Data collection system, data collection server, and data collection method

Abstract

This data collection system comprises a data storage device and a data collection server, and has: a data reception unit that receives, from one or more vehicles, position data of the vehicles; a collection target range decision unit that decides a collection target range that is a range in which travel data is collected from the vehicles; a travel risk level determination unit that determines a travel risk level in the collection target range; a collection data decision unit that decides at least one of the type, the data amount, and the collection cycle of the travel data to be collected from one or more vehicles included in the collection target range; and a collection data request unit that requests, to the one or more vehicles, the travel data decided by the collection data decision unit.

Description

Data collection system, data collection server, and data collection method

[0001] The present invention relates to a data collection system that collects driving data from a vehicle.

[0002] 2. Description of the Related Art There is a data collection system that collects driving data obtained while a vehicle is traveling from the vehicle.

[0003] Background art in this field is disclosed in Patent Document 1 (JP 2020-140657 A). Patent Document 1 describes a vehicle data collection system for collecting vehicle data related to a vehicle situation when the vehicle is in a predetermined vehicle situation, the vehicle data collection system including a condition setting unit that sets desired collection conditions for the vehicle data for each of the vehicles based on a vehicle state indicated by some data included in the vehicle data, and a control unit that controls each of the vehicles and parts of the vehicle data collection system that at least partially handle the process from generation to collection of the vehicle data so that the vehicle data is collected from each of the vehicles under the desired collection conditions set for each of the vehicles.

[0004] JP 2020-140657 A

[0005] The system described in Patent Document 1, commercially available cloud-based drive recorders, and cloud-based vehicle management systems mainly collect data about the vehicle itself.

[0006] However, vehicle accidents and vehicle troubles can be caused by surrounding vehicles or surrounding conditions, and data from the vehicle itself may not be enough to understand the circumstances of the accident or trouble or to investigate the cause and problem. For this reason, it is necessary to collect data from the vehicle itself and surrounding vehicles.

[0007] Furthermore, constantly collecting data from the vehicle itself and surrounding vehicles will result in a huge amount of data, and if the amount of data exceeds the capacity of the communication path, data loss or communication failure will occur, making it difficult to collect data appropriately.

[0008] A representative example of the invention disclosed in this application is as follows. That is, the data collection system comprises: a data storage device mounted on a vehicle and storing driving data obtained by driving the vehicle; and a data collection server that collects the driving data from the vehicle, wherein the data collection server is configured by a computer having an arithmetic unit that executes predetermined arithmetic processing and a storage device connected to the arithmetic unit, and comprises: a data receiving unit that receives vehicle position data from one or more vehicles; a collection target range determination unit that determines a collection target range within which the driving data will be collected from the vehicle based on the received position data; a driving risk determination unit that determines a driving risk level of the collection target range based on the position data received from one or more vehicles included in the collection target range; a collection data determination unit that determines at least one of the type, amount, and collection period of the driving data to be collected from one or more vehicles included in the collection target range based on the determined driving risk level; and a collection data request unit that requests the one or more vehicles to collect the driving data determined by the collection data determination unit, and wherein the data receiving unit receives the driving data determined by the collection data determination unit from the one or more vehicles.

[0009] According to one aspect of the present invention, it is possible to collect an appropriate amount of vehicle data depending on the situation. Objects, configurations, and effects other than those described above will become apparent from the following description of the embodiments.

[0010] 1 is a diagram illustrating an example of the configuration of a data collection system according to a first embodiment; FIG. 2 is a diagram illustrating the operation of a collection target range determination unit according to the first embodiment; FIG. 3 is a diagram illustrating a first setting example of a collection target range according to the first embodiment; FIG. 4 is a diagram illustrating a second setting example of a collection target range according to the first embodiment; FIG. 5 is a diagram illustrating a third setting example of a collection target range according to the first embodiment; FIG. 6 is a diagram illustrating an example of vehicle density when there are few surrounding vehicles in the first embodiment; FIG. 7 is a diagram illustrating an example of vehicle density when there are many surrounding vehicles in the first embodiment; FIG. 8 is a diagram illustrating an example of sudden steering according to the first embodiment; FIG. 9 is a diagram illustrating an example of sudden steering according to the first embodiment; FIG. 10 is a diagram illustrating an example of a sudden approach of a rear vehicle according to the first embodiment; FIG. 11 is a diagram illustrating an example of a sudden approach of a rear vehicle according to the first embodiment; FIG. 12 is a diagram illustrating an example of high-speed driving of surrounding vehicles according to the first embodiment; FIG. 13 is a diagram illustrating an example of setting a danger area in a location where traffic accidents frequently occur according to the first embodiment; FIG. 14 is a diagram illustrating an example of a host vehicle approaching a danger area in a location where traffic accidents frequently occur according to the first embodiment; FIG. 15 is a diagram illustrating an example of setting a danger area in a location where an accident has occurred according to the first embodiment; FIG. 16 is a diagram illustrating an example of a host vehicle approaching a danger area in a location where an accident has occurred according to the first embodiment; FIG. 10 is a diagram illustrating an example of the configuration of a data collection system according to a second embodiment.

[0011] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0012] <First Embodiment> Fig. 1 is a diagram showing an example of the configuration of a data collection system according to a first embodiment of the present invention. The data collection system according to this embodiment includes a data collection server 100 that collects vehicle data transmitted from the vehicle 200, and the vehicle 200 having a data storage device 280 that stores vehicle data obtained during driving. The vehicle 200 includes the vehicle itself and surrounding vehicles that are within a predetermined distance range (collection target range) from the vehicle itself, and the data collection server 100 collects vehicle data from the surrounding vehicles as well as the vehicle itself. The vehicle data is used to understand the situation in the event of a vehicle accident or vehicle trouble, and to investigate the cause or problem.

[0013] In addition, in an embodiment of the present invention, the amount of data collected is controlled. The driving risk level is determined based on the driving conditions, vehicle behavior, and driving location of the vehicle itself and surrounding vehicles within the collection range. When the driving risk level is low, the amount of data collected is reduced, and when the driving risk level is high, the amount of data collected is increased, thereby suppressing the occurrence of data loss and communication failures and appropriately collecting data to understand the situation of accidents and troubles and to investigate the causes and problems.

[0014] The data collection server 100 includes a data receiving unit 110 that receives data transmitted from the vehicle 200, a data storage device 120 on the data collection server 100 side that stores the data received by the data receiving unit 110, a collection target range determination unit 150 that determines a collection target range based on the data received by the data receiving unit 110 and map data 170, a driving risk determination unit 160 that reads data of vehicles included in the collection target range determined by the collection target range determination unit 150 from the data storage device 120 with reference to the map data 170 and determines a driving risk using a neural network, a collection data determination unit 140 that determines data to be collected based on the determination result of the driving risk determination unit 160, and a collection data request unit 130 that requests the determined collection target data from the vehicle 200. The data collection server 100 is preferably constructed on a cloud, but may also be constructed on-premise.

[0015] The data collection server 100 is configured by a computer having a processor (CPU), a memory, an auxiliary storage device, and a communication interface. The data collection server 100 may have an input interface and an output interface.

[0016] The processor is a computing device that executes programs stored in memory. The processor executes various programs to realize the functions of each functional unit of the data collection server 100 (e.g., the data receiving unit 110, the data storage device 120, the collected data request unit 130, the collected data determination unit 140, the collection target range determination unit 150, and the driving danger assessment unit 160). Note that some of the processing performed by the processor by executing the programs may be executed by another computing device (e.g., hardware such as an ASIC or FPGA).

[0017] The memory includes ROM, which is a non-volatile storage element, and RAM, which is a volatile storage element. ROM stores unchanging programs (e.g., BIOS), etc. RAM is a high-speed, volatile storage element such as DRAM (Dynamic Random Access Memory), and temporarily stores programs executed by the processor and data used during program execution.

[0018] The auxiliary storage device is, for example, a large-capacity, non-volatile storage device such as a magnetic storage device (HDD) or flash memory (SSD). The auxiliary storage device also stores data used by the processor when executing a program and the program executed by the processor. In other words, the program is read from the auxiliary storage device, loaded into memory, and executed by the processor to realize each function of the data collection server 100.

[0019] The communication interface is a network interface device that controls communication with other devices according to a predetermined protocol.

[0020] The input interface is an interface to which input devices such as a keyboard and a mouse are connected and which receives input from an operator. The output interface is an interface to which output devices such as a display device and a printer (not shown) are connected and which outputs the results of program execution in a format that can be viewed by the operator. Note that a terminal connected via a network may provide the input interface and the output interface.

[0021] The programs executed by the processor are provided to the data collection server 100 from removable media (such as CD-ROMs or flash memory) or via a network, and are stored in a non-volatile auxiliary storage device, which is a non-transitory storage medium. For this reason, the data collection server 100 should preferably have an interface for reading data from removable media.

[0022] The data collection server 100 is a computer system configured on a single physical computer or on multiple logically or physically configured computers, and may operate on a virtual computer constructed on multiple physical computer resources. For example, the data receiving unit 110, the data storage device 120, the collection data request unit 130, the collection data determination unit 140, the collection target range determination unit 150, and the driving risk assessment unit 160 may each operate on separate physical or logical computers, or multiple units may be combined to operate on a single physical or logical computer.

[0023] Vehicle 200 has a camera 210 that takes pictures of the area around the vehicle, a GNSS receiving unit 220 that identifies the position of the vehicle, a vehicle speed acquiring unit 230 that collects speed, which is vehicle data, a steering angle acquiring unit 240 that collects steering angle, which is vehicle data, a vehicle weight acquiring unit 250 that collects weight related to the axles, which is vehicle data, a brake state acquiring unit 260 that collects current speed due to braking, which is vehicle data, a recognition processing unit 270 that recognizes the image captured by camera 210, a vehicle-side data storage device 280 that stores various data (e.g., position data acquired by GNSS receiving unit 220, and vehicle data collected by vehicle speed acquiring unit 230, steering angle acquiring unit 240, vehicle weight acquiring unit 250, and brake state acquiring unit 260), and a communication processing unit 290 that transmits the data stored in data storage device 280 to data collection server 100 and receives requests from data collection server 100.

[0024] The data collection server 100 grasps the situation when a vehicle accident or vehicle trouble occurs according to the driving risk level, selects effective data (position, vehicle speed, steering angle, vehicle weight, braking state, camera footage, recognition results) to investigate the cause or problem, and collects the selected data from the vehicle 200 or vehicles around the vehicle 200.

[0025] The collection target range determination unit 150 of the data collection server 100 determines the collection target range based on the data received from the vehicle 200 and the map data 170 .

[0026] FIG. 2 is a diagram illustrating the operation of the collection target range determination unit 150 according to the first embodiment.

[0027] The collection target range determination unit 150 obtains a travel distance 320 from the position collected from the vehicle 310 and a position 311 collected from the vehicle after movement, and calculates a stopping distance 321 when braking suddenly. A region having a radius of a distance 322 obtained by multiplying this stopping distance 321 by a predetermined coefficient K (for example, 2) is determined as the collection target range 300. The collection target range can be calculated using the following formula: Travel speed (m / h) = travel distance per second (m) × 3600 seconds Stopping distance when braking suddenly (m) = travel distance per second (m) + (travel speed (m / h) squared ÷ (254 × friction coefficient determined from weather information, etc.)) Radius of collection target range (m) = stopping distance when braking suddenly (m) × K

[0028] The collection target range 300 may be defined as the portion of the road on which the vehicle is traveling, obtained from the map data 170. Furthermore, a vehicle at least partially included in the collection target range 300 is defined as a nearby vehicle. Furthermore, the collection target range 300 may be changed depending on the traveling conditions of the vehicle.

[0029] By determining the collection target range 300 from the travel speed, vehicle data can be collected from vehicles within a stopping distance that takes into account the safety factor (coefficient K).

[0030] When the host vehicle 310 is accelerating, the collection target range 300 may be set to a range that is wide in front and narrow in rear (for example, a front-to-rear ratio of 3:1) rather than a range centered on the host vehicle, as shown in FIG. 3. When the host vehicle 310 is decelerating, the collection target range 300 may be set to a range that is wide in rear and narrow in front (for example, a front-to-rear ratio of 1:3) rather than a range centered on the host vehicle, as shown in FIG. 4. In other words, the front-to-rear ratio of the collection target range may be changed within a range of 3:1 to 1:3 depending on the acceleration and deceleration of the host vehicle. An appropriate rear-end collision risk can be set based on the acceleration and deceleration of the host vehicle 310.

[0031] When the vehicle 310 is traveling near an intersection, it is advisable to define the roads on the left and right sides of the intersection obtained from the map data 170 as part of the collection target range 300, as shown in Fig. 5. This allows surrounding vehicles 400 on the left and right sides of the intersection to be included in the collection target.

[0032] The driving danger level determination unit 160 has a vehicle density determination unit 161, a vehicle behavior change determination unit 162, and a driving location danger level determination unit 163, and determines the driving danger level from the determination results of each unit 161 to 163.

[0033] The vehicle density determination unit 161 determines the risk level by assigning a score based on the number of surrounding vehicles 400 present in the collection target range 300 of the host vehicle 310. For example, the vehicle density determination unit 161 determines that the vehicle density is low when the number of surrounding vehicles 400 present in the collection target range 300 of the host vehicle 310 is less than a predetermined threshold, as shown in FIG. 6 , and determines that the vehicle density is high when the number of surrounding vehicles 400 present in the collection target range 300 of the host vehicle 310 is more than a predetermined threshold, as shown in FIG. 7 . For example, using Table 1, vehicle density can be determined and scored on a five-level scale using four thresholds. Furthermore, weighting may be assigned to each region into which the collection target range 300 is divided. For example, a large weight may be assigned to the region ahead of the host vehicle, and a small weight may be assigned to the region behind the host vehicle. Alternatively, a large weight may be assigned to the lane in which the host vehicle is traveling, and a small weight may be assigned to a lane different from the lane in which the host vehicle is traveling. Alternatively, the vehicle density may be determined by comparing the number of vehicles per unit area with a predetermined threshold. The vehicle density determination unit 161 may be configured as a neural network that is trained using training data that associates vehicle density with the degree of risk.

[0034]

[0035] The vehicle behavior change determination unit 162 detects a sudden change in the vehicle's behavior and determines the degree of danger. For example, the vehicle behavior change determination unit 162 determines a change in the lateral position of the host vehicle over a short period of time, such as a few seconds, when the host vehicle 310 shown in Fig. 8 moves from pre-movement position 312 to position 313 shown in Fig. 9, and then moves from position 313 to position 314 shown in Fig. 10, as a sudden change in vehicle behavior (steering change). For example, it is preferable to determine a sudden change in vehicle behavior when the change in steering angle per unit time exceeds a predetermined threshold.

[0036] The vehicle behavior change determination unit 162 determines a sudden change in vehicle behavior (sudden approach) when the surrounding vehicle 400 shown in FIG. 11 changes its position from the pre-movement position 401 shown in FIG. 12 to the surrounding vehicle 400, when a sudden approach occurs in which a surrounding vehicle ahead of the host vehicle decelerates, or when a surrounding vehicle on the side of the host vehicle cuts into the host vehicle's traveling path. The acceleration and deceleration of the host vehicle and other vehicles can be acquired from the vehicle's electronic control unit for cruise control via the data collection server 100 or through vehicle-to-vehicle communication. A sudden approach may also be determined when the change in the inter-vehicle distance with respect to the rear vehicle over time is greater than a predetermined threshold. Furthermore, when the host vehicle is stopped, it may also be determined that the following vehicle is rapidly approaching. Furthermore, a sudden approach may also be determined when the braking distance calculated from the speed of the following vehicle exceeds the inter-vehicle distance.

[0037] Furthermore, the vehicle behavior change determination unit 162 determines that a sudden change in vehicle behavior (high-speed driving of a nearby vehicle) occurs when a nearby vehicle 400 shown in FIG. 13 changes from its pre-movement position 401 to position 402 shown in FIG. 14 in a short period of time. For example, by using Table 2, scores can be assigned to the determination items (sudden steering, sudden speed change, sudden approach, high-speed driving). When multiple determination items apply, the scores of the corresponding determination items can be added together. The vehicle behavior change determination unit 162 may be configured as a neural network trained using training data that associates vehicle behavior changes (e.g., sudden steering, sudden speed change, sudden approach, high-speed driving) with risk levels.

[0038]

[0039] The traveling location risk determination unit 163 determines whether the collection target range of the host vehicle overlaps with a defined risk area in the map data 170, which is a location where traffic accidents frequently occur, a location where an accident has occurred at the current time, or a location where traffic restrictions are in place due to road construction or the like. For example, when traffic accidents frequently occur at the intersection shown in FIG. 15 , the traveling location risk determination unit 163 determines that the collection target range 300 of the host vehicle 310 overlaps with the risk area 500 defined at the intersection in the state shown in FIG. 16 , and the host vehicle 310 is located in the risk area 500. FIG. 17 shows the risk area 500 of the traffic accident vehicle 402. In the state shown in FIG. 18 , the collection target range 300 of the host vehicle 310 overlaps with the risk area 500, and the host vehicle 310 is located in the risk area 500. For example, using Table 3, a score can be assigned when the collection target range 300 of the host vehicle 310 overlaps with a defined risk area. The driving location danger level determination unit 163 may be configured as a neural network that is trained using training data that associates driving locations with danger levels.

[0040]

[0041] The driving danger level determination unit 160 determines the driving danger level of the subject vehicle and surrounding vehicles by adding up the scores of the determination results of the vehicle density determination unit 161, the vehicle behavior change determination unit 162, and the driving location danger level determination unit 163. The driving danger level determination unit 160 may also determine the driving danger level by weighting each determination and adding up the scores. For example, the driving danger level can be determined using Table 4.

[0042]

[0043] The collection target range may be classified by priority. FIG. 19 shows the priority within the collection target range, with a range 600 close to the host vehicle 310 being assigned a high priority and a range 601 far from the host vehicle 310 (i.e., a range 601 outside the high priority range 600) being assigned a low priority. The driving danger level determination unit 160 assigns a high priority to nearby vehicles within the high priority collection target range 600 and a low priority to nearby vehicles within the low priority collection target range 600. For example, Table 5 can be used to assign priorities to the collection target range. Note that priorities may not be assigned to the ranges, but each nearby vehicle may be assigned a priority. Furthermore, the risk level may be determined based on the relative speed with respect to the host vehicle, rather than the distance from the host vehicle.

[0044]

[0045] The collection data determination unit 140 changes the data to be collected depending on the relationship between the priority of the surrounding vehicle and the driving risk level. For example, the type of data defined in Table 4 is collected depending on the driving risk level. The data collection interval may also be changed depending on the request timing coefficient defined in Table 4. In this way, the amount of data collected per unit time can be changed by changing the type of data and the data collection timing. Furthermore, the vehicle 200 may be notified of the data transmission interval and the risk level.

[0046] When the priority of the nearby vehicle is low, the collected data determination unit 140 collects data of a driving risk level that is one level higher than the driving risk level determined by the driving risk level determination unit 160. When the priority of the nearby vehicle is high, the collected data determination unit 140 collects data according to the driving risk level determined by the driving risk level determination unit 160. The number of nearby vehicles that can exist in the high priority range in which a large amount of data is collected is limited to about 2 to 4 vehicles that can exist in adjacent lanes, and the number of nearby vehicles that can exist within a distance in front of and behind the host vehicle according to the vehicle speed is limited to about 2 to 4 vehicles, so that an increase in the amount of data collected from nearby vehicles can be suppressed.

[0047] The collected data requesting unit 130 requests the data to be collected, which has been determined by the collected data determining unit 140, from the vehicles 200 in the vicinity of the subject vehicle at a predetermined timing (for example, every second).

[0048] The vehicle 200 stores in the data storage device 280 all of the data to be collected determined by the collection data determination unit 140 of the data collection server 100, including position data, camera images, vehicle speed, steering angle, vehicle weight, braking state, and object detection results (type, distance from the vehicle).

[0049] The communication processing unit 290 of the vehicle 200 receives a request from the collected data request unit 130 of the data collection server 100 and transmits the requested collection target data to the data collection server 100 .

[0050] As described above, according to the data collection system of Example 1 of the present invention, the data to be collected is determined based on the driving risk determined from the vehicle itself, surrounding vehicles within the collection range, and the driving location conditions, so that the amount of data can be appropriately controlled and vehicle data can be collected.

[0051] In a second embodiment, the collection target range determination unit 150 is provided in the vehicle 200, rather than in the data collection server 100. In the second embodiment, differences from the first embodiment will be mainly described, and the same components and processes as those in the first embodiment will be assigned the same reference numerals, and descriptions thereof will be omitted.

[0052] 20 is a diagram showing an example of the configuration of a data collection system according to a second embodiment of the present invention. The data collection system of this embodiment collects vehicle data from the subject vehicle and surrounding vehicles.

[0053] In Example 2, the collection target range determination unit 150 of the vehicle 200 calculates the collection target range using the position data acquired by the GNSS receiving unit 220, the vehicle speed acquired by the vehicle speed acquisition unit 230, and the map data 2A0 acquired from the navigation system, and transmits the calculated collection target range to the data collection server 100.

[0054] If the collection target range is determined by the vehicle 200, the processing load on the data collection server 100 can be reduced, and the collection target range that matches the state of the vehicle at the current time can be calculated.

[0055] The present invention is not limited to the above-described embodiments, and includes various modifications and equivalent configurations within the spirit and scope of the appended claims. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to configurations including all of the described configurations. Furthermore, part of the configuration of one embodiment may be replaced with the configuration of another embodiment. Furthermore, the configuration of another embodiment may be added to the configuration of one embodiment. Furthermore, part of the configuration of each embodiment may be added, deleted, or replaced with other configurations.

[0056] Furthermore, the aforementioned configurations, functions, processing units, processing means, etc. may be realized in part or in whole in hardware, for example by designing them as integrated circuits, or may be realized in software by having a processor interpret and execute a program that realizes each function.

[0057] Information such as programs, tables, and files that realize each function can be stored in a storage device such as a memory, hard disk, or SSD (Solid State Drive), or in a recording medium such as an IC card, SD card, or DVD.

[0058] In addition, the control lines and information lines shown are those that are considered necessary for explanation, and do not necessarily represent all the control lines and information lines that are necessary for implementation. In reality, it can be assumed that almost all components are interconnected.

Claims

1. A data collection system comprising: a data storage device mounted on a vehicle and storing driving data obtained by driving the vehicle; and a data collection server that collects the driving data from the vehicle, wherein the data collection server is configured by a computer having an arithmetic unit that executes predetermined arithmetic processing and a storage device connected to the arithmetic unit, and comprising: a data receiving unit that receives position data of the vehicle from one or more vehicles; a collection target range determination unit that determines a collection target range within which the driving data is to be collected from the vehicle based on the received position data; a driving risk determination unit that determines a driving risk of the collection target range based on the position data received from one or more vehicles included in the collection target range; a collection data determination unit that determines at least one of the type, amount, and collection period of the driving data to be collected from one or more vehicles included in the collection target range in accordance with the determined driving risk; and a collection data request unit that requests the driving data determined by the collection data determination unit from the one or more vehicles, wherein the data receiving unit receives the driving data determined by the collection data determination unit from the one or more vehicles.

2. A data collection system according to claim 1, characterized in that the collection target range determination unit is provided in the data collection server.

3. A data collection system according to claim 1, characterized in that the collection target range determination unit is provided in the vehicle.

4. A data collection system as claimed in claim 1, characterized in that the collection target range determination unit determines the collection target range to be a distance ahead or behind the vehicle in accordance with changes over time in the vehicle position data.

5. A data collection system according to claim 1, characterized in that the driving danger determination unit determines the driving danger based on the density of vehicles within the collection target area.

6. A data collection system according to claim 1, characterized in that the driving danger determination unit determines the driving danger based on the behavior of vehicles within the collection target area.

7. A data collection system according to claim 1, characterized in that the driving danger level determination unit determines the driving danger level based on a danger level set for the point at which the vehicle is traveling.

8. A data collection system as described in claim 1, characterized in that, when the collection target range includes multiple surrounding vehicles, the driving danger assessment unit sets priorities to divided areas within the collection target range or to the surrounding vehicles depending on at least one of the distance and relative speed between the vehicle and the multiple surrounding vehicles, and the collection data determination unit determines the driving data to be collected based on the priorities.

9. A data collection server that collects driving data obtained by driving a vehicle, comprising a computer having an arithmetic device that executes predetermined arithmetic processing and a storage device connected to the arithmetic device, and comprising: a data receiving unit that receives vehicle position data from one or more vehicles; a collection target range determination unit that determines a collection target range within which the driving data is to be collected from the vehicles based on the received position data; a driving risk determination unit that determines a driving risk level of the collection target range based on the position data received from one or more vehicles included in the collection target range; a collection data determination unit that determines at least one of the type, data capacity, and collection period of the driving data to be collected from one or more vehicles included in the collection target range in accordance with the determined driving risk level; and a collection data request unit that requests the driving data determined by the collection data determination unit from the one or more vehicles, wherein the data receiving unit receives the driving data determined by the collection data determination unit from the one or more vehicles.

10. A data collection method in which a data collection system collects driving data obtained by driving a vehicle, the data collection system being configured by a computer having a calculation device that executes predetermined calculation processing and a storage device connected to the calculation device, the data collection method comprising: a data receiving step in which the calculation device receives vehicle position data from one or more vehicles; a collection target range determination step in which the calculation device determines a collection target range within which the driving data is to be collected from the vehicles based on the received position data; a driving risk determination step in which the calculation device determines a driving risk of the collection target range based on the position data received from one or more vehicles included in the collection target range; a collection data determination step in which the calculation device determines at least one of the type, data capacity, and collection period of the driving data to be collected from one or more vehicles included in the collection target range in accordance with the determined driving risk; and a collection data request step in which the calculation device requests the one or more vehicles to collect the driving data determined in the collection data determination step, The data collection method, wherein in the data receiving step, the arithmetic device receives the traveling data determined in the collection data determination step from the one or more vehicles.