Data collection device and data collection program

Abstract

A data collection device (102) for collecting data from a plurality of vehicles (101) via a communication network (103) comprises: a collection unit (51) that receives, stores, and collects data acquisition failure information and characteristic information pertaining to the vehicles that have transmitted the data acquisition failure information; an acquisition condition change unit (52); and an instruction unit (53) that gives, if the acquisition condition change unit has determined that the acquisition condition should be changed, an instruction to this effect to the plurality of vehicles. On the basis of the characteristic information, the collection unit classifies the acquisition failure information into one or more groups. The acquisition condition change unit determines to change the acquisition condition if the number of acquisition failure information in any of the groups is greater than or equal to a threshold. The instruction unit identifies characteristic information associated with the acquisition failure information classified as belonging to the group in which the number of the acquisition failure information is greater than or equal to the threshold, and instructs a vehicle for which is set the identified characteristic information to change the acquisition condition.

Description

Data collection device and data collection program CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is based on Japanese Application No. 2024-069044, filed on April 22, 2024, the contents of which are incorporated herein by reference.

[0002] The present disclosure relates to a data collection device and a data collection 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 to be used in future vehicle development or to update the vehicle's control program.

[0004] One example of such a method is a verification method called shadow mode, in which a vehicle control program to be verified is run while the vehicle is running after sales to verify its performance and safety. In a verification using shadow mode, the vehicle control 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 an external network or the like. The collected data is then analyzed to verify the operation of the vehicle control program. Technology related to such shadow mode is described, for example, in Patent Document 1.

[0005] International Publication No. 2022 / 004324

[0006] Incidentally, when collecting data, data is collected when a predetermined trigger condition (acquisition condition) is met. However, if the trigger condition is not set appropriately, data associated with the fulfillment of the trigger condition may not be collected properly, or conversely, excessive data associated with the fulfillment of the trigger condition may be collected, which causes problems.

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

[0008] a collection unit that receives acquisition failure information indicating that a data acquisition condition was not met and characteristic information of the vehicle that transmitted the acquisition failure information, and stores and collects the acquisition failure information in a storage device in association with the characteristic information; an acquisition condition change unit that decides whether to change the acquisition conditions; and an instruction unit that, when the acquisition condition change unit has decided to change the acquisition conditions, instructs the multiple vehicles to do so via the communication network. When storing the acquisition failure information, the collection unit classifies the acquisition failure information associated with the characteristic information based on the characteristic information and sorts it into one or more groups. When the number of pieces of acquisition failure information collected in any of the groups over a predetermined period is equal to or greater than a threshold, the acquisition condition change unit decides to change the acquisition conditions. The instruction unit identifies the characteristic information associated with the acquisition failure information sorted into a group in which the number of pieces of acquisition failure information is equal to or greater than the threshold, and instructs the vehicle for which the identified characteristic information is set to change the acquisition conditions.

[0009] As a result, even if acquisition conditions that do not correspond to the vehicle characteristic information are set, the acquisition conditions for each vehicle can be changed in accordance with the characteristic information by instructions from the instruction unit. Therefore, the acquisition conditions are changed to appropriate acquisition conditions according to the characteristic information, and data can be collected efficiently.

[0010] A second data collection device that solves the above problem is a data collection device that collects data from a plurality of vehicles via a communication network, and includes: a collection unit that receives data acquired when data acquisition conditions are met and characteristic information of the vehicle that transmitted the data, and stores and collects the data in a storage device in association with the characteristic information; an acquisition condition change unit that decides whether to change the acquisition conditions; and an instruction unit that, when the acquisition condition change unit decides to change the acquisition conditions, instructs the plurality of vehicles to do so via the communication network.When storing the data, the collection unit classifies the data associated with the characteristic information based on the characteristic information and sorts it into one or more groups.If the quantity of data collected in any of the groups over a specified period is outside an appropriate range, the acquisition condition change unit decides to change the acquisition conditions.The instruction unit identifies the characteristic information associated with the data sorted into a group where the quantity of data is outside the appropriate range, and instructs the vehicle to which the identified characteristic information is set to change the acquisition conditions.

[0011] As a result, even if acquisition conditions that do not correspond to the vehicle characteristic information are set, the acquisition conditions for each vehicle can be changed in accordance with the characteristic information by instructions from the instruction unit. Therefore, the acquisition conditions are changed to appropriate acquisition conditions according to the characteristic information, and data can be collected efficiently.

[0012] a collection step of receiving acquisition failure information indicating that a data acquisition condition was not met and characteristic information of the vehicle that transmitted the acquisition failure information, and storing the acquisition failure information in a storage device to collect the information; an acquisition condition change step of determining whether to change the acquisition conditions; and an instruction step of, if a change in the acquisition conditions is decided by the acquisition condition change step, instructing the plurality of vehicles to do so via the communication network. In the collection step, when storing the acquisition failure information, the acquisition failure information associated with the characteristic information is classified based on the characteristic information and sorted into one or more groups; in the acquisition condition change step, if the number of pieces of acquisition failure information collected in any of the groups within a predetermined period is equal to or greater than a threshold, it is decided to change the acquisition conditions; and in the instruction step, the characteristic information associated with the acquisition failure information sorted into a group in which the number of pieces of acquisition failure information is equal to or greater than a threshold is identified, and an instruction step is performed to change the acquisition conditions for the vehicle for which the identified characteristic information is set.

[0013] As a result, even if acquisition conditions that do not correspond to the vehicle characteristic information are set, the acquisition conditions for each vehicle can be changed in accordance with the characteristic information by instructions from the instruction unit. Therefore, the acquisition conditions are changed to appropriate acquisition conditions according to the characteristic information, and data can be collected efficiently.

[0014] a collection step of receiving data acquired when a data acquisition condition is satisfied and characteristic information of the vehicle that transmitted the data, and storing and collecting the data in a storage device in association with the characteristic information; an acquisition condition change step of determining whether to change the acquisition conditions; and an instruction step of instructing the multiple vehicles to change the acquisition conditions via the communication network if the acquisition condition change step determines that the acquisition conditions should be changed. In the collection step, when storing the data, the data associated with the characteristic information is classified based on the characteristic information and sorted into one or more groups. In the acquisition condition change step, if the quantity of data collected in any of the groups over a predetermined period is outside an appropriate range, it is determined that the acquisition conditions should be changed. In the instruction step, characteristic information associated with data sorted into a group where the quantity of data is outside the appropriate range is identified, and the vehicle for which the identified characteristic information is set is instructed to change the acquisition conditions.

[0015] As a result, even if acquisition conditions that do not correspond to the vehicle characteristic information are set, the acquisition conditions for each vehicle can be changed in accordance with the characteristic information by instructions from the instruction unit. Therefore, the acquisition conditions are changed to appropriate acquisition conditions according to the characteristic information, and data can be collected efficiently.

[0016] 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 of a vehicle control device and a server, Fig. 3 is a diagram for explaining basic information, Fig. 4 is a diagram for explaining characteristic information, Fig. 5 is a flowchart of a data acquisition process, Fig. 6 is a diagram showing a data structure in storage, Fig. 7 is a diagram showing a data structure in storage in a modified example, and Fig. 8 is a diagram showing a data structure in storage in a modified example.

[0017] Hereinafter, embodiments of a data collection device and a data collection 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 descriptions will not be repeated in principle.

[0018] (First embodiment) Fig. 1 shows a data collection system 100 according to this embodiment. As shown in Fig. 1, the data collection system 100 includes a server 102 as a data collection device, 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. The vehicle control device 10 is mounted on the vehicle 101 and controls the vehicle 101 and performs driving assistance.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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 changed via a communication network 103, such as the Internet, via over-the-air (OTA) or other means.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] When the verification processing unit 11 is running the program to be verified in shadow mode, it receives sensor information from the various sensors 20, just like the processing unit 10a. Based on the received sensor information, the verification processing unit 11 then performs various functions and outputs various control signals for operating each actuator 30. 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 that time, the verification processing unit 11 also stores data related to the sensor information, which is an input value, in association with the data.

[0032] 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.

[0033] 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.

[0034] The vehicle control device 10 uploads the data 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 after the completion of a data acquisition process described below. Alternatively, the predetermined transmission timing may be, for example, a timing when the vehicle 101 is charging, when the vehicle is parked, when the ignition switch is turned off, or the like.

[0035] The server 102 includes a server CPU 102a and a storage 102b serving as a storage device for storing data, etc. The functions provided by the server 102 can be provided by software recorded in a physical memory device and a computer that executes the software, software alone, hardware alone, or a combination of these. For example, the server CPU 102a executes a program stored in a non-transitory tangible storage medium serving as the storage 102b provided by the server 102. The program includes, for example, a program that realizes the functions shown in FIG. 2, etc. Execution of the program results in the execution of a method corresponding to the program. The program stored in the storage 102b can be downloaded and modified from an external device via the communication network 103.

[0036] The server 102 has a function of storing data received from the vehicle control device 10 via the communication network 103 in the storage 102b, and collecting data.

[0037] However, it is difficult to store all data during driving due to issues of storage capacity and communication load. For this reason, data is acquired when predetermined acquisition conditions (trigger conditions) are met so that data for specific scenes can be collected. However, the appropriateness of the acquisition conditions varies depending on the driving conditions of the vehicle 101, etc. If the acquisition conditions are not set appropriately, data may not be collected effectively, or conversely, excessive data may be collected, which is a problem.

[0038] For example, a vehicle 101 that mainly travels at low speeds in urban areas rarely travels at high speeds on expressways. Nevertheless, if the acquisition conditions for high-speed travel are too strict, the probability that the acquisition conditions will be met during high-speed travel drops dramatically, making it difficult to collect data. Therefore, the acquisition conditions are configured to be changed appropriately depending on the travel conditions of the vehicle 101, as will be described in detail below.

[0039] 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 condition setting 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.

[0040] The server 102 also has a function as a collection unit 51, a function as an acquisition condition change unit 52 that changes the acquisition conditions, and a function as an instruction unit 53. These functions are realized by the server CPU 102a by executing a data collection program stored in the storage 102b of the server 102.

[0041] First, we will explain the functions realized by the verification processing device 11 of the vehicle control device 10. The input unit 12 inputs sensor information from the sensor 20. The input unit 12 then inputs some 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 some or all of the input sensor information to the data acquisition unit 14.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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).

[0049] 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.

[0050] Furthermore, the acquisition condition is established when all of the constituent elements of 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 the 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).

[0051] 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.

[0052] 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.

[0053] 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.

[0054] 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, positions, and types 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 dealership worker or the like inputting the information into an input device (e.g., a touch panel display), and then stored in the storage unit 10b.

[0055] 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 an operator or the like inputting it into an input device, and is then stored in the memory unit 10b.

[0056] 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.

[0057] 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 an operator 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.

[0058] 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.

[0059] A method for setting characteristic information will be described in detail below, assuming that basic information K1 and K2 such as those shown in Fig. 3 are 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."

[0060] 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, 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 the information into "age group," which is one of the characteristic parameters constituting the first characteristic information. For example, as shown in FIG. 4, 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.

[0061] Furthermore, since the "regional 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, the characteristic setting unit 15 sets "Japan" as the "country name," which is one of the characteristic parameters constituting the first characteristic information.

[0062] 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 in accordance with the rule for "whether or not there is family living together." In this case, the characteristic setting unit 15 sets "none" as the "whether or not there is family living together," which is one of the characteristic parameters constituting the first characteristic information.

[0063] 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.

[0064] 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.

[0065] 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.

[0066] 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.

[0067] For example, as shown in Figure 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.

[0068] 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.

[0069] The characteristic information set by the characteristic setting unit 15 is stored in the storage unit 10b in association with the data when the data acquisition unit 14 acquires the data.

[0070] The condition setting unit 16 sets data acquisition conditions. Specifically, the acquisition conditions include setting acquisition scenes, functions to be performed, and parameter thresholds. The condition setting unit 16 of this embodiment changes the acquisition conditions in accordance with the characteristic information set by the characteristic setting unit 15. Setting of the acquisition conditions will be described later.

[0071] 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 and is performed after the data acquisition process. When transmitting the data, the transmitter 17 associates the data with the characteristic information that was set when the acquisition condition was met and transmits it to the server 102.

[0072] The flow of data acquisition in this embodiment will be described below with reference to FIG. 5. The data acquisition flow shown below is the flow of data acquisition processing performed by the verification processing unit 11. These processes are performed after the shadow mode is set. The shadow mode can be set at any timing, for example, when the ignition switch is turned on. The data acquisition processing is performed at predetermined intervals.

[0073] First, the characteristic setting unit 15 of the verification processing device 11 acquires basic information and sets characteristic information of the vehicle 101 during running based on the basic information (step S101).

[0074] Then, the condition setting unit 16 of the verification processing unit 11 sets acquisition conditions in accordance with the characteristic information set by the characteristic setting unit 15 (step S102). After that, the input unit 12 of the verification processing unit 11 inputs sensor information from the sensor 20 (step S103).

[0075] 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.

[0076] 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 set in step S102.

[0077] 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 (hereinafter referred to as the met condition). Then, the data acquisition process ends.

[0078] On the other hand, if the determination result in step S105 is negative (if the acquisition condition is not met), the data acquisition unit 14 of the verification processing unit 11 stores acquisition failure information indicating that data acquisition was not possible in the storage unit 10b (step S107). At this time, the acquisition failure information is stored in association with the characteristic information. Then, the data acquisition process ends.

[0079] After one or more data acquisition processes are completed, the transmitter 17 transmits the data stored in the memory 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. When transmitting the data, the transmitter 17 also transmits information regarding the fulfillment conditions associated with the data. The information regarding the fulfillment conditions is information indicating which acquisition conditions have been fulfilled.

[0080] Furthermore, if the acquisition failure information is stored in the storage unit 10b, the transmitter 17 transmits the acquisition failure information indicating that the data could not be acquired in association with the characteristic information.

[0081] Next, the server 102 will be described. The collection unit 51 of the server 102 receives data transmitted from the transmission unit 17 and collects the data. More specifically, when the collection unit 51 receives data transmitted from the transmission unit 17 of each vehicle 101, the collection unit 51 stores the data in the storage 102b of the server 102. When storing data, the collection unit 51 associates the data with characteristic information received together with the data and stores the data. That is, the collection unit 51 stores the data in association with the characteristic information so that it is possible to identify the driving conditions of the vehicle 101 from which the data was obtained. Furthermore, when storing data, the collection unit 51 associates the data with information regarding the fulfillment conditions received together with the data and stores the data. That is, the collection unit 51 stores the data in association with the fulfillment conditions so that it is possible to identify the acquisition conditions that were met to acquire the data.

[0082] Furthermore, when the collection unit 51 receives acquisition failure information, it stores the acquisition failure information in the storage 102b in association with the received characteristic information. At this time, the collection unit 51 sorts the acquisition failure information into one or more groups based on the characteristic information and stores the group in the storage 102b. For example, if there are only a few types (patterns) of characteristic information, the collection unit 51 may group the acquisition failure information by characteristic information. Furthermore, if there are many types (patterns) of characteristic information, the collection unit 51 may perform clustering based on the similarity of the characteristic information and classify the acquisition failure information by group (cluster).

[0083] In other words, one or more pieces of characteristic information are classified into one group (cluster), and the acquisition failure information associated with these pieces of characteristic information is also classified into that cluster. Specifically, as shown in Figure 6, if characteristic information T1 to T10 are classified into the first cluster, the acquisition failure information associated with each piece of characteristic information T1 to T10 will also be classified into the first cluster. The same applies to the data structure of the second and subsequent clusters. The final number of groups (clusters) can be changed as desired depending on the scale of data to be collected and the storage capacity of storage 102b.

[0084] The acquisition condition changing unit 52 determines, for each predetermined period, whether the number of pieces of acquisition failure information classified into any group is equal to or greater than a threshold. That is, the acquisition condition changing unit 52 calculates the number of pieces of acquisition failure information in each group. Specifically, as shown in FIG. 6 , in the first cluster (group), the acquisition failure information 1 to N associated with the characteristic information T1, the acquisition failure information 1 to M associated with the characteristic information T2, and the acquisition failure information 1 to L associated with the characteristic information T10 are added together to calculate the number of pieces of acquisition failure information in the first cluster.

[0085] The acquisition condition change unit 52 then determines whether or not a group exists in which the number of pieces of acquisition failure information is equal to or greater than a threshold. If a group in which the number of pieces of acquisition failure information is equal to or greater than a threshold exists, the acquisition condition change unit 52 identifies the group and identifies the characteristic information classified into the group. Specifically, with reference to FIG. 6 , if the number of pieces of acquisition failure information in the first cluster (group) is equal to or greater than a threshold, the acquisition condition change unit 52 identifies the characteristic information T1 to T10 of the first cluster.

[0086] Then, the acquisition condition changing unit 52 determines to change the acquisition conditions for the vehicle 101 in which the specified characteristic information is set. At that time, the acquisition condition changing unit 52 determines to relax the acquisition conditions so as to reduce the number of pieces of acquisition failure information.

[0087] The instruction unit 53 instructs each vehicle 101 on the contents determined by the acquisition condition change unit 52, i.e., instructions on relaxing the acquisition conditions and on the characteristic information for relaxing the acquisition conditions, via the communication network 103. Upon receiving the instruction from the instruction unit 53, each vehicle 101 temporarily stores the instruction in the storage unit 10b of the vehicle control device 10.

[0088] In this embodiment, the processing by the collection unit 51 corresponds to a collection step, the processing by the acquisition condition change unit 52 corresponds to an acquisition condition change step, and the processing by the instruction unit 53 corresponds to an instruction step. The processing is executed in the order of collection step → acquisition condition change step → instruction step.

[0089] Then, if the characteristic information set in step S101 of the data acquisition process matches the characteristic information for which the server 102 has instructed that the acquisition conditions be relaxed, the acquisition condition change unit 52 relaxes the acquisition conditions in step S102 of the data acquisition process. Any method may be used to relax the acquisition conditions.

[0090] For example, if the parameter threshold in the acquisition conditions is set to "vehicle speed of 50 km or more," the condition is relaxed to "vehicle speed of 40 km or more." Furthermore, if the acquisition conditions include "simultaneous implementation of a forward vehicle approach warning function and a collision damage mitigation braking control function" (AND condition), the condition is relaxed to "implementation of either a forward vehicle approach warning function or a collision damage mitigation braking control function" (OR condition). Furthermore, if the acquisition conditions include "a scene of following a forward vehicle at night," the time-of-day condition is deleted, and the condition is simply set to "a scene of following a forward vehicle."

[0091] Rules for how to relax the acquisition conditions may be stored in advance in the storage unit 10b or the like. Alternatively, the server 102 may determine how to relax the acquisition conditions and instruct each vehicle 101. In this case, how to relax the acquisition conditions may be stored in advance in the storage 102b or the like. Similarly, the contents of the acquisition conditions at the time of initial setup may be stored in advance in the storage unit 10b or the like of the vehicle 101, or may be instructed by the server 102.

[0092] Furthermore, the acquisition conditions may be relaxed in stages each time an instruction is issued. For example, the threshold value of a parameter in the acquisition conditions may be relaxed in stages from a vehicle speed of 50 km or more to a vehicle speed of 40 km or more to a vehicle speed of 30 km or more.

[0093] According to the first embodiment, the following effects are achieved.

[0094] When storing the acquisition failure information, the collection unit 51 of the server 102 classifies the acquisition failure information associated with the characteristic information based on the characteristic information and sorts it into one or more groups. Then, if the number of acquisition failure information classified into any group for each predetermined period is equal to or greater than a threshold, the acquisition condition change unit 52 identifies the characteristic information classified into that group. Then, the acquisition condition change unit 52 determines to relax the acquisition conditions for the vehicles 101 for which the identified characteristic information is set, and the instruction unit 53 instructs each vehicle 101 to do so.

[0095] As a result, even if an acquisition condition that does not appropriately correspond to the characteristics of the vehicle 101, such as the driving conditions, is set, the acquisition condition is changed according to the characteristic information in response to an instruction from the server 102. As a result, for example, for a vehicle 101 that mainly drives at low speeds in urban areas, the speed threshold in the acquisition condition can be lowered to make the acquisition condition more likely to be met. Therefore, the acquisition condition is changed to an appropriate one according to the characteristic information, and data can be collected efficiently.

[0096] The server 102 determines whether or not to change the acquisition conditions based on the acquisition failure information collected from the plurality of vehicles 101 via the communication network 103. Therefore, the acquisition conditions can be changed based on the overall trend, not depending on the special circumstances of only some of the vehicles 101.

[0097] The acquisition failure information is sorted into several groups based on the characteristic information. Therefore, even if the types of characteristic information (number and types of parameters, types of acquisition scenes, etc.) are set in detail, it is possible to issue a change instruction to vehicles 101 that are sorted into the same group and have similar characteristic information set.

[0098] (Modification of the First Embodiment) In the first embodiment, the acquisition failure information may be configured to be set for each acquisition condition that was not met.

[0099] In the first embodiment, the acquisition conditions are relaxed, but it is also possible to simply change the acquisition conditions. That is, even if the acquisition conditions are not relaxed, changing the acquisition conditions may make them suitable for the traveling conditions of the vehicle 101, thereby improving the probability that the acquisition conditions will be met. For example, it is also possible to simply change the time period from morning to afternoon. As a result, if the vehicle 101 mainly travels in the afternoon, the probability that the acquisition conditions will be met will improve.

[0100] In the first embodiment, the verification processing unit 11 is provided, but the processing unit 10a may perform some or all of the functions of the verification processing unit 11. Furthermore, if all of the functions of the verification processing unit 11 are performed, the verification processing unit 11 need not be provided. In other words, if the processing unit 10a can run the program to be verified together with the implementation program, the verification processing unit 11 need not be provided.

[0101] 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. However, 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.

[0102] 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.

[0103] The collection unit 51 in the first embodiment classifies the acquisition failure information based on the characteristic information. As a modification of this, the collection unit 51 may classify the acquisition failure information into groups based on the characteristic information, and then further classify the acquisition failure information into small groups for each unsatisfied acquisition condition. Specifically, when transmitting the acquisition failure information, the transmission unit 17 of the vehicle control device 10 also transmits information about the unsatisfied acquisition condition. When storing the acquisition failure information, the collection unit 51 also stores which of the acquisition conditions is unsatisfied.

[0104] In this case, the collection unit 51 first classifies the acquisition failure information into several large groups based on the characteristic information, and then further classifies the acquisition failure information into small groups for each unsatisfied acquisition condition based on information about the unsatisfied acquisition condition associated with the acquisition failure information. For example, as shown in Figure 7, the collection unit 51 classifies the characteristic information T1 to T10 into a first group (large group), and then classifies the acquisition failure information 1 to 3 into small groups within the first group for each unsatisfied acquisition condition.

[0105] Then, for each predetermined period, if the number of pieces of acquisition failure information in any small group is equal to or greater than a threshold, the acquisition condition change unit 52 identifies the unsatisfied acquisition condition associated with the small group, and further identifies characteristic information to be classified into a large group that aggregates the small group. Referring to Figure 7, if the number of pieces of acquisition failure information 1 to 3 associated with a first acquisition condition is equal to or greater than a threshold, characteristic information T1 that aggregates the first acquisition condition is identified.

[0106] Then, the acquisition condition changing unit 52 determines to change the specified acquisition condition (first acquisition condition in FIG. 7 ) in the vehicle 101 in which the specified characteristic information (characteristic information T1 in FIG. 7 ) is set, and the instructing unit 53 instructs each vehicle 101 to do so. When the characteristic information set in step S101 is the same as the instructed characteristic information (characteristic information T1 in FIG. 7 ), the acquisition condition changing unit 52 relaxes the instructed acquisition condition (first acquisition condition in FIG. 7 ) among the multiple acquisition conditions.

[0107] As a result, even if only some of the acquisition conditions are difficult to satisfy due to the driving conditions of the vehicle 101, the acquisition conditions can be changed and appropriately satisfied by instructions from the server 102. On the other hand, other acquisition conditions for which the number of acquisition failure information pieces is less than the threshold value are determined to be appropriately set and are not changed. This makes it possible to prevent other acquisition conditions for which the number of acquisition failure information pieces is less than the threshold value from being excessively likely to be satisfied.

[0108] Second Embodiment A second embodiment will be described in which the configuration of the data collection system 100 of the first embodiment is partially modified. In the second embodiment, whether or not to change the acquisition conditions is determined based on the quantity of data collected by the server 102. This will be described in detail below.

[0109] When storing data, the collection unit 51 of the second embodiment sorts the data into one or more groups based on the characteristic information and stores the data in the storage 102b. For example, if there are only a few types (patterns) of characteristic information, the collection unit 51 groups the data by each type of characteristic information. On the other hand, if there are many types (patterns) of characteristic information, the collection unit 51 performs clustering based on the similarity of the characteristic information and classifies the data into groups (clusters).

[0110] In other words, one or more pieces of characteristic information are classified into one group (cluster), and the data associated with the pieces of characteristic information are also classified into the group. In other words, the data structure in FIG. 6 is the same as that in FIG. 6, except that the acquisition failure information is replaced with data.

[0111] The acquisition condition change unit 52 then determines, for each predetermined period, whether the quantity of data classified into any of the groups is within an appropriate range. Specifically, the acquisition condition change unit 52 tallies the number of stored data items for each group for the data tallied during the predetermined period. The acquisition condition change unit 52 then determines whether the number of stored data items in the group is within a predetermined appropriate range, thereby determining whether the quantity of data items is within the appropriate range. The upper and lower limits of the appropriate range can be set arbitrarily.

[0112] If there is a group in which the quantity of data is outside the appropriate range, the acquisition condition change unit 52 identifies the characteristic information classified into that group. In other words, the acquisition condition change unit 52 identifies the characteristic information associated with the data sorted into that group.

[0113] The acquisition condition change unit 52 then determines to change the acquisition conditions for the vehicle 101 in which the specified characteristic information is set. At that time, if the quantity of data is below the lower limit, the acquisition condition change unit 52 determines to relax the acquisition conditions so that the quantity of data increases. On the other hand, if the quantity of data is above the upper limit, the acquisition condition change unit 52 determines to tighten the acquisition conditions so that the quantity of data decreases. The instruction unit 53 issues instructions regarding the contents of the determination made by the acquisition condition change unit 52 to each vehicle 101 via the communication network 103.

[0114] When each vehicle 101 receives an instruction from the instruction unit 53, the instruction is temporarily stored in the storage unit 10b of the vehicle control device 10. Then, if an instruction from the instruction unit 53 is stored in step S102 of the data acquisition process, the acquisition condition change unit 52 changes the acquisition conditions in accordance with the instruction.

[0115] For example, if the specified characteristic information was set in step S101 and an instruction to relax the acquisition conditions was given, the acquisition conditions are relaxed in the same manner as in the first embodiment. On the other hand, if the specified characteristic information was set in step S101 and an instruction to strengthen the acquisition conditions was given, the acquisition conditions are strengthened. Strengthening of the acquisition conditions can be performed in the opposite manner to relaxing them, and therefore detailed description thereof will be omitted.

[0116] According to the second embodiment, the following effects are achieved.

[0117] When storing data, the collection unit 51 of the server 102 classifies the data associated with the characteristic information based on the characteristic information and sorts it into one or more groups. Then, if the quantity of data classified into any group for each predetermined period is outside the appropriate range, the acquisition condition change unit 52 identifies the characteristic information classified into that group. Then, the acquisition condition change unit 52 determines to change the acquisition conditions for the vehicles 101 for which the identified characteristic information is set, and the instruction unit 53 instructs each vehicle 101 to do so.

[0118] As a result, even if acquisition conditions that do not appropriately correspond to the driving conditions of the vehicle 101 are set, the acquisition conditions are changed according to the characteristic information in response to an instruction from the server 102. Therefore, the acquisition conditions are changed to appropriate acquisition conditions according to the characteristic information, and data can be collected efficiently.

[0119] The server 102 determines whether or not to change the acquisition conditions based on data collected from a plurality of vehicles 101 via the communication network 103. Therefore, the acquisition conditions can be changed based on overall trends, not depending on the special circumstances of only some of the vehicles 101.

[0120] The data is sorted into several groups based on the characteristic information. Therefore, even if the types of characteristic information (such as the number and types of parameters, the type of scene to be acquired, etc.) are set in detail, it is possible to issue a change instruction to vehicles 101 that are sorted into the same group and have similar characteristic information set.

[0121] The instruction unit 53 instructs the user to relax the acquisition conditions to increase the amount of data when the amount of data is equal to or less than a predetermined lower limit, and instructs the user to tighten the acquisition conditions to reduce the amount of data when the amount of data is equal to or greater than a predetermined upper limit, thereby making it possible to bring the amount of data closer to an appropriate range.

[0122] (Variation of the Second Embodiment) In the above embodiment, the collection unit 51 classifies the data based on the characteristic information. As a variation of this, the collection unit 51 may group the data based on the characteristic information, and then further classify the data into small groups according to the acquisition conditions that are met. Specifically, the transmission unit 17 of the vehicle control device 10 also transmits information about the met conditions associated with the data, and when storing the data, the collection unit 51 stores the data in association with the information about the met conditions received together with the data.

[0123] In this case, the collection unit 51 first classifies the data into several large groups based on the characteristic information, and then further classifies the data into small groups for each satisfied condition (satisfied acquisition condition) based on information about the satisfied conditions associated with the data. For example, as shown in Figure 8, the collection unit 51 classifies the characteristic information T1 to T10 into a first group (large group), and then classifies the data D1 to D3 into small groups within the first group for each satisfied condition.

[0124] If the quantity of data in any small group is outside the appropriate range for each predetermined period, the acquisition condition change unit 52 identifies the acquisition condition associated with that small group and further identifies characteristic information to be classified into a large group that aggregates that small group. Referring to Figure 8, if the quantity of data D1 to D3 associated with a first acquisition condition is outside the appropriate range, characteristic information T1 that aggregates the first acquisition condition is identified.

[0125] Then, the acquisition condition change unit 52 determines to change the specified acquisition condition (first acquisition condition in FIG. 8 ) for the vehicle 101 in which the specified characteristic information (characteristic information T1 in FIG. 8 ) is set. At this time, if the quantity of data is below the lower limit, the acquisition condition change unit 52 determines to relax the specified acquisition condition so that the quantity of data increases. On the other hand, if the quantity of data is above the upper limit, the acquisition condition change unit 52 determines to strengthen the specified acquisition condition so that the quantity of data decreases. Then, the instruction unit 53 instructs each vehicle 101 on the determined matters.

[0126] If the characteristic information set in step S101 is the same as the specified characteristic information (characteristic information T1 in Figure 8), the acquisition condition change unit 52 changes the specified acquisition condition (the first acquisition condition in Figure 8) among the multiple acquisition conditions in accordance with the instruction.

[0127] As a result, even if some of the acquisition conditions are difficult to satisfy (or too easily satisfied) due to the driving conditions of the vehicle 101, the acquisition conditions can be changed and appropriately satisfied by instructions from the server 102. On the other hand, the other acquisition conditions that are appropriately satisfied are not changed.

[0128] In the second embodiment, the acquisition failure information does not need to be stored or transmitted, and the server 102 does not need to collect or tally the acquisition failure information.

[0129] 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.

[0130] The following describes technical ideas that can be derived from the above-described embodiment and modifications.

[0131] [Configuration 1] A data collection device (102) that collects data from a plurality of vehicles (101) via a communication network (103) includes: a collection unit (51) that receives acquisition failure information indicating that a data acquisition condition has not been met and characteristic information of the vehicle that transmitted the acquisition failure information, and stores and collects the acquisition failure information in a storage device (102b) in association with the characteristic information; an acquisition condition change unit (52) that decides whether to change the acquisition conditions; and an instruction unit (53) that, when the acquisition condition change unit has decided to change the acquisition conditions, issues an instruction to the plurality of vehicles via the communication network to that effect; when storing the acquisition failure information, the collection unit classifies the acquisition failure information associated with the characteristic information based on the characteristic information and sorts it into one or more groups; and when the number of acquisition failure information pieces collected in any of the groups during a predetermined period is equal to or greater than a threshold, the acquisition condition change unit decides to change the acquisition conditions. The instruction unit identifies characteristic information associated with the acquisition failure information sorted into a group in which the number of acquisition failure information pieces is equal to or greater than a threshold, and instructs the vehicle in which the identified characteristic information is set to change the acquisition conditions.

[0132] [Configuration 2] A data collection device (102) that collects data from a plurality of vehicles (101) via a communication network (103) includes: a collection unit (51) that receives data acquired when a data acquisition condition is met and characteristic information of the vehicle that transmitted the data, and stores and collects the data in a storage device (102b) in association with the characteristic information; an acquisition condition change unit (52) that decides whether to change the acquisition conditions; and an instruction unit (53) that, when the acquisition condition change unit decides to change the acquisition conditions, issues an instruction to the plurality of vehicles via the communication network to that effect; when storing the data, the collection unit classifies the data associated with the characteristic information based on the characteristic information and sorts it into one or more groups; and when the amount of data collected in any of the groups in a predetermined period is outside an appropriate range, the acquisition condition change unit decides to change the acquisition conditions. The instruction unit identifies characteristic information associated with data sorted into a group in which the quantity of data is outside the appropriate range, and instructs the vehicle in which the identified characteristic information is set to change the acquisition conditions.

[0133] [Configuration 3] The data collection device according to Configuration 2, wherein the instruction unit instructs the relaxation of the acquisition conditions to increase the quantity of data when the quantity of data is equal to or less than a predetermined lower limit, and instructs the tightening of the acquisition conditions to reduce the quantity of data when the quantity of data is equal to or greater than a predetermined upper limit.

[0134] [Configuration 4] A data collection program executed by a data collection device (102) that collects data from a plurality of vehicles (101) via a communication network (103), causes the data collection device to perform a collection step of receiving acquisition failure information indicating that a data acquisition condition was not met and characteristic information of the vehicle that transmitted the acquisition failure information, and storing and collecting the acquisition failure information in a storage device (102b) in association with the characteristic information; an acquisition condition change step of deciding whether to change the acquisition conditions; and an instruction step of instructing the plurality of vehicles to change the acquisition conditions via the communication network when a change of the acquisition conditions is decided by the acquisition condition change step, wherein in the collection step, when storing the acquisition failure information, the acquisition failure information associated with the characteristic information is classified and sorted into one or more groups based on the characteristic information, and in the acquisition condition change step, when the number of acquisition failure information collected in any of the groups in a predetermined period is equal to or greater than a threshold, it is decided to change the acquisition conditions, In the instruction step, the data collection program identifies characteristic information associated with the acquisition failure information sorted into a group in which the number of acquisition failure information pieces is equal to or greater than a threshold, and instructs the vehicle in which the identified characteristic information is set to change the acquisition conditions.

[0135] [Configuration 5] A data collection program executed by a data collection device (102) that collects data from a plurality of vehicles (101) via a communication network (103), the program instructing the data collection device to perform: a collection step of receiving data acquired when a data acquisition condition is met and characteristic information of the vehicle that transmitted the data, and storing and collecting the data in a storage device (102b) in association with the characteristic information; an acquisition condition change step of deciding whether to change the acquisition conditions; and an instruction step of instructing the plurality of vehicles to change the acquisition conditions via the communication network when a change in the acquisition conditions is decided by the acquisition condition change step; wherein, in the collection step, when storing the data, the data associated with the characteristic information is classified based on the characteristic information and sorted into one or more groups; and, in the acquisition condition change step, when the amount of data collected in any of the groups in a predetermined period is outside an appropriate range, it is decided to change the acquisition conditions. In the instruction step, a data collection program identifies characteristic information associated with data sorted into a group in which the quantity of data is outside the appropriate range, and instructs the vehicle in which the identified characteristic information is set to change the acquisition conditions.

[0136] 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 data collection device (102) that collects data from a plurality of vehicles (101) via a communication network (103), comprising: a collection unit (51) that receives acquisition failure information indicating that a data acquisition condition has not been met and characteristic information of the vehicle that transmitted the acquisition failure information, and stores and collects the acquisition failure information in a storage device (102b) in association with the characteristic information; an acquisition condition change unit (52) that decides whether to change the acquisition conditions; and an instruction unit (53) that, when the acquisition condition change unit has decided to change the acquisition conditions, issues an instruction to the plurality of vehicles via the communication network; when storing the acquisition failure information, the collection unit classifies the acquisition failure information associated with the characteristic information based on the characteristic information and sorts it into one or more groups; and when the number of acquisition failure information pieces collected in any of the groups during a predetermined period is equal to or greater than a threshold, the acquisition condition change unit decides to change the acquisition conditions. The instruction unit identifies characteristic information associated with the acquisition failure information sorted into a group in which the number of acquisition failure information pieces is equal to or greater than a threshold, and instructs the vehicle in which the identified characteristic information is set to change the acquisition conditions.

2. A data collection device (102) that collects data from a plurality of vehicles (101) via a communication network (103), comprising: a collection unit (51) that receives data acquired when a data acquisition condition is met and characteristic information of the vehicle that transmitted the data, and stores and collects the data in a storage device (102b) in association with the characteristic information; an acquisition condition change unit (52) that decides whether to change the acquisition conditions; and an instruction unit (53) that, when the acquisition condition change unit decides to change the acquisition conditions, issues an instruction to the plurality of vehicles via the communication network; when storing the data, the collection unit classifies the data associated with the characteristic information based on the characteristic information and sorts it into one or more groups; and when the amount of data collected in any of the groups during a predetermined period is outside an appropriate range, the acquisition condition change unit decides to change the acquisition conditions. The instruction unit identifies characteristic information associated with data sorted into a group in which the quantity of data is outside the appropriate range, and instructs the vehicle in which the identified characteristic information is set to change the acquisition conditions.

3. The data collection device of claim 2, wherein the instruction unit instructs the relaxation of the acquisition conditions to increase the quantity of data when the quantity of data is below a predetermined lower limit, and instructs the tightening of the acquisition conditions to reduce the quantity of data when the quantity of data is above a predetermined upper limit.

4. A data collection program executed by a data collection device (102) that collects data from a plurality of vehicles (101) via a communication network (103), the program causing the data collection device to perform the following steps: a collection step of receiving acquisition failure information indicating that a data acquisition condition was not met and characteristic information of the vehicle that transmitted the acquisition failure information, and storing and collecting the acquisition failure information in a storage device (102b) in association with the characteristic information; an acquisition condition change step of determining whether or not to change the acquisition conditions; and an instruction step of instructing the plurality of vehicles to change the acquisition conditions via the communication network when a change in the acquisition conditions is decided by the acquisition condition change step; wherein in the collection step, when storing the acquisition failure information, the acquisition failure information associated with the characteristic information is classified and sorted into one or more groups based on the characteristic information; and in the acquisition condition change step, when the number of acquisition failure information collected in any of the groups in a predetermined period is equal to or greater than a threshold, it is decided to change the acquisition conditions. In the instruction step, the data collection program identifies characteristic information associated with the acquisition failure information sorted into a group in which the number of acquisition failure information pieces is equal to or greater than a threshold, and instructs the vehicle in which the identified characteristic information is set to change the acquisition conditions.

5. A data collection program executed by a data collection device (102) that collects data from a plurality of vehicles (101) via a communication network (103), the program causing the data collection device to perform the following steps: a collection step of receiving data acquired when a data acquisition condition is met and characteristic information of the vehicle that transmitted the data, and storing and collecting the data in a storage device (102b) in association with the characteristic information; an acquisition condition change step of determining whether or not to change the acquisition conditions; and an instruction step of instructing the plurality of vehicles via the communication network to change the acquisition conditions if a change in the acquisition conditions is decided by the acquisition condition change step; wherein in the collection step, when storing the data, the data associated with the characteristic information is classified based on the characteristic information and sorted into one or more groups; and in the acquisition condition change step, when the amount of data collected in any of the groups in a predetermined period is outside an appropriate range, it is decided to change the acquisition conditions. In the instruction step, a data collection program identifies characteristic information associated with data sorted into a group in which the quantity of data is outside the appropriate range, and instructs the vehicle in which the identified characteristic information is set to change the acquisition conditions.

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