Travel data processing system, driving diagnosis system, and data structure

Abstract

This travel data processing system comprises: a travel data acquisition unit that acquires travel data about a travel state of a vehicle traveling on a travel route including a plurality of road links; a detection unit that detects an event related to the vehicle, for each of the road links, on the basis of the travel data; a creation unit that creates event data indicating the detection result of the event for each of the road links; and a travel result acquisition unit that acquires travel result data indicating the travel result of the vehicle on the travel route. The creation unit associates the travel result data with the event data.

Description

Travel Data Processing System, Driving Diagnosis System, and Data Structure

[0001] This disclosure relates to a travel data processing system, a driving diagnosis system, and a data structure. This application claims priority based on Japanese Application No. 2024-163241 filed on September 20, 2024, and incorporates all the descriptions set forth in the above-mentioned Japanese application.

[0002] Conventionally, technologies for evaluating a driver's driving operations using vehicle travel data have been developed. Patent Document 1 (Japanese Unexamined Patent Application Publication No. 2023-181870) discloses the following technology. That is, a driving diagnosis device includes an acquisition unit that acquires travel data indicating the travel state of a vehicle, a driving evaluation unit that evaluates the driving operations of the driver of the vehicle based on the travel data acquired by the acquisition unit, a passenger presence / absence detection unit that detects the presence or absence of passengers in the vehicle, and a notification unit that notifies the driver of the driving evaluation result detected by the driving evaluation unit and changes the notification method of the driving evaluation result based on the detection result of the passenger presence / absence detection unit.

[0003] Japanese Unexamined Patent Application Publication No. 2023-181870 International Publication No. 2015 / 177858 International Publication No. 2019 / 058462 Japanese Unexamined Patent Application Publication No. 2021-33742 Japanese Unexamined Patent Application Publication No. 2016-197308

[0004] The travel data processing system of this disclosure includes a travel data acquisition unit that acquires travel data related to the travel state of a vehicle traveling on a travel route including a plurality of road links, a detection unit that detects an event related to the vehicle for each road link based on the travel data, a creation unit that creates event data indicating the detection result of the event for each road link, and a travel result acquisition unit that acquires travel result data indicating the travel result of the vehicle on the travel route. The creation unit associates the travel result data with the event data.

[0005] One aspect of this disclosure may be implemented not only as a driving data processing system equipped with such characteristic processing, but also as a step-by-step method for such characteristic processing, or as a program for causing a computer to perform such steps. Furthermore, one aspect of this disclosure may be implemented as a semiconductor integrated circuit that implements part or all of the driving data processing system.

[0006] Figure 1 is a diagram showing an example of the configuration of a communication system according to an embodiment of the present disclosure. Figure 2 is a diagram showing an example of the configuration of an in-vehicle system according to an embodiment of the present disclosure. Figure 3 is a diagram showing an example of driving data created by an in-vehicle device according to an embodiment of the present disclosure. Figure 4 is a diagram showing an example of the configuration of a server according to an embodiment of the present disclosure. Figure 5 is a diagram showing an example of detection result data created by a server according to an embodiment of the present disclosure. Figure 6 is a diagram showing an example of event data created by a server according to an embodiment of the present disclosure. Figure 7 is a diagram showing an example of event data after mapping processing by a server according to an embodiment of the present disclosure. Figure 8 is a diagram showing an example of weather data transmitted by a weather data management device in a communication system according to an embodiment of the present disclosure. Figure 9 is a diagram showing another example of event data after mapping processing by a server according to an embodiment of the present disclosure. Figure 10 is a diagram showing an example of past event data used in estimation processing by a server according to an embodiment of the present disclosure. Figure 11 is a diagram for explaining estimation processing by a server according to an embodiment of the present disclosure. Figure 12 is a diagram showing an example of estimation result data created by a server according to an embodiment of the present disclosure. Figure 13 is a diagram showing another example of estimated result data created by the server according to the embodiment of this disclosure. Figure 14 is a flowchart showing an example of the operation procedure when the in-vehicle device according to the embodiment of this disclosure performs the process of transmitting driving data. Figure 15 is a flowchart showing an example of the operation procedure when the server according to the embodiment of this disclosure performs the process of creating event data. Figure 16 is a flowchart showing an example of the operation procedure when the server according to the embodiment of this disclosure performs the process of creating event data. Figure 17 is a flowchart showing an example of the operation procedure when the server according to the embodiment of this disclosure performs the estimation process. Figure 18 is a flowchart showing an example of the operation procedure when the server according to the embodiment of this disclosure performs the estimation process. Figure 19 is a diagram showing the configuration of Modified Example 1 of the communication system according to the embodiment of this disclosure. Figure 20 is a diagram showing an example of construction status data transmitted by the road data management device in Modified Example 1 of the communication system according to the embodiment of this disclosure.Figure 21 shows an example of event data after mapping processing according to Modification 1 of the server according to the embodiment of this disclosure. Figure 22 shows an example of traffic condition data transmitted by a road data management device in Modification 2 of the communication system according to the embodiment of this disclosure. Figure 23 shows an example of event data after mapping processing according to Modification 2 of the server according to the embodiment of this disclosure.

[0007] When evaluating a driver's driving skills, it is conceivable to use past driving data from one or more vehicles along the route in which the driving skill was performed as reference data for evaluation. However, since the driving routes of each vehicle generally differ from time to time, it is difficult to collect past driving data from vehicles along the same route in which the driving skill being evaluated was performed.

[0008] This disclosure was made to solve the aforementioned problems, and its purpose is to provide a driving data processing system, a driving diagnostic system, and a data structure that can easily evaluate the driver's driving operations.

[0009] According to this disclosure, it is possible to easily evaluate the driver's driving operations.

[0010] First, the contents of the embodiments of the present disclosure will be listed and explained. (1) The driving data processing system according to the embodiments of the present disclosure includes: a driving data acquisition unit that acquires driving data relating to the driving state of a vehicle traveling on a driving route that includes a plurality of road links; a detection unit that detects events relating to the vehicle for each road link based on the driving data; a creation unit that creates event data for each road link showing the detection results of the events; and a driving result acquisition unit that acquires driving result data showing the driving results of the vehicle on the driving route, wherein the creation unit associates the driving result data with the event data.

[0011] With this configuration, when evaluating a driver's driving operations on a particular route, even if there are no or few instances of a vehicle having previously traveled that route, the detection results of events detected when one or more vehicles have previously traveled each road link included in that route can be used as reference data for the evaluation. Furthermore, because the past driving results of vehicles along the entire route are associated with these detection results, the degree of risk when a driver drives a vehicle along that route can be easily estimated using those driving results. Therefore, it is possible to easily evaluate a driver's driving operations on a vehicle.

[0012] (2) In the above (1), the driving data processing system further includes an external data acquisition unit that acquires external data relating to the external conditions of the vehicle, and the creation unit may associate the event data with the driving result data and the external data.

[0013] This configuration allows for a more appropriate driving evaluation that takes into account the external conditions of the vehicle when the driver performs driving operations.

[0014] (3) In (2) above, the external data may include at least one of the following: weather data for the area including the route when the vehicle traveled the route; data relating to the status of construction at at least one of the road links among the plurality of road links; and data relating to traffic conditions at each of the road links.

[0015] This configuration allows for more appropriate driving evaluations that take into account weather conditions during driving, the status of construction on the road links passed through, or the traffic conditions on those road links.

[0016] (4) In any of (1) to (3) above, the driving data processing system further includes an attribute data acquisition unit that acquires attribute data indicating the attributes of the vehicle, and the creation unit may further associate the attribute data with the event data.

[0017] Drivers may operate multiple vehicles with different attributes. With the configuration described above, driving evaluation can be performed using the detection results of past events in vehicles with the same attributes as the vehicle in which the driving operation being evaluated took place, thereby improving the accuracy of the evaluation.

[0018] (5) The driving diagnostic system according to the embodiment of the present disclosure includes: a driving data acquisition unit that acquires driving data relating to the driving state of a vehicle traveling on a driving route that includes a plurality of road links; a detection unit that detects events relating to the vehicle for each road link based on the driving data; a creation unit that creates event data for each road link showing the detection results of the events; and an estimation unit that performs estimation processing to estimate the degree of risk when the driver of the vehicle drives the vehicle along the driving route, based on the event data and past event data which is event data corresponding to the driving route and was created by the creation unit in the past than the event data.

[0019] With this configuration, when evaluating a driver's driving operations on a particular route, even if there are few or no previous instances of each vehicle having traveled that route, the detection results of events detected when one or more vehicles have previously traveled each road link included in that route can be used as reference data for the evaluation. Therefore, it becomes easier to evaluate the driver's driving operations on the vehicle.

[0020] (6) In the above (5), the driving diagnostic system further includes a driving result acquisition unit that acquires driving result data showing the driving results of the vehicle on the driving route, and the estimation unit may perform the estimation process based on the event data created by the creation unit and the past event data to which the driving result data is associated.

[0021] With this configuration, the degree of risk of driving operations along a given route can be easily estimated using past driving results of the vehicle along that route, which are associated with past event data.

[0022] (7) In the above (6), the estimation unit may create a trained model based on the past event data that outputs a prediction result of the driving result data when the event data is input, the estimation unit may calculate an evaluation value for the degree of risk based on the prediction result, and the estimation unit may perform the estimation process using the evaluation value.

[0023] In this configuration, event data is input into a pre-trained model, and estimation processing is performed using evaluation values ​​based on the predicted driving result data output from the trained model. This allows for a more accurate estimation of the degree of risk of driver actions using machine learning techniques.

[0024] (8) The data structure according to the embodiment of the present disclosure is a data structure for data used in estimation processing by a driving diagnostic system, wherein the estimation processing is a process for estimating the degree of driving risk by a driver of a vehicle traveling on a route that includes a plurality of road links, and the data structure comprises data indicating events related to the vehicle for each of the road links included in the route, and data indicating the results of the vehicle's driving on the route.

[0025] This data structure allows for the evaluation of a driver's driving actions along a given route. Even if a vehicle has little or no prior experience traveling that route, the detection results of events detected when one or more vehicles previously traveled each road link included in that route can be used as reference data for the evaluation. Furthermore, because the past driving results of vehicles along a route are associated with these detection results, the degree of risk when a driver drives a vehicle along that route can be easily estimated using those driving results. Therefore, the evaluation of a driver's driving actions can be easily performed.

[0026] Embodiments of this disclosure will be described below with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated. Furthermore, at least some of the embodiments described below may be combined in any way.

[0027] [Communication System] Figure 1 is a diagram showing an example of the configuration of a communication system according to an embodiment of the present disclosure. Referring to Figure 1, the communication system 501 comprises a server 151, a weather data management device 161, and one or more in-vehicle systems 301. The in-vehicle system 301 is mounted on a vehicle 1. The server 151 and the weather data management device 161 are provided outside the vehicle 1. The server 151 is an example of a driving data processing system and an example of a driving diagnostic system.

[0028] Server 151 is used, for example, by a business operator or individual that manages the operation of vehicle 1. Server 151 sends and receives various types of data to and from each vehicle 1 via an external network 171 such as the Internet.

[0029] Server 151 performs estimation processing to estimate the degree of risk B when the driver of vehicle 1 drives vehicle 1 along a route L that includes multiple road links.

[0030] The weather data management device 161 transmits weather data to the server 151 via the external network 171.

[0031] [In-vehicle system] (In-vehicle network) Figure 2 is a diagram showing an example of the configuration of an in-vehicle system according to an embodiment of the present disclosure. Referring to Figure 2, the in-vehicle system 301 comprises an in-vehicle device 101 and a plurality of in-vehicle devices 202.

[0032] The in-vehicle equipment 202 includes an in-vehicle ECU (Electronic Control Unit), sensors, navigation systems, human-machine interfaces, cameras, and LiDAR (Laser Imaging Detection and Ranging). The in-vehicle ECU includes a TCU (Telematics Communication Unit), engine ECU, autonomous driving ECU, steering ECU, brake ECU, and door lock ECU.

[0033] The in-vehicle device 101 and the multiple in-vehicle devices 202 constitute an in-vehicle network 401. The multiple in-vehicle devices 202 are connected to the in-vehicle device 101, for example, via a CAN bus 51 that conforms to the CAN (Controller Area Network) standard.

[0034] In the example shown in Figure 2, the in-vehicle system 301 includes in-vehicle equipment 202, which consists of in-vehicle equipment 202A, 202B, 202C, and 202D. In addition, in the example shown in Figure 2, CAN buses 51A and 51B are provided as CAN buses 51.

[0035] The in-vehicle devices 202A and 202B are connected to the in-vehicle device 101 via the CAN bus 51A. The in-vehicle devices 202C and 202D are connected to the in-vehicle device 101 via the CAN bus 51B.

[0036] For example, the in-vehicle device 101 operates using power supplied from the accessory power supply of the vehicle 1. Each in-vehicle device 202 operates using power supplied from the ignition power supply of the vehicle 1.

[0037] For example, each in-vehicle device 202 transmits a CAN frame to another in-vehicle device 202 or in-vehicle device 101, which includes various data described later, such as data to assist the autonomous driving performed by the vehicle 1 and data used for entertainment, as well as a CAN-ID (Identifier) ​​indicating the type of data, etc.

[0038] The in-vehicle system 301 is not limited to a configuration with three CAN buses 51; it may also have one, two, or four or more CAN buses 51.

[0039] The in-vehicle device 202 is not limited to being connected to the in-vehicle apparatus 101 via the CAN bus 51. For example, it may be connected to the in-vehicle apparatus 101 via a transmission line conforming to other communication standards such as CAN FD (CAN with Flexible Data Rate), Ethernet (registered trademark), FlexRay (registered trademark), MOST (Media Oriented System Transport) (registered trademark), LIN (Local Interconnect Network), and CXPI (Clock Extension Peripheral Interface) (registered trademark).

[0040] In the example shown in FIG. 2, the in-vehicle devices 202A, 202B, 202C, and 202D are also referred to as a GPS (Global Positioning System) receiver 202A, an accelerator sensor 202B, a brake sensor 202C, and a steering sensor 202D, respectively.

[0041] The GPS receiver 202A receives GPS signals from one or more satellites and detects the position of the vehicle 1 based on the received GPS signals. The position coordinates of the vehicle 1 are indicated by, for example, latitude and longitude.

[0042] The GPS receiver 202A transmits position data indicating the detection result and the detection time tp to the in-vehicle apparatus 101. The GPS receiver 202A performs position detection and transmission of position data, for example, every one second.

[0043] The accelerator sensor 202B measures, for example, periodically, the accelerator opening degree of the vehicle 1 and transmits accelerator data indicating the measurement result and the measurement time ta to the in-vehicle apparatus 101. The accelerator sensor 202B measures the accelerator opening degree and transmits the accelerator data, for example, every one second.

[0044] The brake sensor 202C measures, for example, periodically, the brake pressure and transmits brake data indicating the measurement result and the measurement time tb to the in-vehicle apparatus 101. The brake sensor 202C measures the brake pressure and transmits the brake data, for example, every one second.

[0045] The steering sensor 202D measures, for example, the steering angle of the steering wheel of the vehicle 1 periodically, and transmits steering data indicating the measurement result and the measurement time ts to the in-vehicle device 101. The steering angle indicates the amount of rotation in the direction in which the driver rotates the steering wheel from the neutral position of the steering wheel. The steering sensor 202D performs measurement of the steering angle and transmission of the steering data, for example, every 1 second.

[0046] (In-vehicle device) The in-vehicle device 101 includes an in-vehicle communication unit 11, a travel data creation unit 12, an out-vehicle communication unit 13, and a storage unit 14. Some or all of the in-vehicle communication unit 11, the travel data creation unit 12, and the out-vehicle communication unit 13 are executed by, for example, a processing circuit (Circuitry) including one or a plurality of processors. The storage unit 14 is, for example, a non-volatile memory included in the above processing circuit.

[0047] <In-vehicle communication unit> The in-vehicle communication unit 11 acquires vehicle data regarding the vehicle 1. In the present embodiment, for example, the in-vehicle communication unit 11 acquires position data, accelerator data, brake data, and steering data as vehicle data.

[0048] Each time the in-vehicle communication unit 11 receives position data from the GPS receiver 202A, it stores the received position data in the storage unit 14.

[0049] Each time the in-vehicle communication unit 11 receives accelerator data from the accelerator sensor 202B, it stores the received accelerator data in the storage unit 14.

[0050] Each time the in-vehicle communication unit 11 receives brake data from the brake sensor 202C, it stores the received brake data in the storage unit 14.

[0051] Each time the in-vehicle communication unit 11 receives steering data from the steering sensor 202D, it stores the received steering data in the storage unit 14.

[0052] <Driving Data Creation Unit> The driving data creation unit 12 creates driving data D relating to the driving state of vehicle 1 as it travels along the driving route L. More specifically, for example, the driving data creation unit 12 creates driving data D each time vehicle 1 completes a trip. Here, a trip is the period from when vehicle 1 starts driving until it is parked. Specifically, a trip is the period T from when the ignition power of vehicle 1 is turned on until it is turned off.

[0053] For example, the driving data creation unit 12 creates driving data D when the ignition power is switched from the ON state to the OFF state.

[0054] Specifically, for example, the driving data creation unit 12 detects the switching of the ignition power supply to on and off by measuring the output voltage of the ignition power supply when its own in-vehicle device 101 is operating using power supplied from the accessory power supply. The driving data creation unit 12 determines that the ignition power supply is in the ON state if the measured voltage value is greater than or equal to the threshold Th1. On the other hand, the driving data creation unit 12 determines that the ignition power supply is in the OFF state if the measured voltage value is less than the threshold Th1.

[0055] When the driving data creation unit 12 determines that the ignition power of vehicle 1 has switched from the ON state to the OFF state, it retrieves multiple position data, multiple accelerator data, multiple brake data, and multiple steering data stored in the storage unit 14 by the in-vehicle communication unit 11 during the period T.

[0056] The driving data creation unit 12 creates driving data D using the extracted multiple position data, multiple accelerator data, multiple brake data, and multiple steering data.

[0057] Figure 3 shows an example of driving data created by the in-vehicle device according to the embodiment of this disclosure.

[0058] Referring to Figure 3, for example, the driving data D shows the correspondence between the detection time tp of the vehicle 1's position coordinates, the latitude of those position coordinates, the longitude of those position coordinates, the accelerator opening at the measurement time ta closest to the detection time tp, the brake pressure at the measurement time tb closest to the detection time tp, and the steering angle at the measurement time ts closest to the detection time tp.

[0059] In the example shown in Figure 3, in the driving data D, when the detection time tp is 15:00:24 on June 24, 2024, the latitude, longitude, accelerator opening, brake pressure, and steering angle of vehicle 1 are "35.001", "138.050", "10%", "zero" bar, and "8" rad, respectively. At 15:00:25 on June 24, 2024, the latitude, longitude, accelerator opening, brake pressure, and steering angle of vehicle 1 are "35.000", "138.051", "72%", "zero" bar, and "7" rad, respectively. When the detection time tp is 15:23:41 on June 24, 2024, the latitude, longitude, accelerator opening, brake pressure, and steering angle of vehicle 1 are "35.011", "138.051", "zero", "5", and "5", respectively. When the detection time tp is 15:23:42 on June 24, 2024, the latitude, longitude, accelerator opening, brake pressure, and steering angle of vehicle 1 are "35.012", "138.052", "zero", "80", and "67", respectively.

[0060] Referring again to Figure 2, once the driving data creation unit 12 has created the driving data D, it outputs the created driving data D to the external communication unit 13.

[0061] For example, the storage unit 14 stores vehicle identification data (hereinafter also referred to as "vehicle ID (Identifier)") for identifying vehicle 1, and attribute data indicating the attributes of vehicle 1. The vehicle ID is an ID unique to vehicle 1.

[0062] For example, the storage unit 14 stores vehicle class data indicating the vehicle class of vehicle 1 (e.g., small passenger car or large heavy vehicle) as attribute data. The storage unit 14 may also be configured to store other data as attribute data, such as data indicating the vehicle type of vehicle 1 and data indicating the year of manufacture of vehicle 1, in addition to vehicle class data.

[0063] <External Communication Unit> Referring again to Figures 1 and 2, the external communication unit 13 transmits the driving data D created by the driving data creation unit 12 to the server 151.

[0064] More specifically, the external communication unit 13 communicates with the server 151 via the external network 171 by wirelessly communicating with the wireless base station device 181 according to a communication method such as Wi-Fi (registered trademark), LTE (Long Term Evolution) (registered trademark), or 5G. The external communication unit 13 may also be configured to communicate with the server 151 via other in-vehicle devices.

[0065] When the external communication unit 13 receives driving data D from the driving data creation unit 12, it creates an IP packet (hereinafter also referred to as "packet P1") containing the driving data D and vehicle ID and attribute data stored in the storage unit 14, with packet P1 containing the IP address of its own in-vehicle device 101 and the IP address of the server 151 as the source IP address and destination IP address, respectively. The external communication unit 13 then transmits the created packet P1 to the server 151 via the wireless base station device 181 and the external network 171.

[0066] [Server] Figure 4 is a diagram showing an example of the configuration of a server according to an embodiment of the present disclosure. Referring to Figure 4, the server 151 comprises a communication unit 21, a detection unit 22, and an event data creation unit 23. The server 151 may include at least one of the estimation unit 24, a notification unit 25, and a storage unit 26, or any combination thereof or all of them. Some or all of the communication unit 21, detection unit 22, event data creation unit 23, estimation unit 24, and notification unit 25 are executed by a processing circuit including, for example, one or more processors. The storage unit 26 is, for example, a non-volatile memory included in the processing circuit. The communication unit 21 is an example of a driving data acquisition unit, an example of an external data acquisition unit, an example of an attribute data acquisition unit, and an example of a driving result acquisition unit. The event data creation unit 23 is an example of a creation unit.

[0067] (Communication Unit) For example, the communication unit 21 acquires driving data D and attribute data. Specifically, for example, the communication unit 21 receives a packet P1 containing driving data D and attribute data from the in-vehicle device 101 via the wireless base station device 181 and the external network 171. The communication unit 21 then outputs the vehicle-related data, including driving data D, attribute data, and vehicle ID, contained in the received packet P1, to the detection unit 22.

[0068] (Detection Unit) The detection unit 22 performs event detection processing to detect events E related to the vehicle 1 for each road link included in the vehicle 1's driving route, based on the driving data D acquired by the communication unit 21. More specifically, for example, in the event detection processing, the detection unit 22 detects a predetermined driving operation by the vehicle's driver as an event E.

[0069] In this embodiment, for example, the detection unit 22 detects multiple events E, namely events E1, E2, and E3, during the event detection process. Here, events E1, E2, and E3 are, respectively, operations performed by the driver of vehicle 1: sudden acceleration, sudden braking, and sudden steering.

[0070] (a1) When the detection unit 22 receives vehicle-related data from the communication unit 21, it calculates the amount of change in accelerator opening per second at each detection time tp indicated by the driving data D included in the vehicle-related data.

[0071] Specifically, for example, when the detection unit 22 calculates the amount of change Ha at a detection time tp1, which is a certain detection time tp, it uses the accelerator opening at detection time tp1 and the accelerator opening at a detection time tp earlier than detection time tp1 (hereinafter also referred to as "detection time tp2"), which is the closest to detection time tp1, to calculate the amount of change Ha.

[0072] If the calculated change amount Ha is less than the threshold Th11, the detection unit 22 determines that event E1 has not occurred, that is, the driver has not performed a sudden acceleration operation.

[0073] On the other hand, the detection unit 22 determines that event E1 has occurred, i.e., that the driver performed a sudden acceleration operation, if the calculated change amount Ha is greater than or equal to the threshold Th11.

[0074] (a2) When the detection unit 22 receives vehicle-related data from the communication unit 21, it calculates the change in brake pressure per second Hb at each detection time tp indicated by the driving data D included in the vehicle-related data.

[0075] Specifically, for example, when the detection unit 22 calculates the change amount Hb at detection time tp1, it uses the brake pressure at detection time tp1 and the brake pressure at detection time tp2, which is closest to detection time tp1, to calculate the change amount Hb.

[0076] The detection unit 22 determines that if the calculated change amount Hb is less than the threshold Th12, event E2 has not occurred, that is, the driver has not performed an emergency braking operation.

[0077] On the other hand, the detection unit 22 determines that event E2 has occurred, i.e., that the driver has performed a sudden braking operation, if the calculated change amount Hb is greater than or equal to the threshold Th12.

[0078] (a3) When the detection unit 22 receives vehicle-related data from the communication unit 21, it calculates the amount of change in steering angle Hc per second at each detection time tp indicated by the driving data D included in the vehicle-related data.

[0079] Specifically, for example, when the detection unit 22 calculates the amount of change Hc at detection time tp1, it uses the rudder angle at detection time tp1 and the rudder angle at detection time tp2, which is closest to detection time tp1, to calculate the amount of change Hc.

[0080] The detection unit 22 determines that if the calculated change amount Hc is less than the threshold Th13, event E3 has not occurred, meaning the driver has not performed a sudden steering maneuver.

[0081] On the other hand, the detection unit 22 determines that event E3 has occurred, i.e., that the driver performed a sudden steering maneuver, if the calculated change amount Hc is greater than or equal to the threshold Th13.

[0082] Figure 5 shows an example of detection result data created by the server according to the embodiment of this disclosure.

[0083] Referring to Figures 4 and 5, once the detection unit 22 completes the event detection process, it creates detection result data K that shows the detection result of event E at each detection time tp.

[0084] For example, the detection result data K shows the correspondence between the detection time tp of the vehicle 1's position coordinates, the latitude of those position coordinates, the longitude of those position coordinates, and the respective detection results of events E1, E2, and E3. In the detection result data K shown in Figure 5, "True" indicates that event E occurred, and "False" indicates that event E did not occur.

[0085] In the example shown in Figure 5, at 15:00:25 on June 24, 2024, the driver performed a sudden acceleration operation, and the latitude and longitude of the road link where this operation occurred are "35.000" and "138.051", respectively. Also, at 15:23:42 on June 24, 2024, the driver performed a sudden braking operation and a sudden steering operation, and the latitude and longitude of the road link where these operations occurred are "35.012" and "138.052", respectively.

[0086] When the detection unit 22 creates detection result data K, it outputs the detection result data K to the event data creation unit 23, including the vehicle ID and attribute data included in the vehicle-related data received from the communication unit 21.

[0087] Server 151 may be configured to detect other driving operations by the driver other than sudden acceleration, sudden braking, and sudden steering as Event E. Furthermore, Server 151 may be configured to detect not only driving operations by the driver, but also, for example, when an obstacle such as another vehicle approaches Vehicle 1 while Vehicle 1 is in motion, as Event E. In this case, for example, Server 151 receives driving data D from the in-vehicle device 101, including measurement results from in-vehicle equipment 202 such as a camera and LiDAR. Based on these measurement results, Server 151 determines whether or not an obstacle approached Vehicle 1 while Vehicle 1 was in motion.

[0088] (Event Data Creation Section) Figure 6 shows an example of event data created by the server according to the embodiment of this disclosure.

[0089] Referring to Figures 4 and 6, the event data creation unit 23 creates event data G that shows the detection results of events E by the detection unit 22 for each road link included in the vehicle's travel path L.

[0090] For example, event data G shows the correspondence between the time when vehicle 1 entered the road link (hereinafter also referred to as "entry time"), identification data for identifying the road link (hereinafter also referred to as "link ID"), and the number of occurrences of each of events E1, E2, and E3.

[0091] Here, the road link is identified by multiple positional coordinates. Hereafter, these multiple positional coordinates will also be referred to as positional coordinate group F.

[0092] For example, the storage unit 26 stores a road link table that shows the correspondence between link IDs and the group of position coordinates F.

[0093] When the event data creation unit 23 receives detection result data K from the detection unit 22, it refers to the road link table in the storage unit 26 and identifies a link ID corresponding to the group of position coordinates F that includes the position coordinates indicated by the detection result data K. In other words, the event data creation unit 23 identifies the road links that the vehicle 1 traversed in one trip.

[0094] The event data creation unit 23 selects an entry time corresponding to a given link ID from among multiple detection times tp indicated by the detection result data K received from the detection unit 22, for each identified link ID.

[0095] The event data creation unit 23 uses the detection result data K received from the detection unit 22 to perform aggregation processing to aggregate the number of occurrences of each of events E1, E2, and E3 in the road link of the identified link ID.

[0096] The event data creation unit 23 selects the entry time corresponding to each link ID, and once the aggregation process is complete, it creates event data G for each identified link ID, associating the entry time and aggregation result with that link ID.

[0097] In the example shown in Figure 6, the entry time of vehicle 1 into the road link with link ID "1001" was 15:00:24 on June 24, 2024. On that road link, the number of times the driver performed sudden acceleration, sudden braking, and sudden steering operations were "zero," "two," and "one," respectively.

[0098] In the example shown in Figure 6, the entry time of vehicle 1 into the road link with link ID "2005" was 15:01:45 on June 24, 2024. On that road link, the number of times the driver performed sudden acceleration, sudden braking, and sudden steering operations was "1," "zero," and "1," respectively.

[0099] In the example shown in Figure 6, the entry time of vehicle 1 into the road link with link ID "8092" was 15:04:18 on June 24, 2024. On that road link, the number of times the driver performed sudden acceleration, sudden braking, and sudden steering maneuvers was "zero".

[0100] (Mapping event data and attribute data) Referring again to Figure 4, for example, the event data creation unit 23 performs a mapping process C1 to associate the attribute data acquired by the communication unit 21 with the event data G that it has created.

[0101] More specifically, for example, when the event data creation unit 23 creates event data G, it includes the attribute data contained in the detection result data K received from the detection unit 22 in the event data G. Hereinafter, the event data G including the attribute data will also be referred to as event data G1.

[0102] Figure 7 shows an example of event data after mapping processing by the server according to the embodiment of this disclosure.

[0103] In the example shown in Figure 7, the attribute of vehicle 1, indicated by the attribute data attached to event data G, is "small passenger car".

[0104] (Acquisition of weather data) Referring again to Figures 1 and 4, for example, once the event data creation unit 23 completes the mapping process C1, it requests the weather data management device 161 to transmit weather data W for the area including the driving route L (hereinafter also referred to as the "driving area") when the vehicle 1 travels along the driving route L.

[0105] More specifically, for example, once the event data creation unit 23 completes the mapping process C1, it outputs a request notification R1 to the communication unit 21 indicating a request for the transmission of weather data W and showing multiple detection times tp and multiple location coordinates in the detection result data K received from the detection unit 22.

[0106] The communications unit 21 transmits the request notification R1 received from the event data creation unit 23 to the weather data management device 161 via the external network 171.

[0107] Figure 8 shows an example of weather data transmitted by a weather data management device in a communication system according to an embodiment of the present disclosure.

[0108] Referring to Figures 1 and 8, when the weather data management device 161 receives a request notification R1 from the server 151 via the external network 171, it transmits the weather data W to the server 151 in accordance with the request notification R1.

[0109] More specifically, for example, the weather data management device 161 identifies the area traveled by vehicle 1 based on the multiple location coordinates indicated in the request notification R1 received from server 151. The weather data management device 161 then transmits weather data W for the identified area, specifically the weather data W for regular intervals within the time period Tw that includes the multiple detection times tp indicated in the request notification R1, to server 151 via the external network 171.

[0110] For example, weather data W is data showing the weather and temperature hour by hour during the time period Tw in the driving area.

[0111] In the example shown in Figure 8, the weather and temperature in the driving area "AAA" from 15:00 to 16:00 on June 24, 2024, were "cloudy" and "27°C," respectively. The weather and temperature in the driving area "AAA" from 16:00 to 17:00 on June 24, 2024, were "sunny" and "26°C," respectively.

[0112] Referring again to Figure 4, in the server 151, for example, the communication unit 21 acquires external data regarding the external conditions of the vehicle 1, specifically weather data W. More specifically, the communication unit 21 receives weather data W from the weather data management device 161 via the external network 171. The communication unit 21 then outputs the received weather data W to the event data creation unit 23.

[0113] (Mapping event data and weather data) For example, the event data creation unit 23 performs a mapping process C2 to further map the weather data W acquired by the communication unit 21 to the event data G it has created.

[0114] More specifically, for example, the event data creation unit 23 further includes the weather data W received from the communication unit 21 in the event data G1, which includes attribute data.

[0115] Specifically, for example, when the event data creation unit 23 receives weather data W from the communication unit 21, it includes the weather conditions at the time the vehicle 1 entered the road link of that link ID in the event data G1, for each link ID. Hereinafter, the event data G1 including the weather data W will also be referred to as event data G2.

[0116] Figure 9 shows another example of event data after mapping processing by the server according to the embodiment of this disclosure.

[0117] In the example shown in Figure 9, the weather at the time of entry when vehicle 1 enters road link with link ID "1001", the weather at the time of entry when it enters road link with link ID "2005", and the weather at the time of entry when it enters road link with link ID "8092" are "cloudy".

[0118] Referring again to Figure 4, once the event data creation unit 23 completes the mapping process C2, it outputs the event data G2 to the estimation unit 24, including the vehicle ID contained in the detection result data K received from the detection unit 22.

[0119] (Estimation Processing) The estimation unit 24 performs estimation processing based on the event data G2 created by the event data creation unit 23 and the event data G (hereinafter also referred to as "past event data G3") that corresponds to the travel route L and was previously created by the event data creation unit 23.

[0120] Figure 10 shows an example of past event data used in the estimation process by the server according to the embodiment of this disclosure.

[0121] Referring to Figures 4 and 10, the storage unit 26 stores multiple past event data G3 associated with the driving result data. The driving result data is data indicating the driving result of vehicle 1 along the driving route L. Details of the process by which the server 151 saves the past event data G3 will be described later.

[0122] In the example shown in Figure 10, the driving result data associated with past event data G3 indicates a near-miss that occurred when the driver drove along a route L that included road links with link ID "1001", road links with link ID "2005", and road links with link ID "8092", etc.

[0123] For example, the estimation unit 24 performs estimation processing based on the event data G2 created by the event data creation unit 23 and a plurality of past event data G3 to which the driving result data is associated.

[0124] In this embodiment, the estimation unit 24 performs estimation processing using machine learning techniques. More specifically, for example, the estimation unit 24 creates a trained model M that outputs a prediction result of the driving result data when event data G2 is input, based on a plurality of past event data G3 to which the driving result data is associated. Then, the estimation unit 24 performs estimation processing using the created trained model M.

[0125] Specifically, for example, when the estimation unit 24 receives event data G2 from the event data creation unit 23, it retrieves multiple past event data G3 containing the same link ID as the event data G2 from the storage unit 26. If the number of retrieved past event data G3 is greater than or equal to a predetermined value, the estimation unit 24 creates a trained model M corresponding to the link ID based on the retrieved past event data G3. On the other hand, if the number of retrieved past event data G3 is less than a predetermined value, the estimation unit 24 does not create a trained model M. This prevents the use of a trained model M with low prediction accuracy in the estimation process, meaning that past event data G3 corresponding to road links that may have low prediction accuracy for driving results are excluded from the past event data G3 used in the estimation process, thus preventing a decrease in the estimation accuracy of risk level B.

[0126] The estimation unit 24 creates a trained model M for each ink ID in the event data G2 received from the event data creation unit 23, and inputs the detection result, attribute data, and weather data W of each event E corresponding to the link ID into the trained model M. Then, the estimation unit 24 obtains the prediction result of the driving result data output from the trained model M.

[0127] In this embodiment, for example, the trained model M outputs the probability Q1 that the driver's driving operations were normal along the driving route L, the probability Q2 that the driver had a near-miss along the driving route L, and the probability Q3 that the driver had an accident along the driving route L as predicted results of the driving result data.

[0128] Figure 11 is a diagram illustrating the estimation process performed by the server according to an embodiment of the present disclosure.

[0129] In the example shown in Figure 11, the probabilities Q1, Q2, and Q3 when vehicle 1 travels along the road link with link ID "1001" are "80%", "18%", and "2%", respectively. The probabilities Q1, Q2, and Q3 when vehicle 1 travels along the road link with link ID "2005" are "95%", "5%", and "0%", respectively. The probabilities Q1, Q2, and Q3 when vehicle 1 travels along the road link with link ID "8092" are "98%", "1%", and "0%", respectively.

[0130] In the example shown in Figure 11, the probabilities Q1, Q2, and Q3 when vehicle 1 travels along the road link with link ID "8172" are "unpredictable" because a trained model M corresponding to that link ID was not created.

[0131] For example, the estimation unit 24 calculates a score S related to the risk level B based on the probabilities Q1, Q2, and Q3 output from the trained model M that it has created. Then, the estimation unit 24 performs estimation processing using the calculated score S. The score S is an example of an evaluation value.

[0132] More specifically, the estimation unit 24 obtains probabilities Q1, Q2, and Q3 for each link ID, and then uses these probabilities Q1, Q2, and Q3 to calculate a score S for each link ID.

[0133] Specifically, for example, the estimation unit 24 calculates the score S by substituting the acquired probabilities Q1, Q2, and Q3 into the following equation (1). In equation (1), a1, a2, and a3 are coefficients. Here, coefficients a1, a2, and a3 are zero, 1, and 3, respectively. S = Q1 × a1 + Q2 × a2 + Q3 × a3 ... (1)

[0134] In the example shown in Figure 11, the scores S corresponding to link ID "1001", link ID "2005", and link ID "8092" are "24", "5", and "4", respectively. The estimation unit 24 may calculate the score S using a predetermined calculation formula other than formula (1).

[0135] For example, the estimation unit 24 calculates a score S for each link ID and then calculates the average value A of the multiple scores S. Specifically, the estimation unit 24 calculates the average value A by dividing the sum U of the multiple calculated scores S by a number N. Here, the number N is the value obtained by subtracting the number of link IDs for which a trained model M was not created from the number of link IDs in the event data G2 received from the event data creation unit 23.

[0136] For example, the estimation unit 24 estimates whether the risk level B is level 1, level 2, or level 3 by comparing the calculated average value A with a threshold. Here, level 1 indicates a high probability that the driver caused an accident on the route L. Level 2 indicates a high probability that the driver had a near-miss on the route L. Level 3 indicates that the driver's driving operations on the route L were normal. In other words, the risk level is highest at level 1, followed by level 2 and then level 3.

[0137] Specifically, the estimation unit 24 calculates the average value A and then checks whether the average value A is equal to or greater than the threshold Th21.

[0138] For example, if the calculated average value A is equal to or greater than the threshold Th21, the estimation unit 24 estimates the risk level B to be level 1.

[0139] For example, the estimation unit 24 estimates the risk level B to be level 2 if the calculated average value A is less than the threshold Th21 and greater than or equal to the threshold Th22.

[0140] On the other hand, the estimation unit 24 estimates the risk level B to be level 3 if the calculated average value A is less than the threshold Th22.

[0141] The estimation unit 24 creates estimation result data that includes the estimation result, a plurality of link IDs corresponding to the estimation result, and a vehicle ID included in the event data G received from the event data creation unit 23.

[0142] The estimation unit 24 may be configured to perform estimation processing not only based on the comparison result between the average value A of the multiple scores S and the threshold, but also based on the comparison result between the sum U of the multiple scores S and the threshold, etc.

[0143] Figure 12 shows an example of estimated result data created by the server according to the embodiment of this disclosure.

[0144] In the example shown in Figure 12, the estimated risk level B when vehicle 1 travels along a route L that includes road links with link ID "1001", road links with link ID "2005", and road links with link ID "8092", is "Level 2".

[0145] Figure 13 shows another example of estimated result data created by the server according to the embodiment of this disclosure.

[0146] Referring to Figure 13, the estimated risk level B when vehicle 1 travels along route L which includes road links with link ID "1002", road links with link ID "2023", and road links with link ID "2026", is "Level 3".

[0147] When the estimation unit 24 creates estimation result data, it outputs the created estimation result data to the notification unit 25.

[0148] (Notification Processing) The notification unit 25 performs notification processing to notify the risk level B estimated by the estimation unit 24. More specifically, when the notification unit 25 receives the estimation result data from the estimation unit 24, it performs notification processing.

[0149] For example, the storage unit 26 stores a notification table that shows the correspondence between a vehicle ID and data related to the recipient of notifications for risk level B (hereinafter also referred to as "notification recipient data"). In this embodiment, for example, the notification recipient data indicates the email address of the driver of vehicle 1. The notification table is pre-registered in the storage unit 26 by the user, for example. Note that the notification recipient data is not limited to the email address of the driver of vehicle 1, but may also indicate other contact information such as the email address of a relative of the driver.

[0150] When the notification unit 25 receives estimation result data from the estimation unit 24, it refers to the notification table in the storage unit 26 to identify the notification destination data corresponding to the vehicle ID included in the estimation result data.

[0151] The notification unit 25 sends an email in HTML (HyperText Markup Language) format to the email address indicated by the identified notification recipient data, and which contains the estimation result data received from the estimation unit 24.

[0152] (Mapping event data and driving result data) For example, in parallel with the estimation process, the server 151 performs a process to further associate the driving result data with the event data G2 and save it in the storage unit 26.

[0153] More specifically, for example, once the event data creation unit 23 completes the mapping process C2, it requests the driver of the vehicle 1 to send the driving result data.

[0154] Specifically, for example, when the event data creation unit 23 completes the mapping process C2, it outputs a request notification R2 to the communication unit 21 indicating a request for transmission of driving result data, multiple detection times tp in the detection result data K received from the detection unit 22, and the vehicle ID included in the said detection result data K.

[0155] For example, the storage unit 26 stores terminal device data that shows the correspondence between the vehicle ID and identification data (hereinafter also referred to as "terminal ID") for identifying the terminal device owned by the driver. The terminal device is, for example, a communication terminal device such as a smartphone or tablet.

[0156] When the communication unit 21 receives a request notification R2 from the event data creation unit 23, it refers to the terminal device data in the storage unit 26 to identify the terminal ID corresponding to the vehicle ID indicated in the request notification R2.

[0157] The communications unit 21 transmits the request notification R2 received from the event data creation unit 23 to the terminal device with the specified terminal ID via the external network 171.

[0158] For example, when a terminal device receives a request notification R2 from a server 151 via an external network 171, it displays a screen on its own display unit indicating a time period including multiple detection times tp shown in the received request notification R2, and a request for input of driving result data.

[0159] The driver of vehicle 1 inputs data indicating the driving results of vehicle 1 during the time period displayed on the terminal device as driving result data. Specifically, for example, the driver inputs data indicating that the driving during that time period was normal, and that there were any near misses during the driving during that time period, as driving result data.

[0160] When the terminal device receives input of driving result data, it transmits the input driving result data to the server 151 via the external network 171.

[0161] Referring again to Figure 4, in the server 151, the communication unit 21 acquires the driving result data. More specifically, the communication unit 21 receives the driving result data from the terminal device via the external network 171. The communication unit 21 then outputs the received driving result data to the event data creation unit 23.

[0162] For example, the event data creation unit 23 performs a mapping process C3 to further associate the driving result data acquired by the communication unit 21 with the event data G it has created.

[0163] More specifically, for example, the event data creation unit 23 further includes the driving result data received from the communication unit 21 in the event data G2, which includes attribute data and weather data W.

[0164] Once the event data creation unit 23 completes the mapping process C3, it saves the event data G2, which includes the driving result data, to the storage unit 26. The event data creation unit 23 does not need to map the driving result data to the event data G2 used in the estimation process by the estimation unit 24.

[0165] [Operation Flow] Next, the operation of each device in the communication system 501 according to the embodiment of this disclosure will be explained with reference to the drawings.

[0166] Figure 14 is a flowchart illustrating an example of the operation procedure when an in-vehicle device according to an embodiment of the present disclosure performs a process to transmit driving data.

[0167] Referring to Figure 14, first, the in-vehicle device 101, while operating using power supplied from the accessory power supply of the vehicle 1, waits for the ignition power supply of the vehicle 1 to switch to the ON state (NO in step ST101).

[0168] When the in-vehicle device 101 detects that the ignition power has been switched to the ON state (YES in step ST101), it receives vehicle data from a predetermined in-vehicle device 202 and stores it in the storage unit 14. For example, as described above, the in-vehicle device 101 receives position data from the GPS receiver 202A, accelerator data from the accelerator sensor 202B, brake data from the brake sensor 202C, and steering data from the steering sensor 202D as vehicle data and stores it in the storage unit 14 (step ST102).

[0169] The in-vehicle device 101 stores new vehicle data received from a predetermined in-vehicle device 202 in the storage unit 14 (step ST102) until it detects that the ignition power has been switched to the off state (NO in step ST103).

[0170] Next, when the in-vehicle device 101 detects that the ignition power has been switched to the off state (YES in step ST103), it retrieves a plurality of vehicle data received from a predetermined in-vehicle device 202 from the storage unit 14 during the period T from when the ignition power is turned on until it is turned off (step ST104).

[0171] Next, the in-vehicle device 101 creates driving data D using the extracted vehicle data, specifically, multiple position data, multiple accelerator data, multiple brake data, and multiple steering data (step ST105).

[0172] Next, the in-vehicle device 101 sends a packet P1 containing the created driving data D and attribute data and vehicle ID stored in the storage unit 14 to the server 151 (step ST106), and waits for the ignition power to switch to the ON state (NO in step ST101).

[0173] Figures 15 and 16 are flowcharts illustrating an example of the operation procedure when a server according to the embodiment of this disclosure performs the process of creating event data.

[0174] Referring to Figures 15 and 16, first, the server 151 waits for the reception of packet P1 from the in-vehicle device 101 (NO in step ST201).

[0175] When the server 151 receives packet P1 from the in-vehicle device 101 (YES in step ST201), it performs event detection processing to detect an event E related to vehicle 1 for each road link included in the vehicle 1's travel route L, based on the travel data D contained in the received packet P1 (step ST202).

[0176] Next, the server 151 creates event data G showing the detection results of event E for each road link (step ST203).

[0177] Next, when the server 151 creates event data G, it associates the attribute data contained in the received packet P1 with the event data G (step ST204).

[0178] Next, the server 151 requests the weather data management device 161 to transmit weather data W for the area including the travel route L when the vehicle 1 travels along the travel route L (step ST205).

[0179] Next, the server 151 waits for the reception of weather data W from the weather data management device 161 (NO in step ST206).

[0180] When server 151 receives weather data W from weather data management device 161 (YES in step ST206), it further associates the received weather data W with event data G which has attribute data associated with it (step ST207).

[0181] Next, the server 151 requests the driver of vehicle 1 to transmit driving result data showing the driving results of vehicle 1 along the driving route L (step ST208).

[0182] Next, the server 151 awaits the reception of driving result data from the driver's terminal device (NO in step ST209).

[0183] When server 151 receives driving result data from the driver's terminal device (YES in step ST209), it further associates the received driving result data with event data G, which is associated with attribute data and weather data W (step ST210).

[0184] Next, the server 151 stores event data G, which associates attribute data, weather data W, and driving result data, in the storage unit 26 (step ST211), and waits for the reception of a new packet P1 from the in-vehicle device 101 (step ST201, NO).

[0185] Figures 17 and 18 are flowcharts illustrating an example of the operation procedure when the server according to the embodiment of this disclosure performs estimation processing.

[0186] Referring to Figures 17 and 18, the process from step ST301 to step ST307 is the same as the process from step ST201 to step ST207 shown in Figure 15.

[0187] Next, the server 151 retrieves from the storage unit 14 multiple past event data G3 that contain the same link ID as the event data G containing attribute data and weather data W (step ST308).

[0188] Next, the server 151 creates a trained model M based on the extracted past event data G3 (step ST309).

[0189] Next, after creating the trained model M, the server 151 performs an estimation process to estimate the degree of risk B when the driver drives vehicle 1 along the route L (step ST310).

[0190] Next, the server 151 performs a notification process to notify the server of the estimation result data indicating the estimated risk level B (step ST311), and waits for the reception of a new packet P1 from the in-vehicle device 101 (step ST301, NO).

[0191] In the communication system 501 according to the embodiment of this disclosure, the server 151 is configured to include a communication unit 21, a detection unit 22, an event data creation unit 23, and an estimation unit 24, but the invention is not limited to this configuration. For example, a device in the in-vehicle network 401, such as an in-vehicle device 101, may be configured to include a communication unit 21, a detection unit 22, an event data creation unit 23, and an estimation unit 24. Alternatively, multiple devices may share the communication unit 21, a detection unit 22, an event data creation unit 23, and an estimation unit 24 as a driving diagnostic system. For example, the server 151 may include some of the units of the communication unit 21, a detection unit 22, an event data creation unit 23, and an estimation unit 24, while the in-vehicle device 101 includes the remaining units.

[0192] Multiple devices may share a communication unit 21, a detection unit 22, and an event data creation unit 23 as a driving data processing system. For example, a server 151 may comprise some of the units of the communication unit 21, detection unit 22, and event data creation unit 23, while the in-vehicle device 101 comprises the remaining units.

[0193] In the communication system 501 according to the embodiment of this disclosure, the server 151 is configured to perform estimation processing using past event data G3 to which driving result data is associated, but it is not limited to this configuration. The server 151 may also be configured to perform estimation processing using past event data G3 to which data other than driving result data is associated.

[0194] In the communication system 501 according to the embodiment of this disclosure, the server 151 is configured to perform estimation processing using a trained model M, but it is not limited to this. The server 151 may also be configured to perform estimation processing using methods other than machine learning, such as statistical analysis.

[0195] In the communication system 501 according to the embodiment of this disclosure, the server 151 is configured to associate both attribute data and weather data W with the created event data G, but it is not limited to this configuration. The server 151 may be configured to associate one of the attribute data and weather data W with the event data G, while not associating the other with the event data G.

[0196] Some or all of the functions of the server 151 according to the embodiment of this disclosure may be provided by cloud computing. That is, the server 151 according to the embodiment of this disclosure may be a cloud server composed of multiple servers.

[0197] [Modification 1] The server 151 may be configured to associate the created event data G with construction status data J, which concerns the status of construction work at each road link included in the travel route L, instead of weather data W.

[0198] Figure 19 shows the configuration of Modification 1 of the communication system according to the embodiment of the present disclosure. Referring to Figure 19, the communication system 502 is equipped with a road data management device 261 instead of a weather data management device 161, compared to the communication system 501 shown in Figure 1.

[0199] Referring to Figures 4 and 19, in the server 151, once the event data creation unit 23 completes the mapping process C1, it outputs a request notification R21 to the communication unit 21 indicating a request for the transmission of construction status data J, and showing multiple detection times tp and multiple position coordinates in the detection result data K received from the detection unit 22.

[0200] The communications unit 21 transmits the request notification R21 received from the event data creation unit 23 to the road data management device 261 via the external network 171.

[0201] Figure 20 shows an example of construction status data transmitted by a road data management device in Modification 1 of the communication system according to the embodiment of this disclosure.

[0202] Referring to Figures 19 and 20, when the road data management device 261 receives a request notification R21 from the server 151 via the external network 171, it transmits the construction status data J to the server 151 in accordance with the request notification R21.

[0203] More specifically, for example, the road data management device 261 identifies multiple road links that vehicle 1 traveled on based on multiple location coordinates indicated by the request notification R21 received from the server 151. Then, for each identified road link, the road data management device 261 creates construction status data J indicating whether or not the road link was under construction during the time period including the multiple detection times tp indicated by the request notification R21.

[0204] In the example shown in Figure 20, during the period from 3:00 PM to 4:00 PM on June 24, 2024, the road links with link ID "1001" and "8092" were not under construction. During the same period, the road link with link ID "2005" was under construction.

[0205] When the road data management device 261 creates construction status data J, it transmits the created construction status data J to the server 151 via the external network 171.

[0206] Referring again to Figure 4, in the server 151, for example, the communication unit 21 acquires the construction status data J. More specifically, the communication unit 21 receives the construction status data J from the road data management device 261 via the external network 171. The communication unit 21 then outputs the received construction status data J to the event data creation unit 23.

[0207] (Mapping event data with construction status data J) For example, the event data creation unit 23 performs a mapping process C21 to further map the created event data G with the construction status data J acquired by the communication unit 21.

[0208] More specifically, for example, the event data creation unit 23 further includes the construction status data J received from the communication unit 21 in the event data G1, which includes attribute data.

[0209] Specifically, for example, when the event data creation unit 23 receives construction status data J from the communication unit 21, it includes data in the event data G1 indicating whether or not the road link with a given link ID was under construction. Hereinafter, the event data G1 including the construction status data J will also be referred to as event data G21.

[0210] Figure 21 shows an example of event data after mapping processing according to Modification 1 of the server according to the embodiment of this disclosure.

[0211] In the example shown in Figure 21, the road links with link ID "1001" and link ID "8092" that vehicle 1 passed through are not under construction. The road link with link ID "2005" that vehicle 1 passed through is under construction.

[0212] Once the event data creation unit 23 completes the correspondence process C21, it outputs the event data G21 to the estimation unit 24.

[0213] The server 151 is not limited to a configuration that requests the road data management device 261 to transmit data indicating the status of construction work at each road link included in the travel route L, but may also be configured to request the road data management device 261 to transmit data indicating the status of construction work at some of the road links among the plurality of road links.

[0214] [Modification 2] The server 151 may be configured to associate the traffic condition data Y, which pertains to traffic conditions at each road link included in the travel route L, with the created event data G, instead of the weather data W.

[0215] Figure 19 also shows the configuration of a modified example 2 of the communication system according to the embodiment of the present disclosure. Referring to Figures 4 and 19, in the server 151, when the event data creation unit 23 completes the mapping process C1, it outputs a request notification R22 to the communication unit 21 indicating a request for transmission of traffic condition data Y and a plurality of detection times tp and a plurality of position coordinates in the detection result data K received from the detection unit 22.

[0216] The communications unit 21 transmits the request notification R22 received from the event data creation unit 23 to the road data management device 261 via the external network 171.

[0217] Figure 22 shows an example of traffic condition data transmitted by a road data management device in a modified example 2 of the communication system according to the embodiment of the present disclosure.

[0218] Referring to Figures 19 and 22, when the road data management device 261 receives a request notification R22 from the server 151 via the external network 171, it transmits traffic condition data Y to the server 151 in accordance with the request notification R22.

[0219] More specifically, for example, the road data management device 261 identifies multiple road links that vehicle 1 traveled on based on multiple location coordinates indicated by the request notification R22 received from the server 151. Then, for each identified road link, the road data management device 261 creates traffic condition data Y indicating whether or not congestion occurred during the time period including the multiple detection times tp indicated by the request notification R22.

[0220] In the example shown in Figure 22, no congestion occurred on road links with link ID "1001" and "8092" during the period from 15:00 to 16:00 on June 24, 2024. However, congestion occurred on road link "2005" during the same period.

[0221] When the road data management device 261 creates traffic condition data Y, it transmits the created traffic condition data Y to the server 151 via the external network 171.

[0222] Referring again to Figure 4, in the server 151, for example, the communication unit 21 acquires traffic condition data Y. More specifically, the communication unit 21 receives traffic condition data Y from the road data management device 261 via the external network 171. The communication unit 21 then outputs the received traffic condition data Y to the event data creation unit 23.

[0223] (Mapping event data with traffic condition data Y) For example, the event data creation unit 23 performs a mapping process C22 to further associate the created event data G with the traffic condition data Y acquired by the communication unit 21.

[0224] More specifically, for example, the event data creation unit 23 further includes the traffic condition data Y received from the communication unit 21 in the event data G1, which includes attribute data. Hereinafter, the event data G1 including the traffic condition data Y will also be referred to as event data G22.

[0225] Specifically, for example, when the event data creation unit 23 receives traffic condition data Y from the communication unit 21, it includes data in the event data G1 indicating whether or not congestion occurred on the road link of the given link ID, for each link ID.

[0226] Figure 23 shows an example of event data after mapping processing according to Modification 2 of the server according to the embodiment of this disclosure.

[0227] In the example shown in Figure 23, no congestion occurred on the road links with link ID "1001" and "8092" that vehicle 1 passed through. However, congestion occurred on the road link with link ID "2005" that vehicle 1 passed through.

[0228] Once the event data creation unit 23 completes the correspondence process C22, it outputs the event data G22 to the estimation unit 24.

[0229] Server 151 may be configured to associate any two or all of the weather data W, construction status data J, and traffic status data Y with the created event data G. Alternatively, Server 151 may be configured to associate other external data other than weather data W, construction status data J, and traffic status data Y with the created event data G.

[0230] Server 151 may be configured not to associate external data such as weather data W, construction status data J, and traffic status data Y with the created event data G, and not to use external data in the estimation process.

[0231] The embodiments described above should be considered in all respects as illustrative and not restrictive. It should be understood that at least one configuration or feature described in each embodiment and example can be combined with or modified in various ways in other embodiments and examples. The scope of the invention is indicated by the claims rather than the above description, and all modifications within the meaning and scope of the claims are intended to be included.

[0232] Each process (each function) in the above-described embodiment is executed by a common circuit or a combination of multiple circuits (collectively referred to as a circuit). The circuit may consist of at least one processor, at least one memory, various analog circuits, various digital circuits, and the like in an integrated circuit. The memory stores a program (instruction) that causes the processor to execute the function. The processor may execute the function according to the program read from the memory, or it may execute the function according to a logic circuit that has been pre-designed to execute the function. The processor may be any type of processor suitable for controlling a computer (including a cloud server), such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), DSP (Digital Signal Processor), FPGA (Field Programmable Gate Array), or ASIC (Application Specific Integrated Circuit). Processors installed in each of physically separated computers may cooperate with each other via a network such as a LAN (Local Area Network), WAN (Wide Area Network), or the Internet to perform some or all of their functions. The program may be installed into memory via a network from an external server device, or it may be distributed on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), DVD-ROM (Digital Versatile Disc Read Only Memory), or semiconductor memory, and then installed into memory from the recording medium.

[0233] The above description includes the following features: [Addendum 1] A driving data processing system comprising: a driving data acquisition unit that acquires driving data relating to the driving state of a vehicle traveling on a driving route that includes multiple road links; a detection unit that detects events relating to the vehicle for each of the road links included in the driving route based on the driving data acquired by the driving data acquisition unit; a creation unit that creates event data for each of the road links included in the driving route that shows the detection results of the events by the detection unit; and a driving result acquisition unit that acquires driving result data showing the driving results of the vehicle on the driving route, wherein the creation unit associates the created event data with the driving result data acquired by the driving result acquisition unit, and the detection unit detects driving operations by the driver of the vehicle as events.

[0234] [Note 2] A driving diagnostic system comprising: a driving data acquisition unit that acquires driving data relating to the driving state of a vehicle traveling on a route that includes multiple road links; a detection unit that detects events relating to the vehicle for each of the road links included in the route based on the driving data acquired by the driving data acquisition unit; a creation unit that creates event data for each of the road links included in the route that shows the detection results of the events by the detection unit; and an estimation unit that performs estimation processing to estimate the degree of risk when the driver of the vehicle drives the vehicle along the route based on the event data created by the creation unit and past event data which is event data corresponding to the route that was previously created by the creation unit, wherein the detection unit detects driving operations by the driver of the vehicle as events.

[0235] [Note 3] A driving data processing system comprising a processing circuit, wherein the processing circuit acquires driving data relating to the driving state of a vehicle traveling on a driving route that includes a plurality of road links, detects an event relating to the vehicle for each of the road links included in the driving route based on the acquired driving data, creates event data showing the detection result of the event for each of the road links included in the driving route, acquires driving result data showing the driving result of the vehicle on the driving route, and associates the acquired driving result data with the created event data.

[0236] [Note 4] A driving diagnostic system comprising a processing circuit, the processing circuit acquires driving data relating to the driving state of a vehicle traveling along a driving route that includes a plurality of road links, detects events relating to the vehicle for each of the road links included in the driving route based on the acquired driving data, creates event data indicating the detection result of the event for each of the road links included in the driving route, and performs estimation processing to estimate the degree of risk when the driver of the vehicle drives the vehicle along the driving route based on the created event data and past event data which are event data corresponding to the driving route created in the past.

[0237] 1 Vehicle 11 In-vehicle communication unit 12 Driving data creation unit 13 External communication unit 14, 26 Storage unit 21 Communication unit (Driving data acquisition unit, External data acquisition unit, Attribute data acquisition unit, Driving result acquisition unit) 22 Detection unit 23 Event data creation unit (Creation unit) 24 Estimation unit 25 Notification unit 51, 51A, 51B, 51C CAN bus 101 In-vehicle device 151 Server 161 Weather data management device 171 External network 181 Wireless base station device 202, 202A, 202B, 202C, 202D In-vehicle equipment 301 In-vehicle system 401 In-vehicle network 501, 502 Communication system

Claims

1. A driving data processing system comprising: a driving data acquisition unit that acquires driving data relating to the driving state of a vehicle traveling on a driving route that includes multiple road links; a detection unit that detects events relating to the vehicle for each road link based on the driving data; a creation unit that creates event data indicating the detection results of the events for each road link; and a driving result acquisition unit that acquires driving result data indicating the driving results of the vehicle on the driving route, wherein the creation unit associates the driving result data with the event data.

2. The driving data processing system according to claim 1, further comprising an external data acquisition unit that acquires external data relating to the external conditions of the vehicle, and the creation unit associates the event data with the driving result data and the external data.

3. The driving data processing system according to claim 2, wherein the external data includes at least one of the following: weather data for the region including the driving route when the vehicle travels the driving route; data relating to the status of construction at at least one of the plurality of road links; and data relating to traffic conditions at each of the road links.

4. The driving data processing system according to any one of claims 1 to 3, further comprising an attribute data acquisition unit that acquires attribute data indicating the attributes of the vehicle, and the creation unit further associates the attribute data with the event data.

5. A driving diagnostic system comprising: a driving data acquisition unit that acquires driving data relating to the driving state of a vehicle traveling along a driving route that includes multiple road links; a detection unit that detects events relating to the vehicle for each road link based on the driving data; a creation unit that creates event data for each road link showing the detection results of the events; and an estimation unit that performs estimation processing to estimate the degree of risk when the driver of the vehicle drives the vehicle along the driving route, based on the event data and past event data which is event data corresponding to the driving route and was created by the creation unit in the past than the event data.

6. The driving diagnostic system further comprises a driving result acquisition unit that acquires driving result data indicating the driving results of the vehicle along the driving route, and the estimation unit performs the estimation process based on the event data created by the creation unit and the past event data to which the driving result data is associated, according to claim 5.

7. The driving diagnostic system according to claim 6, wherein the estimation unit creates a trained model based on the past event data that outputs a prediction result of the driving result data when the event data is input, the estimation unit calculates an evaluation value for the degree of risk based on the prediction result, and the estimation unit performs the estimation process using the evaluation value.

8. A data structure for data used in estimation processing by a driving diagnostic system, wherein the estimation processing is a process for estimating the degree of driving risk by a driver of a vehicle traveling on a route that includes a plurality of road links, and the data structure comprises data indicating events related to the vehicle for each of the road links included in the route, and data indicating the results of the vehicle's driving on the route.

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