Information management device, information management method, and program

Abstract

The information management device of the embodiment includes: an acquisition unit that acquires vehicle information including location information and behavior information from each of a plurality of vehicles; an abnormality determination unit that, based on the vehicle information, determines whether the same type of abnormality is detected by a vehicle other than the vehicle that detected the abnormality within a predetermined time elapsed since the detection of the abnormality by at least one of the plurality of vehicles; an influence range estimation unit that, when the same type of abnormality is detected, estimates the influence range of the road condition abnormality based on the vehicle information; and a provision unit that provides information regarding the road condition abnormality, including the influence range, to a target vehicle among the plurality of vehicles determined based on the influence range.

Description

Technical Field

[0001] The present invention relates to an information management device, an information management method, and a program.

Background Art

[0002] Conventionally, there are known techniques for determining whether a road is congested based on probe information during vehicle travel, and techniques for identifying the location of a traffic event occurring on a road using a captured image (see, for example, Patent Documents 1 and 2).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, in the conventional technology for managing road conditions, information acquired by each vehicle is collected on the management device side, and the collected information is analyzed to manage the road conditions. Therefore, there is a time lag between the road conditions at the time of analysis completion and the actual road conditions, and there has been a problem that appropriate information may not be provided to the target vehicle in cases such as when an abnormality occurs where more immediacy is important.

[0005] One of the objectives of the present application is to provide an information management device, an information management method, and a program that can more appropriately provide information regarding road conditions to a target vehicle in order to solve the above problems.

Means for Solving the Problems

[0006] The information management device, information management method, and program according to this invention employ the following configuration. (1) An information management device according to one aspect of the present invention is an information management device comprising: an acquisition unit that acquires vehicle information including location information and behavior information from each of a plurality of vehicles; an abnormality determination unit that, based on the vehicle information, determines whether the same type of abnormality is detected by a vehicle other than the vehicle that detected the abnormality within a predetermined time elapsed since the detection of the abnormality by at least one of the plurality of vehicles; an influence range estimation unit that, when the same type of abnormality is detected, estimates the influence range of the road condition abnormality based on the vehicle information; and a provision unit that provides information regarding the road condition abnormality, including the influence range, to a target vehicle among the plurality of vehicles determined based on the influence range.

[0007] (2) In the embodiment of (1) above, the target vehicle is a vehicle that is moving toward the affected area from a location outside the affected area.

[0008] (3) In the embodiment of (1) or (2) above, the behavior information includes at least one of the following: steering behavior of the vehicle, accelerator behavior, brake behavior, yaw rate information, speed information, acceleration information, driving assistance information, wiper operation information, airbag operation information, lighting operation information, vibration information, and sound information.

[0009] (4): In the embodiment of (1) above, the abnormality determination unit determines that at least one of the following is a type of abnormality: traffic congestion, traffic accident, stopped vehicle, obstacle on the road, weather that obstructs driving, road surface freezing, sinkhole, and flooding.

[0010] (5) In the embodiment of (1) above, the abnormality determination unit determines whether or not the abnormality in the road conditions is continuing, based on at least one of the behavior information of the vehicle located within the affected area and the external environment recognition information recognized by the vehicle.

[0011] (6) In the embodiment of (1) above, the abnormality determination unit changes the predetermined time according to the degree of the behavior included in the behavior information.

[0012] (7) In the embodiment of (6) above, the abnormality determination unit shortens the predetermined time as the degree of the behavior increases, or lengthens the predetermined time as the degree of the behavior decreases.

[0013] (8) In the embodiment of (1) above, the providing unit determines whether to provide the affected area as a map area based on map information or based on road information, depending on the type of abnormality in the road conditions.

[0014] (9): In the embodiment of (1) above, the influence range estimation unit estimates the influence range of the road condition abnormality based on the vehicle information if the same type of abnormality is detected a number of times corresponding to the degree of behavior included in the behavior information before the predetermined time has elapsed.

[0015] (10): An information management method according to one aspect of the present invention is an information management method in which a computer acquires vehicle information including location information and behavior information from each of a plurality of vehicles, and when at least one of the plurality of vehicles detects an abnormality in road conditions, the computer determines whether the same type of abnormality is detected by a vehicle other than the vehicle that detected the abnormality within a predetermined time elapsed since the detection of the abnormality, and when the same type of abnormality is detected, the computer estimates the affected area of ​​the road condition abnormality based on the vehicle information, and provides information regarding the road condition abnormality, including the affected area, to a target vehicle among the plurality of vehicles determined based on the affected area.

[0016] (11): A program according to one aspect of the present invention causes a computer to acquire vehicle information including position information and behavior information from each of a plurality of vehicles, and based on the vehicle information, when at least one of the plurality of vehicles detects an abnormality in the road condition, it is determined whether the same type of abnormality is detected from a vehicle different from the vehicle that detected the abnormality until a predetermined time has elapsed since the abnormality was detected. When the same type of abnormality is detected, the influence range of the abnormality in the road condition is estimated based on the vehicle information, and information regarding the abnormality in the road condition including the influence range is provided to a target vehicle determined based on the influence range among the plurality of vehicles.

Advantages of the Invention

[0017] According to the above aspects (1) to (11), information regarding the road condition can be provided to the target vehicle more appropriately.

Brief Description of the Drawings

[0018] [Figure 1] It is a schematic configuration diagram of an information management system 1 using the information management device of the embodiment. [Figure 2] It is a configuration diagram of a vehicle system mounted on a vehicle M of the embodiment. [Figure 3] It is a configuration diagram of an information management device 200 of the embodiment. [Figure 4] It is a diagram for explaining an abnormality determination process and an influence range estimation process. [Figure 5] It is a flowchart showing an example of processing by an abnormality determination unit 240. [Figure 6] It is a flowchart showing an example of an abnormality determination and an influence range estimation process. [Figure 7] It is a flowchart showing an example of processing executed by the information management device 200 of the embodiment.

Modes for Carrying Out the Invention

[0019] Hereinafter, embodiments of an information management apparatus, an information management method, and a program of the present invention will be described with reference to the drawings. In the following, a case where the left - hand traffic regulation is applied on a road will be described. However, when the right - hand traffic regulation is applied, the left and right should be read in reverse.

[0020] [Overall Configuration] FIG. 1 is a schematic configuration diagram of an information management system 1 using the information management apparatus of the embodiment. The information management system 1 includes, for example, one or more vehicles M1 to Mn and an information management apparatus 200. Each of the vehicles M1 to Mn and the information management apparatus 200 can communicate with each other via, for example, a network NW or the like. The network NW includes, for example, a cellular network, a Wi - Fi network, Bluetooth (registered trademark), the Internet, a WAN (Wide Area Network), a LAN (Local Area Network), a public line, a provider device, a dedicated line, a wireless base station, and the like. The vehicles M1 to Mn are, for example, vehicles that have been previously contracted to receive services (for example, information - providing services) by the information management apparatus 200. Hereinafter, unless otherwise distinguished and described for each of the vehicles M1 to Mn, they will be collectively described simply as "vehicle M".

[0021] The vehicle M is, for example, a two - wheel, three - wheel, four - wheel, or other vehicle, and its power source is an internal combustion engine such as a diesel engine or a gasoline engine, an electric motor, or a combination thereof. The electric motor operates using electric power generated by a generator connected to the internal combustion engine, or the discharge power of a secondary battery or a fuel cell. The vehicle M acquires vehicle information including position information and behavior information, and transmits the acquired vehicle information to the information management apparatus 200 via the network NW at a predetermined cycle or at the timing when a request is received from the information management apparatus 200. The behavior information includes, for example, information regarding the behavior of the vehicle M (such as steering, speed, operation of in - vehicle devices, etc.) and information regarding the behavior of the passengers (such as the driver) of the vehicle M (for example, driving operations). Also, the vehicle information may include information regarding the surrounding situation recognized by the vehicle M (external - recognition information).

[0022] Furthermore, vehicle M receives information regarding abnormal road conditions from the information management device 200 and presents the received information to the occupants of vehicle M. Abnormal road conditions include, for example, traffic congestion, traffic accidents, stopped vehicles, obstacles on the road, weather conditions that hinder driving, icy roads, potholes, flooding, etc., but other events may also be included. Information regarding abnormalities includes, for example, information on the area affected by the abnormality that impacts driving (hereinafter sometimes referred to as the "area affected by the abnormality").

[0023] The information management device 200 may be, for example, a server device or a PC (Personal Computer), or a cloud server configured with cloud computing consisting of one or more information processing devices. The information management device 200 acquires vehicle information from multiple vehicles M1 to Mn, and based on the acquired vehicle information, it determines abnormalities in road conditions, etc., and if an abnormality is determined, estimates the scope of impact caused by the abnormal road conditions. The information management device 200 also provides information about the abnormal road conditions to the target vehicle determined based on the estimated scope of impact. Next, the specific configuration of the vehicle M and the information management device 200 will be described.

[0024] [vehicle] Figure 2 is a diagram of the configuration of a vehicle system mounted on vehicle M of the embodiment. The vehicle system includes, for example, a detection device 10, a communication device 20, an HMI (Human Machine Interface) 30, a vehicle sensor 40, on-board equipment 50, a driver control device 60, a driving force output device 70, a brake device 80, a steering device 90, and a vehicle control device 100. These devices and equipment are connected to each other by multiplex communication lines such as CAN (Controller Area Network) communication lines, serial communication lines, wireless communication networks, etc. The configuration shown in Figure 2 is merely an example, and some of the configuration may be omitted, or other configurations may be added.

[0025] The detection device 10 recognizes the surrounding (external) conditions of the vehicle M. The detection device 10 includes, for example, a camera, a radar device, a LiDAR (Light Detection and Ranging), an object recognition device, etc. The camera is, for example, a digital camera using a solid-state image sensor such as a CCD (Charge Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor). The camera is mounted at any location on the vehicle M and captures images of part (at least the front) or all of the omnidirectional area. The camera captures images of the area around the vehicle periodically and repeatedly. The camera may be a stereo camera. The radar device emits radio waves such as millimeter waves around the vehicle M and detects radio waves reflected by surrounding objects (reflected waves) to detect at least the position (distance and direction) of objects. The radar device is mounted at any location on the vehicle M. The radar device may detect the position and velocity of objects using the FM-CW (Frequency Modulated Continuous Wave) method. LiDAR works by irradiating the area around vehicle M with light (or electromagnetic waves with a wavelength close to light) and measuring the scattered light. Based on the time from emission to reception, LiDAR detects the distance to the target. The emitted light is, for example, pulsed laser light. LiDAR can be mounted at any location on vehicle M.

[0026] The object recognition device performs sensor fusion processing on some or all of the detection results from the camera, radar device, and LIDAR 14 to recognize the position, type, speed, etc., of objects present around the vehicle M. The detection device 10 outputs external recognition information, such as detected information (e.g., camera images) and recognition results based on the detection results, to the vehicle control device 100.

[0027] The communication device 20 communicates with the information management device 200 and other various server devices via the network NW. The communication device 20 may also communicate with other vehicles in the vicinity of vehicle M, or with communication terminals such as smartphones and tablet devices used by the occupants of vehicle M, using cellular networks, Wi-Fi networks, Bluetooth, DSRC (Dedicated Short Range Communication), etc.

[0028] The HMI30 presents various information to the occupants of vehicle M and accepts input operations from the occupants. The HMI30 includes a display device, speaker, microphone, buzzer, touch panel, switch (e.g., activation switch), key, etc. The display device is, for example, a display device (so-called multi-information display) located in the center of the instrument panel of vehicle M that displays various information about vehicle M, such as a speedometer showing the vehicle's speed or a tachometer showing the rotational speed of the internal combustion engine of vehicle M. The microphone collects not only the occupants' voices but also sounds from inside and outside the vehicle (e.g., engine noise of vehicle M, sounds around the vehicle, and alarm sounds).

[0029] The vehicle sensor 40 includes a vehicle speed sensor for detecting the speed of the vehicle M, an acceleration sensor (G sensor) for detecting acceleration, a yaw rate sensor for detecting yaw rate (for example, the angular velocity of rotation around the vertical axis passing through the center of gravity of the vehicle M), and an orientation sensor for detecting the orientation of the vehicle M. The vehicle sensor 40 may also be provided with a position sensor for detecting the position of the vehicle M. The position sensor is, for example, a sensor that acquires position information (latitude and longitude information) from a GPS (Global Positioning System) device. Alternatively, the position sensor may be a sensor that acquires position information using a GNSS (Global Navigation Satellite System) receiver of a navigation device. The vehicle sensor 40 may also be provided with a vibration sensor for detecting vibrations of the vehicle M, an operation sensor for detecting the operating status of each device included in the in-vehicle equipment 50, a sensor for detecting specific weather conditions such as rain, fog, or snow, or illuminance in the surroundings, a temperature sensor, and the like. The results detected by the vehicle sensor 40 are output to the vehicle control device 100.

[0030] The in-vehicle equipment 50 is a device mounted in the vehicle M and capable of operating in accordance with the behavior of the vehicle M or the operating instructions of the occupants. The in-vehicle equipment 50 includes, for example, a wiper device 51, an airbag device 52, a lighting device 53, a navigation device 54, a driver assistance device 55, etc. In addition, the in-vehicle equipment 50 may include devices other than those described above (for example, a drive recorder, a driver monitoring camera, audio equipment, etc.).

[0031] The wiper device 51 operates or stops the wipers to remove raindrops and other debris from the windshield, etc., based on, for example, the occupant's instructions or the vehicle sensor 40's detection of surrounding rain. The airbag device 52 inflates airbags located in predetermined positions in the passenger compartment when the vehicle M's behavior meets predetermined conditions (e.g., sudden deceleration), based on, for example, the detection results of the acceleration sensor. The lighting device 53 includes, for example, headlights, fog lights, hazard lights, and interior lights. The lighting device 53 turns on or flashes the target lamp based on, for example, the occupant's instructions or the vehicle sensor 40's detection results of surrounding fog, illuminance, etc.

[0032] The navigation device 54 includes, for example, a GNSS receiver, a navigation HMI, and a route determination unit. The navigation device 54 stores map information in a storage device such as an HDD (Hard Disk Drive) or flash memory. The GNSS receiver determines the position of the vehicle M based on signals received from GNSS satellites. The position of the vehicle M may be determined or supplemented by an INS (Inertial Navigation System) that utilizes the output of the vehicle sensor 40. The navigation HMI includes a display device, speaker, touch panel, keys, etc. The navigation HMI may be partially or completely shared with the HMI 30 described above. The route determination unit determines, for example, a route (hereinafter referred to as the route on the map) from the position of the vehicle M determined by the GNSS receiver (or any input location) to the destination input by the occupant using the navigation HMI, by referring to map information. The map information is, for example, information in which the road shape is represented by links indicating roads and nodes connected by links. Map information may include information such as road curvature and POI (Point of Interest) information, and may also include information about road shape and road structures. Road shape information may include, for example, branches and merges, tunnels (entrances and exits), curved roads, curvature of the road or road markings, radius of curvature, number of lanes, width, and gradient. Information about road structures may include information such as the type of road structure, location, orientation relative to the road extension direction, size, shape, and color. Map information may be updated as needed by the communication unit 210 communicating with an external device. The navigation device 54 provides route guidance using a navigation HMI based on the route on the map.

[0033] The driver assistance device 55 controls either the steering or the speed of the vehicle M, or both, through control by the driving control unit 120, which will be described later, in order to perform driving control by automatic driving. Driving control includes, for example, emergency braking control and collision avoidance steering control to avoid contact between the vehicle M and an object. Driving control may also include various other driving control systems such as LKAS (Lane Keeping Assistance System), ALC (Auto Lane Changing), and ACC (Adaptive Cruise Control System).

[0034] The driver controls 60 include, for example, a brake pedal, an accelerator pedal, a steering wheel, turn signal control switches, a shift lever, and other controls. The driver controls 60 are equipped with sensors that detect the amount of operation or whether or not an operation is performed, and the detection results are output to some or all of the driving force output device 70, the brake device 80, and the steering device 90, or to the vehicle control device 100.

[0035] The driving force output device 70 outputs driving force (torque) to the drive wheels for the vehicle M to move. The driving force output device 70 includes, for example, a combination of an internal combustion engine, an electric motor, and a transmission mounted on the vehicle M, and an ECU (Electronic Control Unit) that controls them. The ECU controls the above configuration according to information input from the driver assistance device 55 or information input from the accelerator pedal of the driver control device 60.

[0036] The brake system 80 includes, for example, a brake caliper, a cylinder that transmits hydraulic pressure to the brake caliper, an electric motor that generates hydraulic pressure in the cylinder, and a brake ECU. The brake ECU controls the electric motor according to information input from the driver assistance device 55 or from the brake pedal of the driver control device 60, so that brake torque corresponding to the braking operation is output to each wheel. The brake system 80 may be equipped with a backup mechanism that transmits the hydraulic pressure generated by the operation of the brake pedal to the cylinder via a master cylinder. The brake system 80 is not limited to the configuration described above, and may also be an electronically controlled hydraulic brake system that controls an actuator according to information input from the driver assistance device 55 to transmit hydraulic pressure from the master cylinder to the cylinder.

[0037] The steering system 90 includes, for example, a steering ECU and an electric motor. The electric motor, for example, applies force to a rack and pinion mechanism to change the direction of the steering wheels. The steering ECU drives the electric motor to change the direction of the steering wheels according to information input from the driver assistance device 55 or from the steering wheel of the driver control device 60.

[0038] The vehicle control device 100 includes, for example, an acquisition unit 110, a driving control unit 120, a management unit 130, an HMI control unit 140, and a storage unit 150. The acquisition unit 110, the driving control unit 120, the management unit 130, and the HMI control unit 140 are realized, for example, by a hardware processor such as a CPU (Central Processing Unit) executing a program (software). Some or all of these components may be realized by hardware (including circuitry) such as an LSI (Large Scale Integration), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), or GPU (Graphics Processing Unit), or by the cooperation of software and hardware. The program may be stored in advance in a storage device (a storage device equipped with a non-transient storage medium) such as the HDD or flash memory of the vehicle control device 100, or it may be stored in a removable storage medium such as a DVD or CD-ROM, and installed in the HDD or flash memory of the vehicle control device 100 when the storage medium (non-transient storage medium) is inserted into the drive device.

[0039] The memory unit 150 is implemented using the various storage devices mentioned above, or an SSD (Solid State Drive), EEPROM (Electrically Erasable Programmable Read Only Memory), ROM (Read Only Memory), or RAM (Random Access Memory), etc. The memory unit 150 stores, for example, programs and various other information. The memory unit 150 may also store, for example, the map information mentioned above, or a vehicle ID or occupant ID.

[0040] The acquisition unit 110 acquires various information from the detection device 10, communication device 20, HMI 30, vehicle sensor 40, in-vehicle equipment 50, driver control unit 60, driving force output device 70, brake device 80, steering device 90, driving control unit 120, and management unit 130. The acquisition unit 110 may also store the acquired information in the storage unit 150, and may generate vehicle information including location information and behavior information based on the acquired information and other information stored in the storage unit 150. Location information is acquired by the location sensor and navigation device 54. Of the behavior information, the behavior of the vehicle M is generated based on the detection results of the vehicle sensor 40 and the working status of the in-vehicle equipment, etc., and the behavior of the occupants is generated based on information received by the HMI 30 and driver control unit 60, etc. Behavioral information includes, for example, at least one of the following: steering behavior of vehicle M (steering angle or steering wheel operation amount), accelerator behavior (accelerator operation amount), brake behavior (brake operation amount), yaw rate information, speed information, acceleration information, driver assistance information (operation information of driver assistance device 55), wiper operation information, airbag operation information, lighting operation information, vibration information, and sound information. In addition to position information and behavioral information, vehicle information may include external recognition information such as camera images captured by the camera of the detection device 10, sound information collected by the microphone of the HMI 30, detection information acquired by other sensors, time information when various information was acquired, vehicle ID, occupant ID, etc.

[0041] The driving control unit 120 controls the driving force output device 70, the brake device 80, and the steering device 90 so that the vehicle M moves in accordance with the driver's operation, based on the information obtained from the driver control device 60 and the information obtained by the acquisition unit 110. The driving control unit 120 also activates the driver assistance device 55 and the like so that predetermined driving control is performed based on the surrounding recognition results from the detection device 10.

[0042] The management unit 130 manages the operating status of the entire vehicle system. For example, the management unit 130 manages the driving status of the vehicle M (e.g., steering behavior, accelerator behavior, brake behavior) and the operating status of the in-vehicle equipment 50 (e.g., driver assistance information, wiper operation information, airbag operation information, lighting operation information), etc. The information managed by the management unit 130 may be stored in the storage unit 150 or output to the acquisition unit 110. The management unit 130 also transmits the vehicle information generated by the acquisition unit 110 to the information management device 200 via the communication device 20 at predetermined intervals or when requested by the information management device 200.

[0043] The HMI control unit 140 notifies the occupant of predetermined information via the HMI 30. The predetermined information includes, for example, information related to the driving of vehicle M, such as information regarding the status of vehicle M and information regarding driving control. Information regarding the status of vehicle M includes, for example, the speed of vehicle M, engine speed, and shift position. The predetermined information may also include information regarding abnormal road conditions provided by the information management device 200. The predetermined information may also include, for example, the current location and destination of vehicle M, and information regarding the remaining fuel level.

[0044] For example, the HMI control unit 140 may generate an image containing the predetermined information described above and display the generated image on the display device of the HMI 30, or it may generate audio indicating the predetermined information and output the generated audio from the speaker of the HMI 30. The HMI control unit 140 may also output images and audio provided by the information management device 200 to the HMI 30. Furthermore, the HMI control unit 140 may output information received by the HMI 30 to the acquisition unit 110, the driving control unit 120, the management unit 130, etc.

[0045] [Information management device] Figure 3 is a configuration diagram of an information management device 200 according to an embodiment. The information management device 200 includes, for example, a communication unit 210, an acquisition unit 220, a management unit 230, an anomaly determination unit 240, an impact range estimation unit 250, a provision unit 260, and a storage unit 270. The acquisition unit 220, the anomaly determination unit 240, the impact range estimation unit 250, and the provision unit 260 are implemented, for example, by a hardware processor such as a CPU executing a program (software). Furthermore, some or all of these components may be implemented by hardware (including circuitry) such as LSIs, ASICs, FPGAs, and GPUs, or by the cooperation of software and hardware. The program may be stored in advance in a storage device such as an HDD or flash memory (a storage device equipped with a non-transient storage medium) provided by the information management device 200, or it may be stored in a removable storage medium such as a DVD or CD-ROM (a non-transient storage medium), and installed in the HDD or flash memory of the information management device 200 when the storage medium is inserted into a drive device provided by the information management device 200.

[0046] The storage unit 270 may be implemented by the various storage devices described above, or by an SSD, EEPROM, ROM, RAM, etc. The storage unit 270 stores, for example, a vehicle information database 272, map information 274, a program, and various other information. The vehicle information database 272 stores vehicle information transmitted from each vehicle M1 to Mn. In this case, time-series data for a predetermined period may be stored for each vehicle ID. The map information 274 may be the same as the map information stored in the navigation device 54 or the storage unit 150, or it may be high-resolution map information. The map information 274 may be updated as needed by the communication unit 210 communicating with an external device.

[0047] The communication unit 210 communicates with vehicles M1 to Mn and other external devices via the network NW. For example, the communication unit 210 receives vehicle information from vehicles M1 to Mn. The communication unit 210 also transmits information regarding abnormal road conditions to the target vehicle among vehicles M1 to Mn that corresponds to the affected area.

[0048] The acquisition unit 220 acquires vehicle information from the information received by the communication unit 210. The acquisition unit 220 may also request vehicle information from a predetermined vehicle among multiple vehicles and acquire the vehicle information from the requested vehicle. The acquired information may be stored in the vehicle information DB 272 of the storage unit 270. The acquisition unit 220 may also acquire information provided by other external devices via the network NW.

[0049] The management unit 230 manages all components of the information management device 200. For example, the management unit 230 manages the operating status of the abnormality detection unit 240, the impact range estimation unit 250, the provision unit 260, etc. The management unit 230 may also manage the registration of vehicles (contracted vehicles) that provide services. Furthermore, the management unit 230 performs authentication processing in advance based on vehicle IDs, occupant IDs, and other authentication information, and provides services to vehicles and occupants that have been registered in advance.

[0050] The abnormality determination unit 240 determines whether a vehicle has detected an abnormality in road conditions based on vehicle information acquired by the acquisition unit 220. The abnormality determination unit 240 may also determine an abnormality such as a malfunction of vehicle M. Furthermore, based on behavioral information, if at least one of the multiple vehicles detects an abnormality in road conditions, the abnormality determination unit 240 determines whether the same type of abnormality has been detected by a different vehicle within a predetermined time elapsed since the abnormality was detected. Details of the functions of the abnormality determination unit 240 will be described later.

[0051] The impact range estimation unit 250 estimates the impact range of the road condition anomaly based on location information and behavior information when the same type of anomaly is detected in a vehicle different from the vehicle in which the anomaly determination unit 240 detected an anomaly. The details of the function of the impact range estimation unit 250 will be described later.

[0052] The information provision unit 260 provides various information to the vehicle M. The information provision unit 260 includes, for example, a determination unit 262 and a generation unit 264. The determination unit 262 determines the target vehicle to provide information about abnormal road conditions based on the area of ​​influence estimated by the area of ​​influence estimation unit 250. For example, the determination unit 262 determines a vehicle that is moving from a location outside the area of ​​influence toward the area of ​​abnormal influence as a target vehicle. Furthermore, in addition to (or instead of) the above conditions, the determination unit 262 may determine the target vehicle according to the distance from the area of ​​influence, or according to the lane each vehicle is traveling in.

[0053] Furthermore, the decision unit 262 determines whether to provide the affected area as a map area based on map information 274 or as road information, depending on the type of road condition anomaly. The type of anomaly is determined by the anomaly determination unit 240. The types of anomalies include, for example, at least one of the following: traffic congestion, traffic accidents, stopped vehicles, obstacles on the road, weather that obstructs driving (e.g., heavy rain, thunderstorms, typhoons, fog, heavy snow, etc.), road freezing, sinkholes, and flooding. For example, if the type of anomaly is weather that obstructs driving, road freezing, or flooding, the decision unit 262 decides to provide the affected area as a map area based on map information 274. Also, if the type of anomaly is traffic congestion, traffic accidents, stopped vehicles, obstacles on the road, or sinkholes, the decision unit 262 decides to provide the affected area as road information, since it is expected that the affected area can be identified to some extent. This allows for the provision of information about the road where the accident occurred if the type of anomaly is a traffic accident, and for area information regardless of the road if it is heavy rain. Therefore, it is possible to provide more appropriate information about abnormal road conditions.

[0054] The generation unit 264 generates information (information regarding abnormal road conditions) for the target vehicle determined by the determination unit 262, including, for example, road conditions (type of abnormality, etc.) and the affected area. The generation unit 264 may also generate information other than information regarding abnormal road conditions (for example, information indicating that the abnormal road conditions have been resolved, detour route information, and response information to inquiries from the occupants). The generation unit 264 transmits the generated information to the target vehicle to provide it to the occupants.

[0055] [Anomaly detection unit and influence range estimation unit] Next, the details of the abnormality determination process by the abnormality determination unit 240 and the influence range estimation process by the influence range estimation unit 250 will be explained. Figure 4 is a diagram illustrating the abnormality determination process and the influence range estimation process. In the example in Figure 4, a road RD1 is shown that extends along the X-axis in the figure and includes a lane L1 that can travel in the X-axis direction and a lane (opposing lane) L2 that can travel in the opposite direction (-X-axis direction) to lane L1. Lane L1 is demarcated by road markings LL and CL, and lane L2 is demarcated by road markings CL and RL. In the example in Figure 4, vehicles M1 to M4 are traveling in lane L1 at speeds VM1 to VM4, respectively, and vehicles M5 to M8 are traveling in lane L2 at speeds VM5 to VM8, respectively. Vehicles M1 to M8 are also assumed to be contract vehicles that can receive information provision services from the information management device 200.

[0056] In the example shown in Figure 4, each of the vehicles M1 to M8 transmits vehicle information, including location information and behavior information, to the information management device 200 at predetermined intervals. The abnormality determination unit 240 uses the location information included in the vehicle information transmitted from the vehicles M1 to M8 to refer to the map information 274 and identifies the road RD1 (or lanes L1, L2) on which the vehicles M1 to M8 are traveling. In this case, the abnormality determination unit 240 may also obtain the shape of road RD1, etc., from the map information 274. The abnormality determination unit 240 then determines whether or not an abnormality in the road conditions identified based on the behavior information included in the vehicle information is detected.

[0057] For example, the abnormality determination unit 240 determines that the vehicle M that transmitted the behavior information has detected an abnormality in road conditions if the information contained in the behavior information satisfies predetermined abnormality determination conditions, and determines that no abnormality has been detected if the abnormality determination conditions are not met. The abnormality determination conditions may include, for example, conditions related to the speed and acceleration / deceleration of the vehicle M (in other words, the occupant's accelerator and brake operations), conditions related to the steering of the vehicle M (steering behavior), and conditions related to the operation of predetermined in-vehicle equipment 50.

[0058] Figure 5 is a flowchart showing an example of processing by the abnormality detection unit 240. In the example in Figure 5, the abnormality detection unit 240 determines whether the difference between the vehicle speed VM included in the behavior information and the reference speed is greater than or equal to a threshold (step S100). The reference speed may be, for example, the speed limit or legal speed of road RD1, or a predetermined fixed speed. If it is determined that the difference between the speed VM and the reference speed is not greater than or equal to the threshold, the abnormality detection unit 240 determines, based on the acceleration information included in the behavior information, whether the deceleration rate of the vehicle M over a predetermined time is greater than or equal to a threshold (step S110).

[0059] If the deceleration rate is determined not to be above a threshold, the abnormality determination unit 240 determines whether the steering angle of the vehicle M is above a predetermined angle based on the steering behavior included in the behavior information (step S120). In step S120, the abnormality determination unit 240 may also determine whether the degree of change in the steering angle over a predetermined time is above a threshold. Furthermore, if the road RD1 being traveled is a curved road, the steering angle will increase in line with the curvature. For this reason, the abnormality determination unit 240 may use the deviation angle of the steering angle with respect to the extension direction of road RD1 obtained from the map information 274 instead of the steering angle.

[0060] If the abnormality determination unit 240 determines that the steering angle is not greater than or equal to a predetermined angle, it determines whether the driver assistance device 55 has been activated based on the driver assistance information included in the behavior information (step S130). In step S130, the abnormality determination unit 240 may also determine whether a predetermined control by the driver assistance device 55 (for example, emergency brake control, collision avoidance steering control) has been activated. If the abnormality determination unit 240 determines that the driver assistance device 55 has not been activated, it determines that the vehicle M that transmitted the behavior information being determined has not detected any abnormal road conditions (step S140). If the abnormality determination unit 240 determines that the driver assistance device 55 has been activated, it determines that the vehicle has detected an abnormal road condition (step S150). Furthermore, if the difference between the vehicle M's speed VM and the reference speed is determined to be greater than or equal to a threshold in step S100, if the deceleration is determined to be greater than or equal to a threshold in step S110, or if the steering angle is determined to be greater than or equal to a predetermined angle in step S120, then it is determined that there is an abnormality in the road conditions. After the processing in step S150, the abnormality determination unit 240 identifies the type of abnormality in the road conditions (step S160). This completes the processing of this flowchart.

[0061] Note that each of the processes in steps S100 to S130 may be executed in an order different from the order shown in Figure 5. Also, the abnormality determination unit 240 may perform a determination based on all abnormality determination conditions regardless of the determination results in each of the processes in steps S100 to S130, and identify one or more types of abnormalities. In addition, the abnormality determination conditions may include, in addition to (or instead of) the conditions in steps S100 to S130 described above, whether or not other in-vehicle equipment (for example, the wiper device 51, the airbag device 52, the lighting device 53) has been activated, whether or not the vibration of the vehicle M is above a threshold, or whether or not a predetermined sound (warning sound) has been detected.

[0062] For example, if the abnormality determination unit 240 detects that an occupant has turned on the fog lights of the lighting device 53 or activated the fog sensor in the occupant operation included in the vehicle information, it analyzes the camera image captured by the vehicle M to check the weather conditions. If fog is detected from the analysis results, it determines that an abnormality in road conditions has been detected, and if fog is not detected, it determines that no abnormality has been detected. For fog detection, a well-known image detection algorithm capable of detecting the state of fog may be used. In addition, the abnormality determination unit 240 may also determine whether or not an abnormality of road surface freezing has been detected based on the distance from when the occupant applies the brakes until the vehicle M comes to a stop, as another abnormality determination condition. In this case, the abnormality determination unit 240 may also include the camera image analysis results as an abnormality determination condition.

[0063] Furthermore, if the abnormality detection unit 240 determines that it has detected an abnormality in at least one vehicle (or part of a vehicle) among vehicles M1 to M8, it sets that abnormality as a provisional state and manages it. A provisional state is a state in which it is predicted that there is a possibility that no abnormality has actually occurred on road RD1, and at this point, the prediction of an abnormality in the road condition is not confirmed. Then, if the abnormality detection unit 240 determines that an abnormality of the same type (which may include a predetermined similar type) has been detected in a vehicle other than the vehicle that detected the abnormality (other vehicles) within a predetermined time after setting it as a provisional state, it sets the provisional state abnormality to a confirmed state.

[0064] The impact range estimation unit 250 estimates the impact range based on the location information of the vehicle M that detected the anomaly once an anomaly is confirmed. For example, the impact range estimation unit 250 refers to map information 274 based on the location information of vehicles M that have detected the same type of anomaly and estimates the area within a predetermined distance from the vehicle M that detected the anomaly as the impact range. For example, the impact range estimation unit 250 estimates the area within a predetermined distance centered on the vehicle M that detected the anomaly in a provisional state as the impact range. In this case, the predetermined range includes the locations of at least other vehicles M that have detected the same type of anomaly. Alternatively, the impact range estimation unit 250 may set an impact range centered on each of the vehicles that have detected the same type of anomaly and estimate the area that includes all of these impact ranges as the final impact range.

[0065] Furthermore, the impact range estimation unit 250 may estimate the impact range based on the road or lane in which the vehicle M that detected the anomaly is traveling. For example, in the situation shown in Figure 4, if an anomaly is first detected in vehicle M1, and then the same type of anomaly is detected in vehicle M2 within a predetermined time elapsed, the impact range estimation unit 250 estimates the area AR1 of lane L1 from the position of vehicle M1 to the position of vehicle M2 as the impact range due to the anomaly. Furthermore, if the same type of anomaly is detected in vehicle M7 in addition to vehicle M2 within the predetermined time elapsed, the impact range estimation unit 250 estimates the area AR2 of road RD1 including the positions of vehicles M1, M2, and M7 as the impact range due to the anomaly. This makes it possible to estimate the impact range more accurately based on road information. Therefore, for example, lanes that are not affected, such as oncoming lanes, branching lanes, or lanes heading in other directions at intersections, located within a predetermined distance from the vehicle that detected the anomaly, can be excluded.

[0066] Furthermore, if the abnormality detection unit 240 detects an abnormality set as a provisional state, it may obtain the position of vehicle M that has detected the same type of abnormality from the behavior information of surrounding vehicles within a predetermined range from the vehicle that detected the abnormality, and estimate the range of influence of the abnormality based on the acquired position information (distribution, etc.) of vehicle M.

[0067] Figure 6 is a flowchart illustrating an example of anomaly detection and impact range estimation processing. Note that the example in Figure 6 shows the processing after an anomaly, which is set as a provisional state in the detection process shown in Figure 5, is detected. In the example in Figure 6, the acquisition unit 220 and the anomaly detection unit 240 acquire behavioral information of other vehicles within a predetermined range from the vehicle that detected the provisional state anomaly (step S200). In this case, the acquisition unit 220 compares the location information of the vehicle that detected the anomaly with the location information of the other vehicles and acquires behavioral information of other vehicles within a predetermined distance. For example, in the situation shown in Figure 4, if an anomaly is detected in vehicle M1, behavioral information of vehicles M2, M3, M4, M7, and M8, which are within a predetermined distance from vehicle M1, is acquired. Alternatively, the acquisition unit 220 may refer to map information 274 to identify the road and lane on which vehicle M, which detected the provisional state anomaly, is traveling, and acquire behavioral information of other vehicles (more specifically, following vehicles) traveling in the identified lane. For example, in the situation shown in Figure 4, if an abnormality is detected in vehicle M1, behavioral information of vehicles M2 to M4, which are traveling in the same lane L1 as vehicle M1 and following behind vehicle M1, will be acquired.

[0068] Next, the abnormality determination unit 240 determines whether the acquired behavior information includes behavior indicating the same type of abnormality (step S210). If it determines that behavior indicating the same type of abnormality is included, the abnormality determination unit 240 manages the vehicle corresponding to that behavior information as a vehicle affected by the same type of abnormality (step S220). Next, the impact range estimation unit 250 estimates the impact range based on the location information (distribution) of the vehicles affected by the same type of abnormality (step S230). This completes the processing of this flowchart. Note that if it is determined in step S210 that the behavior information does not include behavior indicating the same type of abnormality, the abnormality is not confirmed, and the process ends without estimating the impact range. The above processing makes it possible to perform abnormality determination more efficiently and quickly than making a determination using all the behavior information of vehicles M1 to M8. Therefore, it is possible to achieve more immediate road information management.

[0069] After the area of ​​influence is estimated by the area of ​​influence estimation unit 250, the determination unit 262 determines which vehicles will receive the information, and the information is provided to the determined vehicles. For example, in the situation shown in Figure 4, if the area of ​​influence is area AR1, information regarding the abnormality of lane L1 is provided to vehicles M1 and M2 that are traveling toward area AR1. This allows vehicles M3 and M4 to receive more real-time road information before detecting the abnormality. The providing unit 260 may also refer to map information 274 using the location information of vehicles M3 and M4 that have not yet entered the area of ​​influence, and if there is an alternative route that bypasses the area of ​​influence, it may provide information about that alternative route. This allows for the provision of more appropriate information to each vehicle, enables vehicles M3 and M4 to take an alternative route, and can suppress the expansion of the area of ​​influence of the abnormality (e.g., the area of ​​congestion). The providing unit 260 may also provide information regarding the abnormality of lane L1 to vehicles M1 and M2 that are traveling within area AR1.

[0070] Here, for the anomaly determination by the anomaly determination unit 240 and the estimation of the estimated range by the influence range estimation unit 250 described above, AI (Artificial Intelligence) functions such as machine learning (neural networks) and deep learning may be used. For example, the anomaly determination unit 240 obtains the determination result for each vehicle by inputting the vehicle information of vehicles M1 to M8 into a pre-trained model that has been trained in advance to output a determination result of whether or not vehicle M has detected an anomaly (and also the level of the anomaly) when vehicle information (behavior information, sensor data) is input. The influence range estimation unit 250 obtains the influence range by inputting the vehicle information of the vehicle that has detected an anomaly in a provisional state and the vehicle information of the other vehicles into a pre-trained model that has been trained in advance to output the influence range based on the trend (similarity) of the vehicle state when the vehicle information of the vehicle that has detected an anomaly and the vehicle information of other vehicles that have not been determined to have detected an anomaly are input. The pre-trained model described above may be stored in the memory unit 270 or may be obtained from an external source via the communication unit 210.

[0071] Furthermore, the abnormality determination unit 240 may determine whether the abnormal road conditions are continuing based on vehicle information, which includes at least one of the behavior information of the vehicle M located within the affected area and the external environment recognition information recognized by the vehicle M. In this case, the abnormality determination unit 240 may, for example, request vehicle information (more specifically, camera images of the surroundings included in the external environment recognition information) from vehicles located within the affected area, and determine whether the abnormality is continuing based on whether an abnormality has been detected based on the camera images obtained from the requested vehicle. The abnormality determination unit 240 may determine whether the abnormality is continuing based solely on the behavior information, or it may use both the behavior information and the external environment recognition information to more accurately determine whether the abnormality is continuing. In addition, the affected area estimation unit 250 may reduce or expand the affected area at predetermined intervals based on the determination result of whether the abnormality is continuing. This allows for the provision of more real-time information to the vehicle M. Furthermore, the provision unit 260 may provide information regarding the continuation of the abnormality to the target vehicle. This allows the occupants to also be provided with information regarding the continuation of the abnormality.

[0072] Furthermore, the abnormality determination unit 240 may change the predetermined time from detecting an abnormality set as a provisional state to determining whether the same type of abnormality has been detected in other vehicles, according to the degree of behavior (degree of change, intensity) included in the behavior information. In this case, the abnormality determination unit 240 shortens the predetermined time the greater the degree of behavior of vehicle M, or lengthens the predetermined time the less the degree of behavior. This allows for more appropriate abnormality determination and shortens the time from the provisional state to the confirmed state of the abnormality, depending on the degree of behavior.

[0073] Furthermore, depending on the degree of the behavior described above, the number of detections of the same type of abnormality to confirm the abnormality set as a provisional state may be adjusted. In this case, the abnormality determination unit 240 reduces the number of detections for a greater degree of behavior, or increases the number of detections for a smaller degree of behavior. The impact range estimation unit 250 estimates the impact range of the road condition abnormality based on vehicle information if the same type of abnormality is detected a number of times corresponding to the degree of behavior included in the behavior information within a predetermined time elapsed since the provisional state of the abnormality was set. This enables more accurate abnormality determination and estimation of a more appropriate impact range.

[0074] Furthermore, the impact range estimation unit 250 may adjust the impact range according to the type of anomaly. For example, if the type of anomaly is road surface freezing, the impact range estimation unit 250 estimates the impact range based on the position of the vehicle that detected the anomaly and the distance (freezing level) from the braking operation of each vehicle until it stops. For example, in the case of road surface freezing anomaly, setting the impact range to be larger compared to other types of anomalies can provide other vehicles with a more appropriate impact range that takes into account the effects of slipping.

[0075] Furthermore, if the abnormality detection unit 240 determines that there is no abnormality (the abnormality has been resolved) in its continuous abnormality detection, the provision unit 260 may provide information indicating that the abnormality has been resolved to the vehicle that provided information regarding the abnormal road conditions. This allows the occupants of vehicle M to understand the current road conditions more accurately.

[0076] [Processing flow] Figure 7 is a flowchart showing an example of processing performed by the information management device 200 of the embodiment. In the processing shown in Figure 7, the acquisition unit 220 acquires vehicle information, including location information, behavior information, and occupant operation information, from multiple vehicles (step S300). Next, the abnormality determination unit 240 determines whether or not it has detected an abnormality in the road conditions based on the vehicle information (step S310). If it determines that an abnormality in the road conditions has been detected, it sets a provisional abnormality state (step S320), and determines whether or not it has detected the same type of abnormality from the vehicle information of other vehicles within a predetermined time elapsed since the setting (step S330). If it determines that the same type of abnormality has been detected, it sets the provisional abnormality state to a confirmed abnormality state, and the impact range estimation unit 250 estimates the impact range due to the abnormality (step S340).

[0077] Next, the information provision unit 260 determines which vehicles to provide information about abnormal road conditions to (step S350), generates information to be provided for each determined vehicle (step S360), and transmits the generated information to the target vehicles (step S370). This completes the processing of this flowchart. Furthermore, if it is determined in the processing of step S310 that no abnormal road conditions have been detected, or if it is determined in the processing of step S330 that no abnormality of the same type has been detected from other vehicles within the processing time, the processing of this flowchart also completes.

[0078] [Differentiation] In the information management system 1 described above, at least some of the functions of the vehicle M may be performed by the information management device 200, and some of the functions of the information management device 200 may be performed by the vehicle M. For example, the abnormality determination for each vehicle by the abnormality determination unit 240 may be performed on the vehicle side. In this case, the abnormality determination result is transmitted from the vehicle M to the information management device 200, and the information management device 200 performs a confirmation determination of abnormality detection and estimates the affected area based on the abnormality determination result for each vehicle and the vehicle's location information. This reduces the processing load on the information management device 200.

[0079] According to the embodiments described above, the information management device 200 includes an acquisition unit 220 that acquires vehicle information including location information and behavior information from each of the multiple vehicles; an abnormality determination unit 240 that, based on the vehicle information, determines whether the same type of abnormality is detected in a different vehicle from the vehicle that detected the abnormality within a predetermined time elapsed since the abnormality was detected in at least one of the multiple vehicles; an impact range estimation unit 250 that estimates the impact range of the road condition abnormality based on the vehicle information when the same type of abnormality is detected; and a provision unit 260 that provides information on the road condition abnormality, including the impact range, to a target vehicle among the multiple vehicles determined based on the impact range. By including these components, information on road conditions can be provided to the target vehicle more appropriately.

[0080] For example, according to the embodiment, when one or some of multiple vehicles detect an abnormality in road conditions, a provisional abnormality (provisional state of abnormality) is set, and the provisional abnormality is confirmed by determining whether the same type of vehicle behavior is detected from a different vehicle within a predetermined time thereafter. Therefore, the affected area can be estimated even in the initial stages of an abnormality such as congestion, and abnormal road conditions can be provided to target vehicles early, even in situations where immediacy is required. For example, according to the embodiment, by determining the abnormality in road conditions and the affected area from vehicle behavior information and transmitting it to other vehicles, abnormalities such as congestion and weather that affect driving can be communicated to other vehicles in a timely manner. Furthermore, according to the embodiment, the affected area of ​​the abnormality can be adjusted based on information between nearby vehicles, and vehicles moving towards that area can be designated as target vehicles and notified earlier to avoid the effects of the abnormality.

[0081] The embodiments described above can be expressed as follows. A storage medium that stores computer-readable instructions, A processor connected to the storage medium, The processor executes the computer-readable instructions to: Vehicle information, including location and behavior information, is obtained from each of multiple vehicles. Based on the vehicle information, if at least one of the multiple vehicles detects an abnormality in road conditions, it is determined whether a different vehicle detects the same type of abnormality within a predetermined time elapsed since the detection of the abnormality. When the same type of abnormality is detected, the extent of the impact of the road condition abnormality is estimated based on the vehicle information. To provide the target vehicle, determined based on the affected area, with information regarding the abnormal road conditions, including the affected area, among the multiple vehicles: Information management device.

[0082] Although embodiments for carrying out the present invention have been described above using examples, the present invention is not limited in any way to these embodiments, and various modifications and substitutions can be made without departing from the spirit of the present invention. [Explanation of symbols]

[0083] 1...Information management system, 10...Detection device, 20...Communication device, 30...HMI, 40...Vehicle sensor, 50...In-vehicle equipment, 60...Driver's control unit, 70...Driving force output device, 80...Brake device, 90...Steering device, 100...Vehicle control device, 110, 220...Acquisition unit, 120...Driving control unit, 130, 230...Management unit, 140...HMI control unit, 150, 270...Storage unit, 200...Information management device, 210...Communication unit, 240...Anomaly determination unit, 250...Influence range estimation unit, 260...Provision unit, 262...Decision unit, 264...Generation unit, M...Vehicle

Claims

1. An acquisition unit that acquires vehicle information including location information and behavior information from each of multiple vehicles, Based on the vehicle information, if at least one of the multiple vehicles detects an abnormality in road conditions, an abnormality determination unit determines whether or not the same type of abnormality is detected by a different vehicle from the vehicle that detected the abnormality within a predetermined time elapsed since the detection of the abnormality. When the same type of abnormality is detected, the system includes an impact range estimation unit that estimates the affected area of ​​the road condition abnormality based on the vehicle information, A providing unit that provides information regarding abnormal road conditions, including the affected area, to a target vehicle among the multiple vehicles, which is determined based on the affected area. An information management device equipped with the following features.

2. The aforementioned vehicle is a vehicle moving from a location outside the affected area toward the affected area. The information management device according to claim 1.

3. The behavioral information includes at least one of the following: steering behavior, accelerator behavior, brake behavior, yaw rate information, speed information, acceleration information, driver assistance information, wiper operation information, airbag operation information, lighting operation information, vibration information, and sound information of the vehicle. The information management device according to claim 1 or 2.

4. The abnormality detection unit determines that at least one of the following is a type of abnormality: traffic congestion, traffic accidents, stopped vehicles, obstacles on the road, weather conditions that hinder driving, icy roads, sinkholes, and flooding. The information management device according to claim 1.

5. The abnormality determination unit determines whether or not the abnormal road condition is continuing, based on at least one of the behavior information of vehicles within the affected area and the external environment recognition information recognized by the vehicles. The information management device according to claim 1.

6. The abnormality determination unit changes the predetermined time according to the degree of the behavior included in the behavior information. The information management device according to claim 1.

7. The abnormality determination unit shortens the predetermined time as the degree of the behavior increases, or lengthens the predetermined time as the degree of the behavior decreases. The information management device according to claim 6.

8. The providing unit determines, depending on the type of abnormality in the road conditions, whether to provide the affected area as a map area based on map information or based on road information. The information management device according to claim 1.

9. The influence range estimation unit estimates the influence range of the road condition abnormality based on the vehicle information if the same type of abnormality is detected a number of times corresponding to the degree of the behavior included in the behavior information before the predetermined time has elapsed. The information management device according to claim 1.

10. Computers Vehicle information, including location and behavior information, is obtained from each of multiple vehicles. Based on the vehicle information, if at least one of the multiple vehicles detects an abnormality in road conditions, it is determined whether a different vehicle detects the same type of abnormality within a predetermined time elapsed since the detection of the abnormality. When the same type of abnormality is detected, the extent of the impact of the road condition abnormality is estimated based on the vehicle information. To provide the target vehicle, determined based on the affected area, with information regarding the abnormal road conditions, including the affected area, among the multiple vehicles: Information management method.

11. On the computer, Vehicle information, including location and behavior information, is obtained from each of multiple vehicles. Based on the vehicle information, if at least one of the multiple vehicles detects an abnormality in road conditions, the system will determine whether a different vehicle will detect the same type of abnormality within a predetermined time elapsed since the detection of the abnormality. If the same type of abnormality is detected, the system will estimate the extent of the impact of the road condition abnormality based on the vehicle information. Of the aforementioned multiple vehicles, the target vehicle, determined based on the affected area, is to provide information regarding the abnormal road conditions, including the affected area. program.

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