is traveling, and information relating to a region in which the vehicle is traveling, and sets characteristic information of the vehicle during traveling, on the basis of the information; a data acquisition unit (14) that acquires data relating to sensor information acquired by various sensors mounted in the vehicle, when a data acquisition condition is satisfied; and a transmission unit (17) that transmits the data acquired by the data acquisition unit to a server via a communication network. At least one of the acquisition condition and the data acquired by the data acquisition unit is changed in accordance with the characteristic information.

Description

Vehicle control device and in-vehicle program CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is based on Japanese Application No. 2024-069040 filed on April 22, 2024, the contents of which are incorporated herein by reference.

[0002] The present disclosure relates to a vehicle control device and an in-vehicle program.

[0003] In recent years, a method has been adopted in which various data actually acquired from vehicles after they have been sold while they are being driven is collected on a server via a communication network, and the data collected on the server is analyzed and used in future vehicle development or to update the vehicle's control program.

[0004] One example of such a verification method is known as shadow mode, in which a program to be verified is run while a vehicle is being driven after sales to verify program performance and safety, and output values ​​are confirmed. In shadow mode verification, for example, the program to be verified is run in the background, i.e., without being involved in vehicle control, and data related to the output values ​​is stored. The data related to the output values ​​is then collected by a server via a communication network or the like. The collected data is then analyzed to verify the operation of the program to be verified. Technology related to such shadow mode is described, for example, in Patent Document 1.

[0005] International Publication No. 2022 / 004324

[0006] However, when collecting data, if one tries to collect data on all driving conditions for all vehicles in all scenes, the amount of data becomes enormous. Furthermore, if one tries to verify all programs, the amount of data increases even further. The large amount of data leads to problems such as increased communication load, processing load, and analysis load. Furthermore, the data includes data that is unnecessary for verification, resulting in poor efficiency.

[0007] The present disclosure has been made in consideration of the above circumstances, and has as its main object to provide a vehicle control device and an in-vehicle program that can efficiently collect necessary data.

[0008] A first vehicle control device for solving the above problem is a vehicle control device mounted on a vehicle, and includes: a characteristic setting unit that acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on that information; a data acquisition unit that acquires data about sensor information acquired by various sensors mounted on the vehicle when a data acquisition condition is met; and a transmission unit that transmits the data acquired by the data acquisition unit to a server via a communication network, and at least one of the acquisition conditions and the data acquired by the data acquisition unit is changed depending on the characteristic information.

[0009] The second vehicle control device for solving the above problem is a vehicle control device that is mounted on a vehicle and is configured to be able to implement a shadow mode in which a program to be verified operates in a manner that is not related to the control of the vehicle, and is equipped with: a characteristic setting unit that acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information of the vehicle while traveling based on that information; a modification unit that modifies part or all of the program to be verified in accordance with the characteristic information; a data acquisition unit that uses sensor information acquired by various sensors mounted on the vehicle as input values, and when a data acquisition condition is met when the program to be verified is executed or has been executed, acquires data regarding the output result together with data regarding the sensor information, or acquires data regarding the output result instead of data regarding the sensor information; and a transmission unit that transmits the data acquired by the data acquisition unit to a server via a communication network.

[0010] The first in-vehicle program for solving the above problem is an in-vehicle program executed by a vehicle control device mounted on a vehicle, which causes the vehicle control device to acquire at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on that information; a data acquisition step, when a data acquisition condition is met, causes the vehicle control device to acquire data about sensor information acquired by various sensors mounted on the vehicle; and a transmission step, causes the data acquired in the data acquisition step to be transmitted to a server via a communication network, and at least one of the acquisition conditions and the data acquired in the data acquisition step is changed according to the characteristic information.

[0011] The second in-vehicle program for solving the above problem is an in-vehicle program executed by a vehicle control device that is mounted on a vehicle and is configured to be able to implement a shadow mode in which the program to be verified operates without being involved in the control of the vehicle, and includes the following steps: a characteristic setting step in which the vehicle control device acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on that information; a modification step in which the vehicle control device modifies part or all of the program to be verified in accordance with the characteristic information; a data acquisition step in which, using sensor information acquired by various sensors mounted on the vehicle as input values, if a data acquisition condition is met when the program to be verified is executed or has been executed, acquires data about the output result together with data about the sensor information, or acquires data about the output result instead of data about the sensor information; and a transmission step in which the data acquired in the data acquisition step is transmitted to a server via a communication network.

[0012] The above and other objects, features, and advantages of the present disclosure will become more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which Fig. 1 is a schematic configuration diagram of a data collection system, Fig. 2 is a block diagram showing functions performed by a verification processing device, Fig. 3 is a diagram for explaining basic information, Fig. 4 is a diagram for explaining characteristic information, Fig. 5 is a diagram for explaining a method for changing acquisition conditions, Fig. 6 is a diagram for explaining a method for changing acquisition conditions, Fig. 7 is a diagram for explaining a method for changing acquisition conditions, Fig. 8 is a flowchart of data acquisition processing, Fig. 9 is a flowchart of data acquisition processing in a second embodiment, Fig. 10 is a flowchart of data acquisition processing in a third embodiment, Fig. 11 is a block diagram showing functions performed by a processing device in a fourth embodiment, Fig. 12 is a flowchart of data acquisition processing in the fourth embodiment, and Fig. 13 is a flowchart of data acquisition processing in a modified example.

[0013] Hereinafter, embodiments of a vehicle control device and an on-board program according to the present disclosure will be described in detail with reference to the drawings. Note that, between the embodiments and modifications, the same or corresponding parts in the drawings are designated by the same reference numerals, and their description will not be repeated in principle.

[0014] 1 shows a data collection system 100 to which a vehicle control device 10 according to this embodiment is applied. The vehicle control device 10 is mounted on a vehicle 101, and controls the vehicle 101 and performs driving assistance.

[0015] As shown in Fig. 1, a data collection system 100 includes a server 102 and is capable of communicating with one or more vehicles 101 via a communication network 103 such as the Internet. Fig. 1 shows only one vehicle 101. The vehicle 101 includes a vehicle control device 10, a sensor 20, an actuator 30, and the like.

[0016] The sensor 20 includes various sensors for measuring the traveling conditions of the vehicle 101, such as a vehicle speed sensor 21, an acceleration sensor 22, and a yaw rate sensor 23. The sensors for measuring the traveling conditions of the vehicle 101 may include other sensors, or any of the vehicle speed sensor 21, the acceleration sensor 22, and the yaw rate sensor 23 may not be included.

[0017] The sensor 20 also includes various sensors for detecting other vehicles and obstacles, such as a camera 24 and a millimeter-wave radar 25. The sensor for detecting other vehicles and obstacles is not limited to the millimeter-wave radar 25, but may also be a laser radar (LiDAR), an ultrasonic sensor, or a combination of these. The camera 24 may also be a monocular camera or a compound camera. The camera 24 may also capture either still images or videos. The number, position, and type of the cameras 24 may be changed as desired. For example, the vehicle may include a front camera that captures the area in front of the vehicle, a right-side camera that captures the area on the right side of the vehicle, a left-side camera that captures the area on the left side of the vehicle, and a rear camera that captures the area behind the vehicle.

[0018] The sensor 20 also includes various sensors for detecting various amounts of operation by the driver, such as an accelerator sensor 26 that detects the amount of accelerator operation by the driver, a brake sensor 27 that detects the amount of brake operation, and a steering angle sensor 28 that detects the amount of steering (steering angle) of the steering wheel by the driver.

[0019] These sensors 20 are connected to the vehicle control device 10 wirelessly or by wire, and the measurement results (or detection results) of these sensors 20 are input to the vehicle control device 10 or the like as sensor information.

[0020] The actuators 30 include, for example, actuators for driving the vehicle 101, such as a motor that serves as the main engine of the vehicle 101. The actuators 30 may also include actuators for controlling the behavior of the vehicle 101, such as an actuator for operating a steering wheel, an actuator for operating a brake pedal, or an actuator for operating an accelerator pedal. The actuators 30 may also include devices for operating accessories of the vehicle 101, such as a display, a speaker, an indicator, and a headlight. The driving and operation of the vehicle 101 are controlled by the actuators 30.

[0021] The vehicle control device 10 is primarily composed of a microcomputer including a processing unit 10a such as a CPU and a storage unit 10b such as various types of memory. The functions provided by the microcomputer can be provided by software recorded in a physical memory device and a computer executing the software, software alone, hardware alone, or a combination thereof. For example, when the microcomputer is provided by electronic circuits, which are hardware, the functions can be provided by digital circuits including numerous logic circuits or analog circuits. For example, the processing unit 10a of the microcomputer executes programs stored in a non-transitory tangible storage medium (non-transitory tangible storage medium) that serves as the storage unit 10b. The programs include, for example, programs that realize functions shown in FIG. 2 . Execution of the programs results in the execution of methods corresponding to the programs. The storage unit 10b is, for example, a non-volatile memory. The programs stored in the storage unit 10b can be downloaded and updated via a communication network 103, such as the Internet, via over-the-air (OTA) or other means.

[0022] The vehicle control device 10 has various functions (application programs) for assisting the driving of the vehicle 101, and these functions control the actuator 30 based on sensor information input from the sensor 20.

[0023] Typical functions for assisting the driving of the vehicle 101 include, for example, an adaptive cruise control system (ACC), a forward collision warning (FCW), an advanced emergency braking system (AEBS), a night vision / pedestrian detection (NV / PD), a traffic sign recognition (TSR), a lane departure warning (LDW), a lane keeping assist system (LKAS), a rear cross traffic alert (RCTA), an adaptive front lighting system (AFS), and an advanced parking assist (APA). The vehicle 101 may be provided with all or some of these functions. Furthermore, the vehicle 101 may also be provided with other driving assistance functions. Furthermore, the vehicle 101 may also be provided with a function for realizing autonomous driving of the vehicle 101. These functions are realized by the arithmetic processing unit 10a executing a driving assistance control program stored in the storage unit 10b.

[0024] Furthermore, in order to verify the performance and safety of the driving assistance control program, the vehicle control device 10 has a function called a shadow mode in which a driving assistance control program to be verified (hereinafter referred to as a verification target program) is run while the vehicle is running after sales, that is, in an actual use case, and output values ​​are checked. In verification using the shadow mode, for example, the verification target program is run in the background, that is, in a manner not related to vehicle control, and data related to the output values ​​is stored, and the server 102 collects the data related to the output values ​​via the communication network 103. Note that the shadow mode is a type of data collection mode for collecting data.

[0025] The configuration and functions of the shadow mode according to this embodiment will be described below. The timing of switching to the shadow mode may be any timing. For example, the switching may be performed by an operation by the driver or by an instruction from the server 102. Alternatively, the switching to the shadow mode may be performed when the ignition switch is turned on.

[0026] In the following, the driving assistance control program that actually operates the vehicle 101 will be referred to as an "implemented program" to contrast it with the program to be verified. It will also be referred to as an "implemented program" in FIG. 1 . The vehicle control device 10 is equipped with a verification processing device 11 for executing the program to be verified, taking into account the processing load when executing the implemented program. The verification processing device 11 may have performance equivalent to or different from that of the processing device 10a, as long as it has the performance to execute the program to be verified. The program to be verified is stored in the storage unit 10b. A storage device dedicated to the shadow mode may also be provided.

[0027] Execution of the program to be verified executes various functions in the background to assist the driving of the vehicle 101. The functions implemented by execution of the program to be verified may be the same as the functions actually realized by the arithmetic processing device 10a, or some of the functions may be omitted. Furthermore, functions other than the functions actually realized by the arithmetic processing device 10a may also be implemented.

[0028] When the verification target program is running in shadow mode, the verification processing unit 11, like the processing unit 10a, receives sensor information from the various sensors 20. Based on the received sensor information, the verification processing unit 11 then performs various functions and outputs various control signals for operating the actuators. These control signals (output results) are not actually input to the actuators 30, but are stored in the storage unit 10b as data related to the output results. At this time, the verification processing unit 11 also stores data related to the sensor information, which is an input value, in association with the data.

[0029] The verification processing unit 11 also receives the control signal output from the processing unit 10a after inputting sensor information as an input value and processing it based on the implementation program, and stores the control signal in the storage unit 10b as data related to the output result. That is, the verification processing unit 11 also stores the control signal output from the processing unit 10a after processing it based on the implementation program in order to compare and verify the output result of the implementation program with the output result of the program to be verified.

[0030] Furthermore, the verification processing device 11 may input sensor information (vehicle speed, yaw rate, acceleration amount, accelerator pedal operation amount, brake pedal operation amount, steering angle, etc.) detected when a control signal processed and output based on the implementation program is input to the actuator 30 and the vehicle 101 moves as a result, and store the information in the storage unit 10b. In other words, the sensor information related to the actual operation of the vehicle 101 for each scene, that is, the sensor information necessary to verify the correct operation, may also be stored.

[0031] The vehicle control device 10 uploads the data thus stored in the storage unit 10b to the server 102 via the communication network 103 at a predetermined transmission timing. The predetermined transmission timing may be any timing, for example, a timing when an upload instruction is issued from the server 102. Alternatively, the predetermined transmission timing may be, for example, a timing when the vehicle 101 is charging, when the vehicle is parked or stopped, or when the ignition switch is turned off.

[0032] However, there is a problem in that the storage capacity of the storage unit 10b is likely to be insufficient to store all data while the vehicle 101 is traveling. Also, if all the vehicles 101 upload all of the data they have stored, there is a risk that an excessive load will be placed on the communication network 103. Furthermore, there is also a problem in that the processing load on the server 102 will be too large if all of the uploaded data is analyzed by the server 102. There is also a problem in that there is a lot of waste in acquiring and analyzing all of the data in the first place.

[0033] For this reason, it is desirable to configure the system so that only the amount of data necessary for verification and analysis is stored, transmitted, and received, and it is also desirable that metadata (tag information) is set in the data so that it is easy for the server 102 to analyze. Therefore, the vehicle control device 10 of this embodiment is configured to be able to identify the state of the vehicle 101 in which the data was acquired, and to store, transmit, and receive only data acquired by the vehicle 101 in a specified state. This will be described in detail below.

[0034] 2, the verification processing device 11 of the vehicle control device 10 has a function as an input unit 12, a function as a processing unit 13, a function as a data acquisition unit 14, a function as a characteristic setting unit 15, a function as a change unit 16, and a function as a transmission unit 17. These functions are realized by the verification processing device 11 by executing an in-vehicle program stored in the storage unit 10b.

[0035] The input unit 12 inputs sensor information from the sensor 20. Then, the input unit 12 inputs part or all of the input sensor information to the processing unit 13 as input values ​​for the program to be verified. The input unit 12 also inputs part or all of the input sensor information to the data acquisition unit 14.

[0036] The processing unit 13 runs the program to be verified and performs processing based on various functions (application programs) realized by the program to be verified, based on input values ​​(sensor information) input from the input unit 12. The processing unit 13 then inputs control signals (control signals for the actuator 30) as the processing results to the data acquisition unit 14. Note that, as described above, these control signals are not input to the actuator 30.

[0037] The data acquisition unit 14 determines whether the acquisition condition (also called the trigger condition) is met based on at least one of the input value (sensor information) input from the input unit 12 and the output result (control signal) input from the processing unit 13.

[0038] The acquisition conditions may include, for example, thresholds for one or more parameters as components. The parameters of the acquisition conditions may be, for example, parameters included in sensor information such as vehicle speed, yaw rate, accelerator operation amount, brake operation amount, and steering amount, or parameters included in output results such as required torque and an output instruction signal to a display. The acquisition conditions may also include parameters calculated or estimated from sensor information or output results. For example, the acquisition condition parameters may include the relative distance to an obstacle (such as a preceding vehicle or pedestrian), the relative speed to the obstacle, and the time-to-collision (TTC) calculated from the recognition results of a camera image or the detection results of the millimeter-wave radar 25. The acquisition condition parameters may also include the difference between the output results based on the implemented program and the output results of the program to be verified. For example, the parameter may be the difference between the brake operation amount output by processing based on the implemented program and the brake operation amount output by processing based on the program to be verified. The threshold may be either the upper limit or lower limit of any of these parameters, or both.

[0039] Furthermore, a component of the acquisition condition may be whether or not the scene in which the vehicle 101 is traveling (hereinafter simply referred to as the scene) is a predetermined acquisition scene. The scene refers to various scenes that are expected when the vehicle 101 is traveling, such as a scene in which the vehicle overtakes a preceding vehicle, a scene in which the vehicle passes between vehicles, a scene in which the vehicle follows a preceding vehicle, a scene in which a pedestrian crosses in front of the vehicle 101 at night, a scene in which the vehicle 101 merges from an acceleration lane onto a main lane on a motorway, a scene in which the vehicle is parking or stopping, a scene in which the vehicle is waiting at a traffic light, and the like.

[0040] These scenes are estimated based on sensor information. For example, the vehicle control device 10 may recognize camera images or the like and estimate the scenes. More specifically, the sensor information such as camera images may be input to a machine-learned inference model such as a deep neural network to estimate the scenes. Note that image recognition does not have to be performed by the vehicle control device 10, and may be performed by an external device of the vehicle control device 10, such as an image recognition device, and the results may be input as sensor information.

[0041] Furthermore, among various functions (application programs) based on the program to be verified, an executed function (executed function) may be a component of the acquisition condition. For example, the acquisition condition may be satisfied when a collision damage mitigation braking control function is executed. Note that which function has been executed can be determined based on the output result (control signal) input from the processing unit 13.

[0042] In this embodiment, the acquisition condition is set by combining the acquisition scene, the execution function, and the parameter threshold (i.e., an AND condition). For example, the acquisition condition may be satisfied when the scene is following a preceding vehicle and the vehicle speed (a parameter of the acquisition condition) is equal to or greater than a threshold (50 km / h).

[0043] The combination of components of the acquisition condition may be an acquisition scene and an implementation function, an acquisition scene and a parameter threshold, or an implementation function and a parameter threshold. Furthermore, the components included in one acquisition condition may include two or more implementation functions, and in this case, the implementation functions may be an AND condition or an OR condition. For example, the condition may be that both the forward vehicle approach warning function and the collision damage mitigation braking control function are implemented, or that either one of them is implemented. Similarly, the parameter threshold may be a threshold for two or more types of parameters.

[0044] Furthermore, the acquisition condition is established when all of the conditions of the components that make up the acquisition condition are satisfied. For example, if the acquisition scene of the acquisition condition is "a scene of following a preceding vehicle," the implementation function of the acquisition condition is "a following driving function," and the threshold value of the parameter of the acquisition condition is "50 km / h or more," the acquisition condition is established when the following driving function is implemented in a scene of following a preceding vehicle and the vehicle speed (a parameter of the acquisition condition) is equal to or greater than the threshold value (50 km / h).

[0045] The number of acquisition conditions is not limited to one, and multiple acquisition conditions may be set. For example, a first acquisition condition may be a scene in which the vehicle is following a preceding vehicle and the vehicle speed is equal to or greater than a first threshold, and a second acquisition condition may be a scene in which a pedestrian is crossing in front of the vehicle 101, the distance to the pedestrian is equal to or less than a second threshold, and the amount of brake operation is equal to or greater than a third threshold.

[0046] When any of the acquisition conditions is satisfied, the data acquisition unit 14 stores data related to input values ​​and output results in the storage unit 10b. As described above, the input values ​​include, for example, sensor information input to the verification processing device 11. Furthermore, the output results include, for example, control signals processed and output based on the program to be verified, or control signals processed and output based on the implemented program. Furthermore, the output results may include sensor information related to the actual operation of the vehicle 101 for each scene. Furthermore, the output results may include a difference between the output results based on the implemented program and the output results of the program to be verified. The stored (acquired) data may be changed depending on the acquisition condition that is satisfied. For example, when an acquisition condition is satisfied in a scene in which the vehicle is following a preceding vehicle and the vehicle speed is equal to or greater than a first threshold, data related to the vehicle speed may be acquired. On the other hand, when an acquisition condition is satisfied in a scene in which a pedestrian is crossing in front of the vehicle 101 and the distance to the pedestrian is equal to or less than a second threshold and the brake operation amount is equal to or greater than a third threshold, data related to the brake operation amount may be acquired.

[0047] Next, the characteristic setting unit 15 will be described. The characteristic setting unit 15 acquires at least one of information about the vehicle 101 itself, information about the owner (purchaser) of the vehicle 101, information about the driving conditions of the vehicle 101, and information about the area where the vehicle 101 is located, and sets characteristic information about the vehicle 101 while it is driving based on this information. Note that "while driving" does not necessarily mean when the vehicle is actually driving, but also includes when the vehicle is parked or stopped as long as the ignition switch is on (power is on). Furthermore, the information about the vehicle 101 itself, information about the owner (purchaser) of the vehicle 101, information about the driving conditions of the vehicle 101, and information about the area where the vehicle 101 is located may be collectively referred to as basic information.

[0048] The basic information will be described in more detail with reference to Figure 3. The information about the vehicle 101 itself includes, for example, information about the number, location, and type of sensors 20 mounted on the vehicle 101. The information about the vehicle 101 itself may also include the vehicle model, vehicle width, vehicle height, size, shape, model year, vehicle weight, etc. The information about the vehicle 101 itself may be pre-stored in the storage unit 10b, or may be input to the vehicle control device 10 by a dealer or the like via an input device (e.g., a touch panel display) and then stored in the storage unit 10b.

[0049] The information about the owner (purchaser) of the vehicle 101 includes, for example, the living area, family structure, gender, and age of the owner of the vehicle 101. Information about the vehicle 101 itself is input to the vehicle control device 10 by a dealer or the like through an input device, and is then stored in the memory unit 10b.

[0050] The information about the driving conditions of the vehicle 101 includes, for example, information about the weather, the time of day the vehicle is driving, and the road the vehicle is driving on. The road the vehicle is driving on refers to information about the road itself, such as whether it is a highway for motor vehicles only, whether it is a mountain road with many ups and downs and curves, or whether it is a road in an urban area. The information about the driving conditions of the vehicle 101 is identified in real time from camera images using image recognition that utilizes a deep neural network, and input to the vehicle control device 10. Note that the weather may be identified by a rain sensor and the information input, or the time of day the vehicle is driving on may be identified by a clock installed in the vehicle 101 and the information input. Furthermore, the information about the road the vehicle is driving on may be identified by a navigation system and the information input.

[0051] The information about the region where the vehicle 101 is located may be, for example, the name of the country where the vehicle 101 is located (Japan, etc.), the regional division where the vehicle 101 is located (Kanto region, etc.), or the name of the city where the vehicle 101 is located (Tokyo, etc.). It may also include, for example, a climate zone (temperate, heavy snow region, heavy rain region, dry region, etc.). The information about the region where the vehicle 101 is located may be input to the vehicle control device 10 by a dealer or the like through an input device and stored in the storage unit 10b, or may be identified and input in real time by a navigation system. In other words, the location information of the vehicle 101 may be detected by a GPS (Global Positioning System), and the name of the country where the vehicle 101 is located, the regional division where the vehicle 101 is located, etc. may be identified based on the location information and input to the vehicle control device 10.

[0052] The characteristic setting unit 15 extracts and abstracts the necessary information from this basic information, or performs either extraction and abstraction, to convert it into one or more characteristic parameters that indicate the characteristics of the vehicle 101 while driving, and sets it as characteristic information.

[0053] A method for setting characteristic information will be described in detail below, assuming that basic information K1 such as that shown in Fig. 3 has been stored. First, a case where characteristic information is represented by three characteristic parameters, namely, "age group," "whether or not there are family members living together," and "country," will be described. Note that, hereinafter, characteristic information composed of multiple characteristic parameters such as "age group," "whether or not there are family members living together," and "country" may be referred to as "first characteristic information."

[0054] The characteristic setting unit 15 extracts information from the basic information in accordance with predetermined rules and abstracts the extracted information to set the first characteristic information. For example, as shown in FIG. 4 , the characteristic setting unit 15 extracts "age" information from the basic information and abstracts it in accordance with rules that define those aged 30 or younger as "young people," those aged 31 to 60 as "middle-aged people," and those aged 61 or older as "elderly people," and converts it into "age group," which is one of the characteristic parameters constituting the first characteristic information. For example, since the "age" in the basic information K1 is "25 years old," the characteristic setting unit 15 sets "young people" as the "age group," which is one of the characteristic parameters constituting the characteristic information.

[0055] Furthermore, since the "region division" in the basic information K1 is "Kanto region," the characteristic setting unit 15 extracts information on the "Kanto region" from the basic information K1 and abstracts it according to the rules for "country name." In this case, as shown in Figure 4, the characteristic setting unit 15 sets "Japan" as the "country name," which is one of the characteristic parameters constituting the first characteristic information.

[0056] Furthermore, since the basic information K1 indicates that the "family structure" is "single," the characteristic setting unit 15 extracts the information "single" from the basic information K1 and abstracts it according to the rule for "whether or not there is family living together." In this case, as shown in Fig. 4, the characteristic setting unit 15 sets "none" as "whether or not there is family living together," which is one of the characteristic parameters constituting the first characteristic information.

[0057] The extraction and abstraction may be performed on a rule basis, or an inference model such as a neural network trained by machine learning may be used to estimate characteristic information from basic information. Furthermore, this extraction and abstraction is not essential, and the basic information may be used as characteristic information as is. In particular, when the amount of information in the basic information is small, it may be used as characteristic information as is.

[0058] Furthermore, the type of characteristic information can be set arbitrarily. For example, the characteristic information may be information that indicates a more specific driving situation. For example, the characteristic information may indicate a specific driving situation, such as "a single person's sports car driving on a mountain road on a sunny day" or "a family car driving in an urban area on a rainy night." Several specific driving situations may be prepared in advance, and the most appropriate driving situation may be selected from among them based on the basic information. Note that, hereinafter, characteristic information that indicates a specific driving situation may be referred to as second characteristic information.

[0059] The second characteristic information may be determined based on rules or by using an inference model. For example, as shown in Fig. 4, the characteristic setting unit 15 may input all of the basic information K1 into the inference model to infer that "a single person in a sports car is driving on a mountain road during the daytime on a sunny day" and set this as the second characteristic information.

[0060] Alternatively, clustering may be performed on the basic information, and the resulting clusters may be used as characteristic information. For example, a data set consisting of multiple pieces of basic information may be stored in advance, and clustering may be performed using a predetermined method to separate the pieces into multiple predetermined clusters. Then, basic information containing input information such as owner information may be included in the data set, and clustering may be performed using a predetermined method to separate the pieces into one of multiple predetermined clusters based on the similarity of the basic information. The clusters into which the input basic information is separated may then be used as characteristic information. Note that, hereinafter, characteristic information determined by clustering may be referred to as third characteristic information.

[0061] For example, as shown in FIG. 4, if the characteristic setting unit 15 includes basic information K1 in a dataset and performs clustering, and the result is classified into the first cluster, the first cluster may be set as the third characteristic information.

[0062] In this embodiment, the characteristic setting unit 15 may adopt any pattern of characteristic information from among the first characteristic information, the second characteristic information, and the third characteristic information.

[0063] The change unit 16 changes the acquisition conditions according to the characteristic information set by the characteristic setting unit 15. That is, the acquisition conditions change the acquisition scene and the parameter thresholds. A case where the first characteristic information is adopted will be described. For example, as shown in FIG. 5 , in the case of the first characteristic information T1 based on the basic information K1 (when the characteristic parameters are “young person,” “no family,” and “Japan”), the acquisition scene may be limited to a “parking scene” and the acquisition conditions may not be acquired for other scenes. Furthermore, as shown in FIG. 6 , in the case of the first characteristic information T2 based on the basic information K2 (when the characteristic parameters are “middle-aged or elderly,” “with family,” and “America”), the acquisition scene may be set to a “scene following a preceding vehicle” and the acquisition conditions may be satisfied when the “vehicle speed” is 50 km / h or higher.

[0064] Furthermore, when second characteristic information indicating specific driving conditions is employed, the determination of whether or not the second characteristic information is satisfied can be changed for each type of second characteristic information. For example, as shown in Fig. 7, when the second characteristic information is "a single person's sports car is driving on a mountain road on a sunny day," the acquisition condition is satisfied, but the acquisition condition may not be satisfied for other characteristic parameters (such as "a family car is driving on a city street on a rainy nighttime day").

[0065] Furthermore, when the third characteristic information determined by clustering is employed, whether or not the third characteristic information is satisfied may be changed for each cluster. For example, when the third characteristic information indicates the first cluster, the acquisition condition may be satisfied, and the acquisition condition may not be satisfied for other clusters.

[0066] The method for changing the acquisition conditions in accordance with the characteristic information may be stored in advance in the storage unit 10b, or may be downloaded from an external device such as the server 102 via the communication network 103.

[0067] The transmitter 17 transmits the data acquired by the data acquisition unit 14 and stored in the storage unit 10b to the server 102 via the communication network 103 at a predetermined transmission timing. The predetermined transmission timing is as described above.

[0068] The flow of data acquisition in this embodiment will be described below with reference to FIG. 8. The flow of data acquisition shown below is the flow of data acquisition processing performed by the verification processing unit 11. This processing is performed after the shadow mode is set. The timing at which the shadow mode is set is arbitrary, but may be, for example, the timing at which the ignition switch is turned on.

[0069] The characteristic setting unit 15 of the verification processing device 11 acquires basic information and sets characteristic information of the vehicle 101 during driving based on the acquired basic information (step S101). Next, the change unit 16 of the verification processing device 11 changes the acquisition conditions in accordance with the characteristic information set by the characteristic setting unit 15 (step S102). Thereafter, the input unit 12 of the verification processing device 11 inputs sensor information from the sensor 20 (step S103).

[0070] The processing unit 13 runs the program to be verified and performs processing based on various functions realized by the program to be verified, based on the input values ​​(sensor information) input from the input unit 12 (step S104). In step S104, the processing unit 13 inputs control signals as the processing results to the data acquisition unit 14.

[0071] The data acquisition unit 14 determines whether the acquisition condition is met based on at least one of the input value (sensor information) and the output result (control signal, etc.) (step S105). Note that the acquisition condition in step S105 is the acquisition condition changed in step S102 according to the characteristic information.

[0072] If the determination result is positive (if the acquisition condition is met), the data acquisition unit 14 stores (acquires) data regarding the input values ​​and output results in the storage unit 10b (step S106). When storing the data, the data acquisition unit 14 also associates the data with the characteristic information and the met acquisition condition, and then ends the process. On the other hand, if the determination result is negative, the verification processing unit 11 ends the process.

[0073] These processes are executed at regular intervals after the shadow mode is set. After the shadow mode is set, the processes of steps S101 and S102 may be skipped in the second and subsequent data acquisition processes.

[0074] The transmitter 17 transmits the data acquired by the data acquisition unit 14 and stored in the storage unit 10b to the server 102 via the communication network 103 at a predetermined transmission timing. At that time, the transmitter 17 also transmits characteristic information associated with the data and information regarding the acquisition conditions that have been met.

[0075] When the server 102 receives the data transmitted from the transmitter 17 of each vehicle 101, it stores the data in the storage device of the server 102. When storing the data, the data is stored in association with the characteristic information received together with the data. In other words, the data is stored after being classified by the characteristic information. In addition, information regarding the acquisition conditions that were met when the data was acquired may also be stored in association with the data. In other words, the data may be classified by the characteristic information, and then further classified by the acquisition conditions before being stored. This allows data based on similar assumptions, such as driving conditions, to be grouped, making it easier to analyze the data.

[0076] According to the first embodiment, the following effects are achieved.

[0077] The change unit 16 sets the characteristic information of the vehicle 101 during driving from the basic information, and changes the data acquisition conditions based on the characteristic information. This makes it possible to acquire data only for vehicles 101 that have predetermined characteristic information. This reduces the burden on communication, processing, analysis, and the like.

[0078] The thresholds of the parameters that make up the acquisition conditions and the acquisition scene are changed depending on the characteristics information. Therefore, the driving conditions to be acquired can be changed according to the characteristics information, and data that is more suitable for the characteristics information can be acquired.

[0079] The characteristic setting unit 15 uses GPS to acquire the location information of the vehicle 101 as information relating to the area in which the vehicle 101 is traveling, thereby eliminating the need for inputting information.

[0080] The characteristic setting unit 15 uses a deep neural network to recognize at least one of the time of day, weather, and road surface conditions when the vehicle 101 is traveling from the camera image of the camera 24, and sets the information as information about the situation in which the vehicle 101 is traveling. This can save the effort of inputting information, etc. Also, the basic information can be changed in real time and reflected in the characteristic information.

[0081] The characteristic setting unit 15 uses a deep neural network to recognize the roads on which the vehicle 101 has traveled from the camera image of the camera 24, and sets the information as information relating to the area in which the vehicle 101 is traveling. This can save the effort of inputting information, etc. Also, the basic information can be changed in real time and reflected in the characteristic information.

[0082] The characteristic setting unit 15 extracts necessary information from the basic information and abstracts it, or performs either extraction and abstraction, to convert it into one or more characteristic parameters that indicate the characteristics of the vehicle 101 while it is running, and sets it as characteristic information. Therefore, the amount of information in the characteristic information can be reduced compared to the basic information, making it easier to handle as parameters.

[0083] Furthermore, when the characteristic setting unit 15 sets characteristic information from basic information according to rules, the characteristic information can be made to better reflect the ideas of the rule designer. On the other hand, when the characteristic setting unit 15 sets characteristic information using an inference model or clustering, there is no need to determine detailed rules, and development efforts can be reduced.

[0084] (Variations of the First Embodiment) In the first embodiment, it is not necessary to acquire the control signal (data related to the output result) that is processed and output based on the implementation program. On the other hand, after the acquisition condition is met, sensor information (vehicle speed, yaw rate, acceleration amount, accelerator pedal operation amount, brake pedal operation amount, steering angle, etc.) detected when the vehicle 101 is operating may be acquired until a predetermined time has elapsed.

[0085] In the first embodiment, the driving assistance function does not need to be implemented. In this case, sensor information (vehicle speed, yaw rate, acceleration amount, accelerator pedal operation amount, brake pedal operation amount, steering angle, etc.) detected when the vehicle 101 is operating due to an operation by the driver may be acquired until a predetermined time has elapsed after the acquisition condition is met.

[0086] In the first embodiment, the verification processing unit 11 is provided. However, if the processing unit 10a can run the program to be verified together with the implementation program, the verification processing unit 11 does not have to be provided.

[0087] Second Embodiment A second embodiment in which the vehicle control device 10 in the first embodiment is partially modified will be described.

[0088] The change unit 16 of the second embodiment changes the data acquired by the data acquisition unit 14 in accordance with the characteristic information set by the characteristic setting unit 15. That is, the change unit 16 changes the number and type of data acquired by the data acquisition unit 14 in accordance with the characteristic information.

[0089] For example, the change unit 16 may change whether to acquire only data related to the sensor information input to the verification processing device 11 depending on the characteristic information, or whether to acquire both data related to the sensor information and the output results.

[0090] Furthermore, the change unit 16 may change the number and type of data related to the sensor information according to the characteristic information. For example, the change unit 16 may change whether to acquire data related to the vehicle speed, data related to the vehicle speed and yaw rate, or data related to the accelerator operation amount and steering amount from the sensor information according to the characteristic information.

[0091] Furthermore, the modification unit 16 may change the number and type of data related to the output results to be acquired according to the characteristic information. More specifically, the modification unit 16 may change, according to the characteristic information, which of the multiple functions (application programs) implemented by the program to be verified acquires data from which functions acquire data and which functions do not acquire data. For example, the modification unit 16 may change, according to the characteristic information, whether to acquire data related to the output results of the following driving function, the output results of the collision damage mitigation braking control function, or the output results of the automatic headlamp beam axis adjustment function.

[0092] The flow of data acquisition in the second embodiment will be described below with reference to Fig. 9. When the data acquisition process starts, steps S101 to S102 are performed in the same manner as in the first embodiment.

[0093] Then, the change unit 16 of the second embodiment changes the data acquired by the data acquisition unit 14 in accordance with the characteristic information set by the characteristic setting unit 15 (step S201). After that, steps S103 to S105 are performed.

[0094] If the determination result in step S105 is positive (if the acquisition condition is met), the data acquisition unit 14 of the second embodiment acquires the data related to the input values ​​and output results that were set to be acquired in step S201, and stores it in the storage unit 10b (step S202). Then, the processing ends. The following description is omitted as it is the same as in the first embodiment.

[0095] In the second embodiment, the acquisition conditions may or may not be changed, as in the first embodiment, i.e., the process of step S102 may not be performed.

[0096] According to the second embodiment, the following effects are achieved.

[0097] The change unit 16 changes the data to be acquired based on the characteristic information. More specifically, the change unit 16 changes at least one of the number and type of data to be acquired based on the characteristic information. This makes it possible to acquire only the data required according to the characteristic information, thereby reducing the burden on communication, processing, analysis, etc.

[0098] For example, when the second characteristic information is employed and the second characteristic information indicates that "a single driver's sports car is driving on a mountain road during sunny daytime," data related to the output results of the following driving function may be acquired, and data related to other output results may not be acquired, whereas when the second characteristic information indicates that "a family car is driving on an urban area during rainy nighttime," data related to the output results of the automatic headlamp beam axis adjustment function may be acquired, and data related to other output results may not be acquired. In this way, data related to the output results of the functions to be acquired can be appropriately changed according to the characteristic information.

[0099] Furthermore, when the first characteristic information is employed, for example, if the "country name" parameter in the first characteristic information is "Japan," data related to the output result of the rear cross traffic alert may be acquired, and data related to other output results may not be acquired, whereas if the "country name" parameter is "America," data related to the output result of the traffic sign recognition function may be acquired, and data related to other output results may not be acquired. This allows data related to the output result of the desired function to be acquired efficiently according to the characteristic information.

[0100] Third Embodiment A third embodiment will be described in which the vehicle control device 10 in the first embodiment is partially modified.

[0101] The modification unit 16 of the third embodiment modifies part or all of the program to be verified in accordance with the property information set by the property setting unit 15. For example, a plurality of programs to be verified may be stored in the storage unit 10b or the like, and the modification unit 16 may change the program to be verified either as the first program to be verified or as the second program to be verified in accordance with the property information.

[0102] In addition, for example, the change unit 16 may change which of the various functions (application programs) executed by the program to be verified is to be executed. Specifically, the change unit 16 may change whether or not to execute the following driving function, whether or not to execute the forward vehicle approach warning function, etc., depending on the characteristic information.

[0103] In addition, for example, the content of the function (application program) implemented by the program to be verified may be changed. For example, the change unit 16 may store multiple patterns of follow-up driving functions (application programs) and change which pattern of follow-up driving function is to be implemented depending on the characteristic information.

[0104] Furthermore, parameters such as thresholds in various functions may be changed according to the characteristic information. For example, in the following driving function, the change unit 16 may change whether the following distance is 30 m or 40 m according to the characteristic information.

[0105] The flow of data acquisition in the third embodiment will be described below with reference to Fig. 10. When the data acquisition process starts, steps S101 to S102 are performed in the same manner as in the first embodiment.

[0106] The modification unit 16 of the third embodiment then modifies part or all of the program to be verified in accordance with the property information set by the property setting unit 15 (step S301). Then, the processing from step S103 onward is performed. The flow of the subsequent processing is the same as that of the first embodiment, and therefore will not be repeated.

[0107] In the third embodiment, the acquisition conditions may or may not be changed, as in the first embodiment. That is, the process of step S102 may not be performed. Also, the third embodiment and the second embodiment may be combined. That is, the data to be acquired may be changed in the third embodiment.

[0108] According to the third embodiment, the following effects are achieved.

[0109] The modification unit 16 modifies part or all of the program to be verified in accordance with the characteristic information. This allows the verification content to be modified in accordance with the characteristic information to obtain the necessary data, thereby reducing the burden on communication load, processing load, analysis load, etc. Furthermore, because the content of the program to be verified is modified, the content of the function can be adjusted in accordance with the characteristic information to obtain the necessary output results. This allows various types of verification to be performed.

[0110] Fourth Embodiment A fourth embodiment will be described in which the vehicle control device 10 in the first embodiment is partially modified.

[0111] The vehicle control device 10 in the fourth embodiment is configured to acquire and collect only data related to sensor information and data related to output results based on the installed program, without executing the program to be verified. In other words, in the fourth embodiment, a data collection mode is set in which the program to be verified is not executed.

[0112] The configuration and functions relating to the data collection mode according to the fourth embodiment will be described below. In the fourth embodiment, the verification processing unit 11 is not provided, and the processing unit 10a performs the processing relating to the data collection mode. As in the first embodiment, the verification processing unit 11 may be provided and may perform the processing in place of the processing unit 10a. Furthermore, the verification target program is not stored.

[0113] 11 , in the fourth embodiment, the arithmetic processing device 10a of the vehicle control device 10 has a function as an input unit 112, a function as a processing unit 113, a function as a data acquisition unit 114, a function as a characteristic setting unit 115, a function as a change unit 116, and a function as a transmission unit 117. These functions are realized by the arithmetic processing device 10a as the arithmetic processing device 10a executes an in-vehicle program stored in the storage unit 10b.

[0114] The input unit 112 inputs sensor information from the sensor 20. The input unit 112 inputs some or all of the input sensor information to the processing unit 113 as input values ​​for the implementation program. The input unit 112 also inputs some or all of the input sensor information to the data acquisition unit 114.

[0115] The processing unit 113 runs the implementation program and performs processing based on various functions (application programs) realized by the implementation program, based on input values ​​(sensor information) input from the input unit 112. The processing unit 113 then inputs control signals (control signals for the actuator 30) as the processing results to the data acquisition unit 114. These control signals are also input to the actuator 30.

[0116] The data acquisition unit 114 determines whether or not an acquisition condition is met based on at least one of the input value (sensor information) input from the input unit 112 and the output result (control signal) input from the processing unit 13. The acquisition condition is the same as in the first embodiment, and therefore a description thereof will be omitted.

[0117] When the acquisition condition is met, the data acquisition unit 114 stores data related to the input values ​​and output results in the storage unit 10b. As described above, the input values ​​include, for example, sensor information input to the arithmetic processing device 10a. The output results include, for example, control signals processed and output based on the implementation program.

[0118] Furthermore, the data acquisition unit 114 of the arithmetic processing device 10a may input sensor information (vehicle speed, yaw rate, acceleration amount, accelerator pedal operation amount, brake pedal operation amount, steering angle, etc.) detected when a control signal processed and output based on the implementation program is input to the actuator 30 and the vehicle 101 operates, and store the information in the storage unit 10b. In other words, the sensor information related to the actual operation of the vehicle 101 for each scene, that is, the sensor information necessary to verify the correct operation, may also be stored.

[0119] The characteristic setting unit 115, the change unit 116, and the transmission unit 117 are similar to the characteristic setting unit 15, the change unit 16, and the transmission unit 17 in the first embodiment, and therefore a description thereof will be omitted.

[0120] The flow of data acquisition in this embodiment will be described below with reference to FIG. 12. The flow of data acquisition shown below is the flow of data acquisition processing performed by the arithmetic processing device 10a. These processes are performed after the data collection mode is set. The timing at which the data collection mode is set is the same as the timing at which the shadow mode is set in the first embodiment.

[0121] The characteristic setting unit 115 of the arithmetic processing device 10a acquires basic information and sets characteristic information of the vehicle 101 during driving based on the basic information (step S401). Next, the change unit 116 of the arithmetic processing device 10a changes the acquisition conditions in accordance with the characteristic information set by the characteristic setting unit 115 (step S402). Thereafter, the input unit 112 of the arithmetic processing device 10a inputs sensor information from the sensor 20 (step S403).

[0122] The processing unit 113 of the arithmetic processing device 10a runs the implementation program and performs processing based on various functions realized by the implementation program, based on the input values ​​(sensor information) input from the input unit 12 (step S404). In step S404, the processing unit 113 inputs control signals as the processing results to the actuator 30 and the data acquisition unit 114.

[0123] The data acquisition unit 114 determines whether the acquisition condition is met based on at least one of the input value (sensor information) and the output result (control signal, etc.) (step S405). Note that the acquisition condition in step S405 is the acquisition condition changed in step S402 according to the characteristic information.

[0124] If the determination result is positive (if the acquisition condition is met), the data acquisition unit 114 stores data regarding the input values ​​and output results in the storage unit 10b (step S406). When storing the data, the data acquisition unit 114 also associates the data with the characteristic information and the met acquisition condition and stores the data. Then, the processing ends. On the other hand, if the determination result is negative, the arithmetic processing device 10a ends the processing as is.

[0125] These processes are executed at regular intervals after the shadow mode is set. After the shadow mode is set, the processes of steps S401 and S402 may be skipped in the second and subsequent data acquisition processes.

[0126] The transmitter 117 transmits the data acquired by the data acquisition unit 114 and stored in the storage unit 10b to the server 102 via the communication network 103 at a predetermined transmission timing. At that time, the transmitter 117 also transmits characteristic information associated with the data and information regarding the acquisition conditions that have been met. The processing of the server 102 is the same as in the first embodiment, and therefore will not be described.

[0127] According to the fourth embodiment, the following effects are achieved.

[0128] Since the program to be verified is not executed, the processing load can be reduced. Accordingly, the verification processing unit 11 does not need to be provided, and the configuration can be simplified.

[0129] (Modification of the Fourth Embodiment) In the fourth embodiment, the change unit 116 may change the data to be acquired in accordance with the characteristic information, similar to the second embodiment. In this case, it is not necessary to change the acquisition conditions.

[0130] In the fourth embodiment, the data acquisition unit 114 acquires data related to the output results (control signals) based on the operation of the installed program. However, it is not necessary to acquire data related to the output results based on the operation of the installed program. In this case, only sensor information used as input values ​​may be acquired. Furthermore, a control signal processed and output based on the installed program may be input to the actuator 30, and sensor information (vehicle speed, yaw rate, acceleration amount, accelerator pedal operation amount, brake pedal operation amount, steering angle, etc.) detected when the vehicle 101 operates may be acquired.

[0131] In the fourth embodiment, the implementation program is executed to perform various driving assistance functions during the data collection mode, but the various driving assistance functions do not have to be executed during the data collection mode. In other words, during the data collection mode, sensor information (vehicle speed, yaw rate, acceleration amount, accelerator pedal operation amount, brake pedal operation amount, steering angle, etc.) detected when the vehicle 101 is operating may be acquired based on operations by the driver.

[0132] More specifically, the input unit 112 receives sensor information from the sensor 20 and inputs part or all of the received sensor information to the data acquisition unit 114 .

[0133] The data acquisition unit 114 determines whether or not an acquisition condition is met based on the input value (sensor information) input from the input unit 112. The acquisition condition is the same as in the first embodiment, and therefore a description thereof will be omitted.

[0134] When an acquisition condition is met, the data acquisition unit 114 stores data related to the input values ​​in the storage unit 10b. After the acquisition condition is met, the data acquisition unit 114 of the arithmetic processing device 10a inputs sensor information detected when the vehicle 101 is operating based on an operation by the driver via the input unit 112 or the like, and stores data related to the sensor information in the storage unit 10b. The sensor information detected when the vehicle 101 is operating includes vehicle speed, yaw rate, acceleration amount, accelerator pedal operation amount, brake pedal operation amount, steering angle, etc. After the acquisition condition is met, the data acquisition unit 114 inputs and stores the sensor information until a predetermined time has elapsed. The predetermined time may be changed depending on the type of acquisition condition that has been met.

[0135] The characteristic setting unit 115, the change unit 116, and the transmission unit 117 are similar to the characteristic setting unit 15, the change unit 16, and the transmission unit 17 in the first and fourth embodiments, and therefore description thereof will be omitted.

[0136] The flow of data acquisition in this modified example will be described below with reference to Fig. 13. The flow of data acquisition shown below is the flow of data acquisition processing performed by the arithmetic processing device 10a. This processing is performed after the data collection mode is set.

[0137] The characteristic setting unit 115 of the arithmetic processing device 10a acquires basic information and sets characteristic information of the vehicle 101 during driving based on the basic information (step S501). Next, the change unit 116 of the arithmetic processing device 10a changes the acquisition conditions in accordance with the characteristic information set by the characteristic setting unit 115 (step S502).

[0138] Thereafter, the input unit 112 of the arithmetic processing device 10a inputs the sensor information from the sensor 20 (step S503). The data acquisition unit 114 determines whether the acquisition condition is met based on the input value (sensor information) (step S504). Note that the acquisition condition in step S504 is the acquisition condition changed in step S502 according to the characteristic information.

[0139] If the determination result is positive (if the acquisition condition is met), the data acquisition unit 114 stores data related to the input value in the storage unit 10b (step S505). The data acquisition unit 114 also inputs sensor information detected when the vehicle 101 is operating until a predetermined period of time has elapsed, and stores data related to the sensor information in the storage unit 10b. When storing the data, the data acquisition unit 114 also associates the data with characteristic information and the met acquisition condition, and stores the data. Then, the processing ends. On the other hand, if the determination result is negative, the arithmetic processing device 10a ends the processing. The following description is omitted as it is the same as in the fourth embodiment.

[0140] In this modification, the change unit 116 may change the data to be acquired in accordance with the characteristic information, similar to the second embodiment, without changing the acquisition conditions.

[0141] The controller and methods described herein may be implemented by a special-purpose computer configured with a processor and memory programmed to perform one or more functions embodied in a computer program. Alternatively, the controller and methods described herein may be implemented by a special-purpose computer configured with a processor configured with one or more dedicated hardware logic circuits. Alternatively, the controller and methods described herein may be implemented by one or more special-purpose computers configured with a processor and memory programmed to perform one or more functions in combination with a processor configured with one or more hardware logic circuits. Furthermore, the computer program may be stored as instructions executed by a computer on a computer-readable non-transitory storage medium.

[0142] The following describes technical ideas that can be derived from the above-described embodiment and modifications.

[0143] [Configuration 1] A vehicle control device (10) mounted on a vehicle (101), comprising: a characteristic setting unit (15) that acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on the information; a data acquisition unit (14) that acquires data related to sensor information acquired by various sensors mounted on the vehicle when a data acquisition condition is met; and a transmission unit (17) that transmits the data acquired by the data acquisition unit to a server via a communication network, wherein at least one of the acquisition conditions and the data acquired by the data acquisition unit is changed according to the characteristic information. [Configuration 2] The vehicle control device is configured to be able to implement a shadow mode in which the program to be verified operates in a manner not related to the control of the vehicle, and the data acquisition unit acquires data on the output result together with the data on the sensor information when the program to be verified is executed or will be executed using the sensor information as an input value, or acquires data on the output result instead of the data on the sensor information.[Configuration 3] A vehicle control device (10) that is mounted on a vehicle (101) and is configured to be capable of implementing a shadow mode in which a program to be verified operates without being involved in the control of the vehicle, the vehicle control device comprising: a characteristic setting unit (15) that acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on that information; a modification unit (16) that modifies part or all of the program to be verified in accordance with the characteristic information; a data acquisition unit (14) that uses sensor information acquired by various sensors mounted on the vehicle as input values ​​and, when a data acquisition condition is met when the program to be verified is executed or has been executed, acquires data about the output result together with data about the sensor information, or acquires data about the output result instead of data about the sensor information; and a transmission unit (17) that transmits the data acquired by the data acquisition unit to a server via a communication network. [Configuration 4] The vehicle control device of Configuration 3, wherein the change unit further changes at least one of the acquisition conditions and the data acquired by the data acquisition unit according to the characteristic information. [Configuration 5] The vehicle control device of any of Configurations 1 to 4, wherein the characteristic setting unit acquires location information of the vehicle as information related to the area in which the vehicle is traveling using a GPS. [Configuration 6] The vehicle control device of any of Configurations 1 to 5, wherein the characteristic setting unit uses a deep neural network to recognize at least one of the time of day, weather, and road surface conditions when the vehicle is traveling from camera images of an on-board camera, and obtains the information related to the situation in which the vehicle is traveling. [Configuration 7] The vehicle control device of any of Configurations 1 to 6, wherein the characteristic setting unit uses a deep neural network to recognize roads on which the vehicle has traveled from camera images of an on-board camera, and obtains the information related to the area in which the vehicle is traveling.[Configuration 8] The vehicle control device according to any one of Configurations 1 to 7, wherein the characteristic setting unit inputs at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling into an inference model, and outputs the characteristic information based on that information. [Configuration 9] The vehicle control device according to any one of Configurations 1 to 7, wherein the characteristic setting unit performs clustering on information including at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets the characteristic information to clusters divided into clusters. [Configuration 10] An in-vehicle program executed by a vehicle control device (10) mounted on a vehicle (101), the in-vehicle program causing the vehicle control device to perform the following steps: a characteristic setting step of causing the vehicle control device to acquire at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and to set characteristic information about the vehicle while traveling based on that information; a data acquisition step of causing the vehicle control device to acquire data about sensor information acquired by various sensors mounted on the vehicle when a data acquisition condition is met; and a transmission step of causing the data acquired by the data acquisition unit to be transmitted to a server via a communication network, wherein at least one of the acquisition conditions and the data acquired by the data acquisition unit is changed according to the characteristic information.[Configuration 11] An on-board program executed by a vehicle control device (10) mounted on a vehicle (101) and configured to be capable of implementing a shadow mode in which a program to be verified operates without being involved in the control of the vehicle, the on-board program causing the vehicle control device to perform the following steps: a characteristic setting step in which the vehicle control device acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on that information; a modification step in which the vehicle control device modifies part or all of the program to be verified according to the characteristic information; a data acquisition step in which, using sensor information acquired by various sensors mounted on the vehicle as input values, when a data acquisition condition is met when the program to be verified is executed or has been executed, the vehicle control device acquires data about the output result together with data about the sensor information, or acquires data about the output result instead of data about the sensor information; and a transmission step in which the vehicle control device transmits the data acquired by the data acquisition unit to a server via a communication network.

[0144] Although the present disclosure has been described with reference to the embodiments, it is understood that the present disclosure is not limited to the embodiments or structures. The present disclosure also encompasses various modifications and equivalent modifications. In addition, various combinations and forms, including only one element, more than one element, or less than one element, are also within the scope and spirit of the present disclosure.

Claims

1. A vehicle control device (10) mounted on a vehicle (101), comprising: a characteristic setting unit (15) that acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on that information; a data acquisition unit (14) that acquires data about sensor information acquired by various sensors mounted on the vehicle when a data acquisition condition is met; and a transmission unit (17) that transmits the data acquired by the data acquisition unit to a server via a communication network, wherein at least one of the acquisition conditions and the data acquired by the data acquisition unit is changed according to the characteristic information.

2. The vehicle control device of claim 1, wherein the vehicle control device is configured to be capable of implementing a shadow mode in which the program to be verified operates in a manner not related to the control of the vehicle, and the data acquisition unit acquires data regarding the output results together with the data regarding the sensor information when the program to be verified is executed using the sensor information as input values, or acquires data regarding the output results instead of the data regarding the sensor information.

3. A vehicle control device (10) mounted on a vehicle (101) and configured to be capable of implementing a shadow mode in which a program to be verified operates without being involved in the control of the vehicle, the vehicle control device comprising: a characteristic setting unit (15) that acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on that information; a modification unit (16) that modifies part or all of the program to be verified in accordance with the characteristic information; a data acquisition unit (14) that uses sensor information acquired by various sensors mounted on the vehicle as input values ​​and, when a data acquisition condition is met when the program to be verified is executed or has been executed, acquires data about the output result together with data about the sensor information, or acquires data about the output result instead of data about the sensor information; and a transmission unit (17) that transmits the data acquired by the data acquisition unit to a server via a communication network.

4. The vehicle control device according to claim 3, wherein the change unit further changes at least one of the acquisition conditions and the data acquired by the data acquisition unit in accordance with the characteristic information.

5. A vehicle control device according to any one of claims 1 to 4, wherein the characteristic setting unit uses a GPS to acquire location information of the vehicle as information relating to the area in which the vehicle is traveling.

6. A vehicle control device according to any one of claims 1 to 4, wherein the characteristic setting unit uses a deep neural network to recognize at least one of the time of day, weather, and road conditions when the vehicle is traveling from camera images captured by an onboard camera, and uses this information as information regarding the situation in which the vehicle is traveling.

7. A vehicle control device according to any one of claims 1 to 4, wherein the characteristic setting unit uses a deep neural network to recognize the road on which the vehicle has traveled from camera images captured by an onboard camera, and uses the recognized information as information relating to the area in which the vehicle is traveling.

8. A vehicle control device described in any one of claims 1 to 4, wherein the characteristic setting unit inputs at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling into an inference model, and outputs the characteristic information based on that information.

9. A vehicle control device according to any one of claims 1 to 4, wherein the characteristic setting unit performs clustering on information including at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets the clusters obtained as the characteristic information.

10. An on-board program executed by a vehicle control device (10) mounted on a vehicle (101), which causes the vehicle control device to perform the following steps: a characteristic setting step for acquiring at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and setting characteristic information about the vehicle while traveling based on that information; a data acquisition step for acquiring data about sensor information acquired by various sensors mounted on the vehicle when a data acquisition condition is met; and a transmission step for transmitting the data acquired in the data acquisition step to a server via a communication network, wherein at least one of the acquisition conditions and the data acquired in the data acquisition step is changed according to the characteristic information.

11. An on-board program executed by a vehicle control device (10) mounted on a vehicle (101) and configured to be capable of implementing a shadow mode in which a program to be verified operates without being involved in the control of the vehicle, the on-board program executing the following steps: a characteristic setting step in which the vehicle control device acquires at least one of information about the vehicle itself, information about the owner of the vehicle, information about the situation in which the vehicle is traveling, and information about the area in which the vehicle is traveling, and sets characteristic information about the vehicle while traveling based on that information; a modification step in which part or all of the program to be verified is modified according to the characteristic information; a data acquisition step in which, using sensor information acquired by various sensors mounted on the vehicle as input values, if a data acquisition condition is met when the program to be verified is executed or has been executed, data about the output results is acquired together with data about the sensor information, or data about the output results is acquired instead of data about the sensor information; and a transmission step in which the data acquired in the data acquisition step is transmitted to a server via a communication network.

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