Control device, control method, and program for control device

Abstract

To provide a control device for outputting information with as high accuracy as possible in advance relative to, for example, a situation in which a vehicle is likely to encounter a traffic event.SOLUTION: A control device: acquires (S11) own-vehicle current information based on at least own-vehicle surroundings information indicating surrounding situations of a vehicle; acquires (S10), relative to a plurality of event-encountered vehicles having encountered a traffic event, a plurality of pieces of pre-event-encountered information based on at least event-encountered vehicle surroundings information indicating surrounding situations of the event-encountered vehicle at a predetermined time before encountering the event; and causes output means of the vehicle to operate (S12 to S14) when a plurality of pieces of pre-event encounter information include information that satisfies a similar criterion set in advance relative to the own car current information.SELECTED DRAWING: Figure 13

Description

[Technical Field]

[0001] The present application belongs to the technical field of a control device, a control method, and a program for the control device. [Background technology]

[0002] Technologies have been developed to prevent accidents involving vehicles, an example of a moving body, as far as possible in advance. For example, Patent Document 1 below discloses a road condition information providing system that, when a vehicle approaches a high-accident spot, transmits intermittent information to an in-vehicle terminal that the vehicle is approaching the high-accident spot, and the in-vehicle terminal displays the high-accident spot on a map displayed on a display and also notifies the vehicle of this by voice. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-165378 Summary of the Invention [Problem to be solved by the invention]

[0004] Traffic events such as accidents are related to human factors, vehicle factors, and environmental factors, and even if an accident-prone area is located, it does not necessarily mean that the risk of an accident is high. However, the technology described in Patent Document 1 above issues an alert when a vehicle approaches an accident-prone area, which has the problem of issuing an alert even when the risk of an accident is low.

[0005] The present application has been made in consideration of the above-mentioned problems, and one example of the object of the application is to provide a control device or the like that outputs information as accurately as possible in advance in situations where a traffic incident is likely to occur. [Means for solving the problem]

[0006] In order to solve the above problem, the invention described in claim 1 is characterized by comprising a first acquisition means for acquiring current vehicle information based at least on vehicle surrounding information indicating the vehicle's surrounding conditions, a second acquisition means for acquiring a plurality of pre-event encounter information for a plurality of event-encounter vehicles that have encountered a traffic event, the pre-event encounter information being based at least on event-encounter vehicle surrounding information indicating the surrounding conditions of the event-encounter vehicle a predetermined time before the event was encountered, and a control means for operating the vehicle's output means when information that satisfies a predetermined similarity criterion for the vehicle current information is present in the plurality of pre-event encounter information.

[0007] The invention described in claim 9 is a control method executed by a control device that operates an output means of a vehicle, characterized in that it includes: a first acquisition step in which a first acquisition means acquires current host vehicle information based at least on host vehicle surrounding information indicating the surrounding conditions of the vehicle; a second acquisition step in which a second acquisition means acquires, for a plurality of event-encounter vehicles that have encountered a traffic event, a plurality of pre-event encounter information based at least on event-encounter vehicle surrounding information indicating the surrounding conditions of the event-encounter vehicle a predetermined time before the event was encountered; and a control step in which a control means operates the output means of the vehicle when information that satisfies a predetermined similarity criterion for the host vehicle current information is present in the plurality of pre-event encounter information. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 2 is a block diagram showing an example of a schematic configuration of a control device according to the embodiment. [Figure 2] 1 is a schematic diagram illustrating an example of a schematic configuration of a control system according to an embodiment. [Figure 3] 3 is a block diagram showing an example of a schematic configuration of the in-vehicle terminal device of FIG. 2. FIG. [Figure 4] 3 is a block diagram showing an example of a schematic configuration of the information processing server device of FIG. 2. FIG. [Figure 5] 5 is a schematic diagram showing an example of a database of the information processing server device of FIG. 4. FIG. [Figure 6] FIG. 1 is a schematic diagram illustrating an example of a traffic event. [Figure 7] FIG. 1 is a schematic diagram illustrating an example of a traffic event. [Figure 8] FIG. 1 is a schematic diagram illustrating an example of a traffic event. [Figure 9] FIG. 1 is a schematic diagram illustrating an example of a traffic event. [Figure 10] FIG. 1 is a schematic diagram illustrating an example of a traffic event. [Figure 11] FIG. 1 is a schematic diagram illustrating an example of a traffic event. [Figure 12] FIG. 10 is a sequence diagram showing an example of an operation for generating event scene data. [Figure 13] 4 is a flowchart illustrating an example of an operation of the control system according to the embodiment. [Figure 14] FIG. 2 is a schematic diagram showing an example of a host vehicle in a certain surrounding situation. [Figure 15] FIG. 2 is a schematic diagram showing an example of a host vehicle in a certain surrounding situation. DETAILED DESCRIPTION OF THE INVENTION

[0009] An embodiment of the present invention will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of a schematic configuration of a control device according to the embodiment.

[0010] 1, the control device 1 is configured to include a first acquisition unit 1a, a second acquisition unit 1b, and a control unit 1c. Here, examples of the control device 1 include an in-vehicle terminal device such as a navigation device mounted on a mobile object, a server device that outputs information to the in-vehicle terminal device, etc. Examples of the mobile object include an automobile, a motorbike, a bicycle, a person, a train, a ship, an airplane, etc.

[0011] In this configuration, the first acquisition means 1a acquires current vehicle information based at least on surrounding information of the vehicle that indicates the surrounding conditions of the vehicle.

[0012] Examples of the information about the surroundings of the vehicle include road attributes relating to the road on which the vehicle that is the target of the output of a warning or the like is traveling, road attributes relating to connecting roads to intersections near the current location of the vehicle, weather information for the current location of the vehicle (e.g., temperature, wind speed, wind direction, amount of precipitation / snowfall, etc.), time, etc. Examples of road attributes include road type, speed limit, number of lanes, gradient, entry restrictions to nearby intersections, and connecting directions to nearby intersections. Intersections are points where two or more roads intersect, and include junctions where a branch road merges with a main road.

[0013] Examples of road types include expressways, national highways, prefectural roads, municipal roads, farm roads, forest roads, and other roads.

[0014] The current vehicle information based at least on the vehicle surroundings information includes the current vehicle surroundings information of the vehicle that is the subject of output.

[0015] The control device 1 acquires information about the surroundings of the vehicle from various devices such as sensors, cameras, and microphones mounted on the vehicle, or from an in-vehicle terminal device.

[0016] In this configuration, the second acquisition means 1b acquires, for a plurality of event-encounter vehicles that have encountered a traffic event, a plurality of pieces of pre-event encounter information that are based at least on event-encounter vehicle surrounding information that indicates the surrounding conditions of the event-encounter vehicle a predetermined time before the event was encountered.

[0017] Examples of traffic events include an accident with an object, contact with an object, sudden braking due to abnormal approach to an object, and avoidance. Examples of objects include other moving objects, buildings, structures, etc. Examples of incident-encounter vehicles that encounter a traffic event include a vehicle that has had an accident with an object, a vehicle that has contacted an object, and a vehicle that has abnormally approached an object. Examples of the predetermined time before the event encounter include 3 seconds, 5 seconds, 7 seconds, 10 seconds, 15 seconds, etc., and any time that has a strong causal relationship with the event is acceptable.

[0018] Examples of information surrounding the incident-encountered vehicle include road attributes relating to the road on which the incident-encountered vehicle was traveling, road attributes relating to the connecting roads to intersections near the vehicle's current location, weather information for the vehicle's current location, and the time.

[0019] An example of pre-event encounter information based at least on the event-encounter vehicle surroundings information is event-encounter surroundings information for the event-encounter vehicle that is a predetermined time before the event is encountered.

[0020] The control device 1 acquires information about the surroundings of the incident-encountered vehicle from various devices such as sensors, cameras, and microphones mounted on the incident-encountered vehicle, or from an in-vehicle terminal device.

[0021] In this configuration, the control means 1c operates the output means of the vehicle when there is information among the plurality of pre-event information that satisfies a similarity criterion set in advance with respect to the current information of the vehicle.

[0022] Here, an example of a similarity criterion is that the similarity between the vehicle current information and the pre-event encounter information can be determined, for example, whether the calculated similarity is equal to or greater than a predetermined value. The similarity between each piece of pre-event encounter information and the vehicle current information is determined. Information that satisfies a predetermined similarity criterion is extracted from the plurality of pieces of pre-event encounter information.

[0023] Furthermore, the similarity with the host vehicle current information may be calculated based on the result of matching the host vehicle current information with the pre-event encounter information, and a determination may be made as to whether the pre-event encounter information satisfies a predetermined similarity standard. Here, examples of the result of matching the host vehicle current information with the pre-event encounter information include matching the same items of information in the host vehicle current information and the pre-event encounter information, and determining whether they match or whether the values ​​of the items of information fall within the same range of values. Furthermore, the similarity with the host vehicle current information may be calculated, for example, from the number of items that match or the number of items that belong in the matching. The similarity may be, for example, the percentage of items that match or the percentage of items that belong. Furthermore, the similarity may be calculated by assigning a weight to each item. The similarity may also be calculated by matching only specific items.

[0024] Examples of vehicle output means include a display that displays warning messages, a speaker that outputs audio warning messages, and a drive control device that outputs control signals to decelerate the vehicle to a predetermined speed and control signals to prepare for braking.

[0025] The first acquisition means 1a may acquire, as the current vehicle information, information based at least on the surroundings information of the vehicle and the vehicle state information indicating the current traveling situation of the vehicle.

[0026] Examples of vehicle status information include information on the vehicle's model, the vehicle's driving speed, the vehicle's acceleration, the vehicle's direction of travel, the vehicle's headlight status, the vehicle's turn signal status, the wiper status, the horn status, and the distance to an intersection near the vehicle.

[0027] In addition, the second acquisition means 1b may acquire, as the plurality of pre-event encounter information, information based at least on event-encounter vehicle surrounding information and event-encounter vehicle state information indicating the driving conditions of the event-encounter vehicle that encountered a traffic event a predetermined time before the event was encountered.

[0028] Examples of incident-encounter vehicle status information include information on the vehicle type at the time of the incident, information on the driving speed at the time of the incident, information on the acceleration at the time of the incident, information on the direction of travel at the time of the incident, information on the state of the headlights at the time of the incident, information on the turn signal at the time of the incident, the state of the wipers, the state of the horn, information on the distance to the intersection near the time of the incident, and information on the type of traffic regulation violation.

[0029] The vehicle status information may also include vehicle travel information relating to the vehicle's travel speed, travel direction, and distance to an intersection near the vehicle.

[0030] Here, examples of vehicle driving information include information about the vehicle when it is driving, such as information about the vehicle's driving speed, information about the vehicle's acceleration, information about the vehicle's direction of travel, information about the state of the vehicle's headlights, information about the vehicle's turn signal lights, and information about the distance to an intersection near the vehicle.

[0031] The event-encountered vehicle status information may include event-encountered vehicle travel information relating to the travel speed and direction of the event-encountered vehicle, and the distance to an intersection near the event-encountered vehicle.

[0032] Here, an example of event-encounter vehicle driving information is information about the vehicle when the event-encounter vehicle is driving, such as information about the driving speed of the event-encounter vehicle, information about the acceleration of the event-encounter vehicle, information about the direction of travel of the event-encounter vehicle, information about the state of the headlights of the event-encounter vehicle, information about the turn signal of the event-encounter vehicle, and information about the distance to the intersection near the event-encounter vehicle.

[0033] In addition, the control means 1c may calculate the similarity between the vehicle's current information and the vehicle's driving information based at least on the results of comparing the vehicle's driving information with the event-encountered vehicle's driving information, and operate the vehicle's output means when information that satisfies a predetermined similarity criterion is present.

[0034] Here, as an example of the result of comparing the own vehicle driving information with the event-encountered vehicle driving information, the same items of information in the own vehicle driving information and the event-encountered vehicle driving information are compared to see whether they match, or whether the values ​​of the information items fall within the same range of values, etc.

[0035] The vehicle surrounding information may also include vehicle surrounding road attributes relating to the road on which the vehicle is traveling and other roads connected to intersections near the vehicle.

[0036] Here, examples of the surrounding road attributes of the vehicle include the road attributes of the road on which the vehicle is traveling and the road attributes of other roads connected to an intersection near the vehicle.

[0037] The information about the surroundings of the incident-encountered vehicle may also include the surrounding road attributes of the incident-encountered vehicle regarding the road on which the incident-encountered vehicle was traveling and other roads that connect to intersections near the incident-encountered vehicle.

[0038] Here, examples of the road attributes surrounding the incident-encountered vehicle include the road attributes of the road on which the incident-encountered vehicle is traveling, and the road attributes of other roads that connect to an intersection near the incident-encountered vehicle.

[0039] In addition, the control means 1c may calculate the similarity between the current information of the vehicle and the surrounding road attributes of the vehicle based at least on the results of matching the surrounding road attributes of the vehicle that encountered the incident, and operate the output means of the vehicle when information that satisfies a predetermined similarity standard is present.

[0040] Here, an example of the result of matching the road attributes around the vehicle and the road attributes around the vehicle encountering the event is to compare the same items of information in the road attributes around the vehicle and the road attributes around the vehicle encountering the event, and see whether they match, or whether the values ​​of the information items fall within the same range of values.

[0041] The vehicle surroundings information may also include vehicle object information relating to attributes of an object approaching an intersection near the vehicle and the distance of the object to the intersection.

[0042] Here, examples of objects approaching an intersection near a vehicle include peripheral objects such as moving objects present around the vehicle, and moving objects approaching an intersection near the vehicle. Peripheral objects include, for example, peripheral moving objects, and in the case of vehicles, peripheral vehicles. The number of objects approaching an intersection near the vehicle may be multiple or zero depending on the situation. Examples of object attributes include the type of object, the traveling speed of the object, the acceleration of the object, and the traveling direction of the object. Examples of object types include the type of vehicle and person. Examples of vehicle types include large vehicles, medium-sized vehicles, small vehicles, motorcycles, and the like. If the object is a vehicle, examples of object attributes include information on the status of the headlights of the surrounding vehicles, information on the turn signals of the surrounding vehicles, and information on traffic rule violations by the surrounding vehicles. Examples of information on traffic rule violations include no violation, speeding, and stop sign violation.

[0043] The incident-encountered vehicle surroundings information may also include incident-encountered vehicle object information relating to attributes of objects approaching an intersection near the incident-encountered vehicle and the distance of the objects to the intersection.

[0044] Examples of incident-encountered vehicle object information include surrounding objects such as moving objects present around the incident-encountered vehicle, and moving objects approaching an intersection near the incident-encountered vehicle.

[0045] In addition, the control means 1c may calculate the similarity between the subject vehicle current information based at least on the result of matching the subject vehicle object information with the event-encountered vehicle object information, and operate the vehicle's output means when information that satisfies a predetermined similarity criterion is present.

[0046] Here, an example of the result of matching the own vehicle object information with the event-encountered vehicle object information is to compare the same items of information in the own vehicle object information and the event-encountered vehicle object information to see whether they match, or whether the values ​​of the information items fall within the same range of values.

[0047] The first acquisition means 1a may further acquire, as the current vehicle information, host vehicle driving tendency information relating to the driving tendency of the driver of the vehicle.

[0048] Here, examples of the driving tendencies of the vehicle driver include the driver's acceleration tendency (e.g., the number of sudden accelerations per unit distance), the driver's deceleration tendency (e.g., the number of sudden decelerations per unit distance), the driver's steering operation tendency (e.g., the number of sudden decelerations per unit distance), the driver's continuous driving time (e.g., the driving duration from the start of driving), the driver's speed tendency (e.g., the average speed ratio to the legal speed), the driver's stop sign violation rate (e.g., the rate of stop sign violations), the driver's straight-line stability (e.g., the magnitude of left-right sway on a straight road), the driver's cornering stability (e.g., the speed on a curve, the magnitude of left-right sway), the driver's following distance (e.g., the average following distance based on camera images), the driver's lane crossing frequency (e.g., the number of lane crossings per unit distance), and the driver's traffic light passing characteristics (e.g., the frequency of passing through a yellow light without stopping).

[0049] The second acquisition means 1b may further acquire, as the pre-event encounter information, event-encounter vehicle driving tendency information relating to the driving tendency of the driver of the event-encounter vehicle.

[0050] Here, an example of the driving tendency of the driver of the incident-encountered vehicle is the tendency of the driver of the incident-encountered vehicle to accelerate.

[0051] In addition, the control means 1c may calculate the similarity between the vehicle's current information and the driving tendency information of the vehicle that encountered the incident based at least on the results of comparing the vehicle's driving tendency information with the driving tendency information of the vehicle that encountered the incident, and operate the vehicle's output means when information that meets a predetermined similarity standard is present.

[0052] Here, an example of the result of comparing the driving tendency information of the subject vehicle with the driving tendency information of the event-encountered vehicle is to compare the same items of information in the driving tendency information of the subject vehicle and the driving tendency information of the event-encountered vehicle to see whether they match, or whether the values ​​of the items of information fall within the same range of values.

[0053] The second acquisition means 1b may further acquire event type information relating to the type of event corresponding to the pre-event encounter information.

[0054] Examples of traffic incident type information include person-to-vehicle, vehicle-only, (vehicle-to-vehicle) head-on collision, rear-end collision, head-on collision, accident with an object when turning left or right, contact with an object, sudden braking due to abnormal approach to an object, avoidance, etc.

[0055] In addition, when there is information among the multiple pre-event encounter information that satisfies a predetermined similarity standard with the vehicle's current information, the control means 1c may cause the vehicle's alarm means to issue a warning based on the event type information corresponding to the pre-event encounter information that has the highest similarity to the vehicle's current information.

[0056] Among at least one piece of pre-event encounter information that meets a predetermined similarity criterion, the event type information corresponding to the pre-event encounter information with the highest similarity is selected. For example, an example of a warning based on the event type information is a content that notifies the driver of the selected event type information. Examples of notification means that are an example of the vehicle output means include a display, a speaker, etc. mounted on the vehicle.

[0057] In addition, the control means 1c may operate the output means of the vehicle when part of the plurality of pieces of pre-event information and part of the corresponding information of the vehicle's current information satisfy a predetermined similarity criterion.

[0058] An example of a portion of the plurality of pieces of pre-event information is a predetermined item of the pre-event information. An example of a portion of the corresponding host vehicle current information is an information item corresponding to the predetermined information item of the pre-event information.

[0059] As described above, according to the operation of the control device 1 of the embodiment, when pre-event encounter information similar to the vehicle's current information exists, the vehicle's output means is operated, so that information as accurate as possible can be output in advance for situations where a similar traffic event is likely to be encountered. [Example]

[0060] [1. Control system configuration and functional overview] Next, specific examples corresponding to the above-described embodiments will be described with reference to the drawings. Note that the examples described below are examples in which the present invention is applied to an information processing server device or an in-vehicle terminal device.

[0061] FIG. 2 is a schematic diagram illustrating an example of a schematic configuration of a control system according to an embodiment.

[0062] 2, the control system S according to the embodiment includes an in-vehicle terminal device 10 (an example of a control device 1) mounted on a vehicle 5 (an example of a moving body) and a vehicle 7 (an example of a moving body), an information processing server device 20 that collects information about the vehicles 5 and 7 from the in-vehicle terminal device 10 and provides information processing results, and an external server device SV that provides weather information, traffic information, etc. to the information processing server device 20. Here, the in-vehicle terminal device 10 is an example of the control device 1. The information processing server device 20 is an example of the control device 1.

[0063] Vehicle 5 is an example of a moving body and an example of an incident-encountered vehicle. Vehicle 7 is an example of a moving body and an example of the subject vehicle. For convenience, the vehicles are classified as vehicles 5 and 7. The information processing server device 20 communicates with these multiple vehicles 5 and 7.

[0064] When the vehicle 5 encounters a traffic incident, the in-vehicle terminal device 10 of the vehicle 5 transmits pre-event encounter information to the information processing server device 20.

[0065] The on-board terminal device 10 of the vehicle 7 transmits current vehicle information to the information processing server device 20 and receives information processing results from the information processing server device 20. The on-board terminal device 10 may also have a navigation function. The on-board terminal device 10 communicates wirelessly with a network NW that has a wireless base station.

[0066] The information processing server device 20 collects pre-event encounter information from the in-vehicle terminal device 10 of the vehicle 5 and updates the database. The information processing server device 20 acquires host vehicle current information from the in-vehicle terminal device 10 of the vehicle 7, compares the host vehicle current information with multiple pieces of pre-event encounter information, and outputs the information processing result to the in-vehicle terminal device 10 of the vehicle 7.

[0067] The information processing server device 20 acquires weather information for the current positions of the vehicles 5 and 7, the latest traffic information for each road, etc. from the external server device SV. Based on the position coordinates of the vehicle 5 that encountered the event and the date and time of the event, the information processing server device 20 acquires information about the weather at the event site (for example, temperature, wind speed, wind direction, amount of precipitation / snowfall, etc.) from the external server device SV.

[0068] The external server device SV provides the information processing server device 20 with traffic information for each road from VICS (registered trademark), traffic information collected from the in-vehicle terminal devices 10 of other vehicles, etc. For example, the information processing server device 20 acquires traffic information from the external server device SV in real time. The information processing server device 20 may acquire traffic information at predetermined time intervals (for example, in units of 0.1 seconds, in units of seconds, etc.).

[0069] The in-vehicle terminal device 10, the information processing server device 20, and the external server device SV are capable of transmitting and receiving data to and from each other via a network NW using, for example, a communication protocol such as TCP / IP. The network NW is constructed, for example, by the Internet, a dedicated communication line (for example, a CATV (Community Antenna Television) line), a mobile communication network (including base stations, etc.), a gateway, etc.

[0070] [2. Configuration and Function of Each Device] (2.1 Configuration and Functions of the In-Vehicle Terminal Device 10) Next, the configuration and functions of the in-vehicle terminal device 10 will be described with reference to FIG.

[0071] FIG. 3 is a block diagram showing an example of a schematic configuration of the in-vehicle terminal device 10. As shown in FIG.

[0072] As shown in FIG. 3, the in-vehicle terminal device 10, which functions as a computer, has a communication unit 11, a display unit 12, a camera unit 13, a memory unit 14, a sensor unit 15, an operation unit 16, a speaker unit 17, a microphone unit 18, and a control unit 19.

[0073] The communication unit 11 has a wireless communication function. The communication unit 11 connects to a mobile communication network of the network NW and controls the communication state with the information processing server device 20, etc. The communication unit 11 communicates with the information processing server device 20 by wireless communication using radio waves.

[0074] Display unit 12 is configured with, for example, a liquid crystal display element or an EL (Electro Luminescence) element, etc. Map information, guidance information, warning information, etc. are displayed on display unit 12. Display unit 12 is an example of output means and notification means.

[0075] The camera unit 13 has an imaging element such as a CCD (Charge Coupled Device) image sensor or a CMOS (Complementary Metal Oxide Semiconductor) image sensor. The camera unit 13 is a color digital camera. The camera unit 13 takes still images or videos. The camera unit 13 takes images of the surroundings of the vehicles 5 and 7. The camera unit 13 takes images of the front, rear, and side views, for example.

[0076] The storage unit 14 is formed of, for example, a silicon disk drive or a hard disk drive. The storage unit 14 stores various programs for controlling the in-vehicle terminal device 10. Examples of the various programs include an operating system, navigation, and application software for playing music. The storage unit 14 may store map information and music data for navigation. The storage unit 14 may also store information about the vehicle in which the in-vehicle terminal device 10 is installed (e.g., vehicle model, engine displacement, etc.). Note that some or all of the map information for navigation, music data, and information about the vehicle in which the in-vehicle terminal device 10 is installed may be stored in an external storage device (not shown) that is communicatively connected via the communication unit 11.

[0077] Furthermore, the memory unit 14 stores the driving tendency of the driver based on various data from the sensor unit 15 in order to calculate the driving tendency of the driver.

[0078] The various programs may be obtained, for example, via a network such as a wireless communication network, or may be recorded on a recording medium such as a CD (Compact Disc) or a DVD (Digital Versatile Disc) and read via a drive device.

[0079] The sensor unit 15 acquires information such as the vehicle's position information (latitude and longitude information), direction of movement information, speed information, altitude information, and current time from the GPS sensor, direction sensor, speed sensor, altitude sensor, and timer installed in the vehicle 5.

[0080] The operation unit 16 includes various buttons such as a mechanical power button and volume button, and the display unit 12 is a touch switch type display panel such as a touch panel.

[0081] The speaker unit 17 outputs, for example, warning information, guidance information, music, voice, and other sounds, etc. The speaker unit 17 is an example of an output means and a notification means.

[0082] The microphone unit 18 collects sounds from the vehicle itself and sounds around the vehicle.

[0083] The control unit 19 includes, for example, a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory). It reads and executes various programs stored in the ROM, RAM, and storage unit 14. It controls the operation of each unit of the in-vehicle terminal device 10.

[0084] The control unit 19 performs image analysis on image data from the camera unit 13. The control unit 19 performs analysis on various data from the sensor unit. The control unit 19 performs sound analysis on sound data from the microphone unit 18. Note that these image analyses and sound analyses may be configured so that the image data from the camera unit 13 and the sound data from the microphone unit 18 are transmitted to an external analysis device (not shown) via the communication unit 11, and the analysis results from the analysis device are received via the communication unit 11.

[0085] The control unit 19 may control the drive system of the vehicle as an example of an output means. The drive system controls the accelerator amount to control the speed and acceleration of the vehicle. The drive system controls the steering angle to change the direction of travel of the vehicle. The drive system controls the braking amount to decelerate and stop the vehicle. The drive system also controls lights, turn signals, etc.

[0086] (2.2 Configuration and Function of Information Processing Server Device 20) Next, the configuration and functions of the information processing server device 20 will be described with reference to FIGS.

[0087] Fig. 4 is a block diagram showing an example of a schematic configuration of the information processing server device 20. Fig. 5 is a schematic diagram showing an example of a database of the information processing server device 20. Figs. 6 to 11 are schematic diagrams showing examples of traffic events.

[0088] As shown in FIG. 4, the information processing server device 20 functioning as a computer includes a communication unit 21, a storage unit 22, a display unit 23, an operation unit 24, and a control unit 25.

[0089] The communication unit 21 is connected to the network NW and controls the state of communication between the in-vehicle terminal device 10 and the external server device SV.

[0090] The storage unit 22 is configured by, for example, a hard disk drive, a silicon disk drive, etc. The storage unit 22 has a database 22a.

[0091] The database 22a stores pre-event encounter information as event scene data for each event that has occurred. For example, as shown in Fig. 5, information on the event type (an example of event type information), information on the surrounding environment of the event-encountered vehicle (an example of event-encountered vehicle surrounding information), information on surrounding objects of the event-encountered vehicle (an example of event-encountered vehicle surrounding information and an example of event-encountered vehicle object information), information on the vehicle state of the event-encountered vehicle (an example of event-encountered vehicle state information), information on the driving tendency of the driver of the event-encountered vehicle (an example of event-encountered vehicle driving tendency information), and the like are stored in association with the event number of the event that has occurred.

[0092] The traffic event type item in the database 22a stores information such as person-to-vehicle, vehicle-only, head-on collision, rear-end collision, meeting, left turn, right turn, and others.

[0093] The surrounding environment includes road information about the road on which the event-encountering vehicle (e.g., vehicle 5) was traveling, road information about each connecting road at the intersection near the location where the event-encountering vehicle encountered the event, weather information about the area near the location where the event-encountering vehicle encountered the event, the time when the event occurred, etc.

[0094] Further, the road information may include items such as road type, speed limit, number of lanes, gradient, entry restrictions to nearby intersections, and directions of connections to nearby intersections.

[0095] The road type field in the database 22a stores information such as whether the road is an expressway, a national highway, a prefectural road, a municipal road, a farm road, a forest road, or other road. The speed limit field in the database 22a stores the value and range of the road speed limit. The number of lanes field in the database 22a stores the number of lanes on the road. The gradient field in the database 22a stores road gradient information. In the database 22a, the entry restrictions to nearby intersections field stores information such as red lights, stop signs, and no restrictions. In the database 22a, the connection direction field to nearby intersections stores information such as direction (north, northeast, east, southeast, south, southwest, west, or northwest).

[0096] The surrounding objects include the type of moving object, which is an example of an object related to a traffic event, such as the incident-encounter vehicle (e.g., vehicle 5), information on the moving speed of the moving object, information on the acceleration of the moving object, information on the direction of travel of the moving object, and if the moving object is a vehicle, information on the status of the vehicle's headlights, information on the vehicle's turn signal, the distance to an intersection near the moving object, and information on the type of traffic regulation violation.

[0097] The database 22a stores information such as whether the mobile object is a large vehicle, a medium vehicle, a small vehicle, a two-wheeled vehicle, a bicycle, a person, etc. The database 22a stores information such as the value and range of the mobile object's traveling speed in the mobile object's traveling speed field. For example, examples of the traveling speed of a mobile object include over 80 km / h, 80 to 60 km / h, 60 to 40 km / h, 40 to 20 km / h, and less than 20 km / h.

[0098] The value and range of the acceleration of a moving body are stored in the item of acceleration of a moving body in the database 22a. For example, examples of the acceleration of a moving body include over 0.5 G, 0.4 to 0.2 G, 0.2 to 0 G, 0 to -0.2 G, -0.2 to -0.4 G, and less than -0.4 G.

[0099] The heading direction of the mobile object in the database 22a stores information on directions such as north, northeast, east, southeast, south, southwest, west, or northwest.

[0100] The vehicle headlights item in the database 22a stores the state of the headlights of the target vehicle when the incident-encounter vehicle encounters the moving object, etc. Examples of the headlight state include high beam on / low beam on / low beam on / low beam off, etc.

[0101] The vehicle turn signal item in the database 22a stores the state of the turn signal of the target vehicle when the incident-encounter vehicle encounters the moving object. Examples of the turn signal state include left operation / right operation / not operation.

[0102] The database 22a stores information on distances to nearby intersections of a mobile object, such as over 100 m, about 100 m, 50 to 100 m, and less than 50 m. The database 22a stores information on the type of traffic regulation violation of a mobile object, such as no violation, speeding, stop sign violation, and red light violation.

[0103] The vehicle status includes information on the type of vehicle that encountered the event, information on the driving speed of the vehicle that encountered the event, information on the acceleration of the vehicle that encountered the event, information on the direction of travel of the vehicle that encountered the event, information on the state of the headlights of the vehicle that encountered the event, information on the turn signal of the vehicle that encountered the event, and the distance to the intersection near the vehicle that encountered the event.

[0104] The driving tendency includes acceleration tendency, deceleration tendency, steering tendency, continuous driving time, speed tendency, stop sign violation rate, straight line stability, cornering stability, following distance, lane crossing frequency, traffic light passing characteristics, and the like.

[0105] The acceleration tendency item of the database 22a stores information such as whether the sudden acceleration tendency is high, normal, or low.

[0106] As shown in FIG. 6, in the case of a head-on collision at intersection c1 between vehicle 5 on road r1 and target vehicle T1 on road r3, intersection c1 is a nearby intersection. Vehicle 5 on road r1 indicated by a dashed line indicates the position of vehicle 5, the incident-encounter vehicle, a predetermined time ago. Intersection c1 is an intersection ahead of the position of vehicle 5, the incident-encounter vehicle, a predetermined time ago. Road information such as the value "2" in the field for the number of lanes of road r1 on which vehicle 5 was traveling a predetermined time ago and the value "north" in the field for the direction of connection of road r1 to intersection c1 is stored in database 22a. Road information such as the number of lanes and connecting direction for each of roads r2, r3, and r4 connected to intersection c1 is stored in database 22a.

[0107] As shown in FIG. 7, when a vehicle 5 making a right turn from road r1 onto road r4 collides head-on with an object vehicle T1 on road r4, intersection c1 is a nearby intersection. The vehicle 5 on road r1 indicated by a dashed line indicates the position of the vehicle 5, the incident-encounter vehicle, a predetermined time ago. Intersection c1 is an intersection ahead of the position of the vehicle 5, the incident-encounter vehicle, a predetermined time ago. Roads r1, r2, r3, and r4 are connected to intersection c1. Road information such as a value "1" for the number of lanes of road r1 on which vehicle 5 was traveling a predetermined time ago and a value "northwest" for the direction of connection of road r1 to intersection c1 is stored in database 22a. Road information such as the number of lanes and connection direction for each of roads r2, r3, and r4 connected to intersection c1 is stored in database 22a.

[0108] As shown in Figure 8, when vehicle T1 coming out of side road r3 collides head-on with vehicle 5 traveling on main road r1, intersection c1 is the nearby intersection. Vehicle 5 on road r1 indicated by a dashed line indicates the position of vehicle 5, the incident-encountered vehicle, a predetermined time ago. Intersection c1 is the intersection ahead of the position of vehicle 5, the incident-encountered vehicle, a predetermined time ago. Roads r1, r2, and r3 connect to intersection c1.

[0109] As shown in Figure 9, when vehicle T1 rear-ends vehicle 5 that is stopped at intersection c1 on road r1, intersection c1 is a nearby intersection. Two-lane roads r1, r2, r3, and r4 connect to intersection c1.

[0110] As shown in Figure 10, in the case of a head-on collision between vehicle 5 and target vehicle T1 at a five-way intersection c1, intersection c1 is the nearby intersection. Vehicle 5 on road r5 indicated by the dashed line indicates the position of vehicle 5, the event-encountered vehicle, a predetermined time ago. Intersection c1 is the intersection ahead of the position of vehicle 5, the event-encountered vehicle, a predetermined time ago. Roads r1, r2, r3, r4, and r5 connect to intersection c1.

[0111] As shown in Figure 11, when vehicle 5 and vehicle T1 collide at intersection c1, the intersection c1 is a nearby intersection. Intersection c1 is an intersection ahead of the position of vehicle 5, the incident-encounter vehicle, a predetermined time ago. At intersection c1, two-lane roads r1 and r2 connect with road r3.

[0112] The storage unit 22 also stores map information, traffic information acquired from the external server device SV, weather information, and the like.

[0113] The storage unit 22 also stores various programs such as an operating system and a server program. The various programs may be acquired from other server devices via the network NW, or may be recorded on a recording medium and read via a drive device.

[0114] The display unit 23 is configured by, for example, a liquid crystal display element or an EL element.

[0115] The operation unit 24 is configured by, for example, a keyboard and a mouse.

[0116] The control unit 25 has, for example, a CPU, a ROM, a RAM, etc. The control unit 25 controls the operation of each unit of the information processing server device 20. The control unit 25 executes various processes by reading and executing various programs stored in the storage unit 22. The control unit 25 is an example of an output means and a notification means.

[0117] [3. Guidance system operation] Next, the operation of the control system S according to the embodiment will be described with reference to FIGS. (3.1 Generation of Event Scene Data) The operation of the control system S to collect pre-event encounter information from the in-vehicle terminal device 10 of each vehicle that encounters an event (for example, each vehicle 5) and generate event scene data will be described with reference to Fig. 12. Note that even when vehicle 7 encounters an event, the in-vehicle terminal device 10 of vehicle 7 may transmit the pre-event encounter information, but for convenience, the in-vehicle terminal device 10 of vehicle 5 will be described here.

[0118] FIG. 12 is a sequence diagram showing an example of the operation of generating event scene data.

[0119] While the vehicle 5 is traveling on a road, the in-vehicle terminal device 10 of the vehicle 5 acquires information about the surroundings of the event-encountered vehicle and various data for the driving information of the event-encountered vehicle. For example, to collect the information about the surroundings of the event-encountered vehicle, the camera unit 13 captures video images of the surroundings and the microphone unit 18 collects sound. In addition, to collect the driving information of the event-encountered vehicle, the sensor unit 15 measures various data such as the position information, driving speed, acceleration, and direction of travel of the vehicle 5.

[0120] The video, various sensor data, and sound data are recorded in the memory unit 14, etc. for a time longer than a predetermined time (3 seconds ago, 5 seconds ago, 7 seconds ago, 10 seconds, 15 seconds ago, etc.) from the current time. Assume that an event occurs when the vehicle 5 collides with or comes into contact with an object such as another vehicle.

[0121] As shown in Fig. 12, the control system S detects an event (step S1). Specifically, the control unit 19 of the in-vehicle terminal device 10 in the vehicle 5 acquires acceleration data from the acceleration sensor of the sensor unit 15, and if the acceleration data is equal to or greater than a predetermined value, it determines that an impact has occurred and detects that an event has been encountered. The control unit 19 may also acquire sound data such as an impact sound from the microphone unit 18, and if the sound resembles a predetermined waveform such as a horn sound, or if the volume of the surrounding environmental sound is equal to or greater than a predetermined value, detect that an event has been encountered. The control unit 19 may also perform image analysis of video from the camera unit 13 to determine whether an event has been encountered.

[0122] Next, the control system S acquires information such as video from a predetermined time ago (step S2). Specifically, the control unit 19 acquires information from the vehicle 5 from the storage unit 14 or the like from the predetermined time before the time when the event occurred. More specifically, the control unit 19 acquires from the storage unit 14 or the like video from the camera unit 13, vehicle driving information data from the sensor unit 15, and sound data from the microphone unit 18 within a predetermined time including the predetermined time before the time when the event occurred. If the sensors of the sensor unit 15 themselves have memory, the control unit 19 may acquire this information from the memory of each sensor.

[0123] Furthermore, the control unit 19 refers to the storage unit 14 to acquire information on the vehicle model of the vehicle 5 and information on the driving tendency of the driver of the vehicle 5 .

[0124] Next, the control system S transmits the acquired information to the information processing server device 20 (step S3). Specifically, the control unit 19 of the in-vehicle terminal device 10 in the vehicle 5 transmits the acquired information, such as location information of the location where the event occurred, the time when the event occurred, video, sound information, vehicle driving information, information on the vehicle model of the vehicle 5, and information on driving tendencies, together with the vehicle ID to the information processing server device 20 via the communication unit 11.

[0125] Next, the control system S receives information from the in-vehicle terminal device 10 (step S4). Specifically, the control unit 25 of the information processing server device 20 receives, via the communication unit 21, acquired information from the in-vehicle terminal device 10 in the vehicle 5, such as location information of the location where the event occurred, the time when the event occurred, video, sound information, vehicle driving information, information on the vehicle model of the vehicle 5, and information on driving tendencies.

[0126] Next, the control system S acquires meteorological information such as the weather, temperature, and precipitation at the location and time when the event occurred from the external server device SV (step S5). Specifically, the control unit 25 acquires meteorological information such as the weather, temperature, and precipitation at the location and time when the event occurred from the external server device SV based on the location information of the location where the event occurred and the time when the event occurred.

[0127] Next, the control system S analyzes the information from the in-vehicle terminal device 10 and the information from the external server device SV to generate pre-event encounter information (step S6). Specifically, in the case of information on the surrounding environment of the vehicle 5, the control unit 25 identifies the position of the vehicle 5 a predetermined time ago from the position information at which the event was encountered, and further identifies an intersection near the position of the vehicle 5 a predetermined time ago by referring to the map information in the memory unit 22. Examples of this identified intersection include the intersection closest to the position of the vehicle 5 a predetermined time ago, and the intersection ahead of the position of the vehicle 5 a predetermined time ago.

[0128] Based on the identified intersection and map information, the control unit 25 extracts road information for each road connecting to the intersection, such as the road type, speed limit, number of lanes, gradient, entry restrictions to nearby intersections, and direction of connection to nearby intersections, and generates pre-event encounter information.

[0129] Furthermore, the control unit 25 calculates the time a predetermined time before the time when the event was encountered as an example of the information on the surrounding environment, and generates pre-event encounter information.

[0130] In the case of information about objects around the vehicle 5, the control unit 25 performs image analysis of the video for a period of time including a predetermined time from the time the event was encountered, extracts the objects, and identifies each object around the vehicle 5. The control unit 25 performs image analysis and calculates the type of the identified object, the distance to the object, the speed, acceleration, direction of travel, whether or not headlights are on, whether or not turn signals are on, the distance to the identified intersection, etc., to generate pre-event encounter information.

[0131] Furthermore, the control unit 25 performs image analysis of the video to estimate the road surface condition, such as dry, wet, frozen, or snowy, and generates pre-event information.

[0132] In the case of vehicle information of vehicle 5, the control unit 25 calculates the driving speed of vehicle 5, the acceleration of vehicle 5, the direction of travel of vehicle 5, the state of the headlights of vehicle 5, the state of the turn signal of vehicle 5, and the distance to an intersection near vehicle 5 based on the vehicle driving information data from the sensor unit 15.

[0133] The type of the event that the vehicle 5 has encountered is calculated, for example, by the control unit 19 analyzing the video image captured by the camera unit 13, based on the direction of collision with the object, etc.

[0134] Furthermore, the control unit 19 processes the weather information for use in the database 22a.

[0135] Next, the control system S stores the generated pre-event encounter information as event scene data for collation (step S7). Specifically, the control unit 25 associates the generated pre-event encounter information with the event number and adds and stores the information in the database 22a.

[0136] (3.2 Operation for determining current vehicle information) Next, the operation of determining the vehicle's current information will be described with reference to FIGS. 13 to 15. FIG.

[0137] Fig. 13 is a flowchart showing an example of the operation of the control system according to the embodiment. Fig. 14 and Fig. 15 are schematic diagrams showing an example of the host vehicle in a certain surrounding situation.

[0138] 13, the control system S acquires event scene data for determination from the information processing server device 20 (step S10). Specifically, the control unit 19 of the in-vehicle terminal device 10 of the vehicle 7 acquires, from the information processing server device 20, the event scene data for determination that indicates each piece of pre-event encounter information stored in the database 22a.

[0139] Next, the control system S acquires information such as video (step S11). Specifically, the control unit 19 of the in-vehicle terminal device 10 of the vehicle 7 acquires information such as video at the current time of the in-vehicle terminal device 10 of the vehicle 7, as in step S2. Here, unlike step S2, data is acquired from the camera unit 13, the sensor unit 15, and the microphone unit 18 for a predetermined period from the current time.

[0140] Next, the control system S generates the current vehicle information (step S12). Specifically, the control unit 19 of the in-vehicle terminal device 10 of the vehicle 7 generates the current vehicle information based on the video from the vehicle 7, the position information of the vehicle 7, the driving situation of the vehicle 7, etc., instead of the pre-event information, as in step S6.

[0141] 14, when the vehicle 7 is traveling on a road r10 and approaches an intersection c2, the control unit 19 generates the surrounding road attributes of the vehicle for the road r10 on which the vehicle is traveling and the surrounding road attributes of the roads r11, r12, and r13 that connect to the intersection c2 ahead of the vehicle 7. If the target vehicle T2 is captured in the video, the control unit 19 generates the attributes of the target approaching the intersection c2.

[0142] As shown in Figure 15, when vehicle 7 is traveling on road r10 and approaches intersection c2, control unit 19 generates the road attributes around the vehicle for road r10 on which vehicle 7 is traveling, and the road attributes around the vehicle for roads r11 and r12 that connect to intersection c2 ahead of vehicle 7.

[0143] The control unit 19 may transmit information such as the video acquired in step S11 to the information processing server device 20, which may then generate the host vehicle current information. Here, the items of the host vehicle current information and the items of the pre-event encounter information are the same except for the event type item.

[0144] Regarding the driving tendency of the driver of the vehicle 7, the control unit 19 of the in-vehicle terminal device 10 of the vehicle 7 may send a request to the information processing server device 20 to acquire the driving tendency together with the vehicle ID of the vehicle 7 or the user ID of the driver of the vehicle 7, and acquire information on the driving tendency of the driver of the vehicle 7 from the information processing server device 20. The control unit 19 may acquire weather information from the information processing server device 20 or from an external server device SV, or may determine the weather and road surface conditions from images captured by the camera unit 13.

[0145] Next, the control system S calculates the similarity between each item of pre-event encounter information in the event scene data for determination and the vehicle current information (step S13). Specifically, the control unit 19 compares the value of each item of the vehicle current information with the value of each item of the pre-event encounter information for each event number in the corresponding event scene data for determination, calculates the number of matching items, and divides the result by the number of items to calculate the similarity. Note that only some of the items may be used to calculate the similarity. Furthermore, the items used to calculate the similarity may be changed depending on the event type.

[0146] Next, the control system S determines whether the similarity is equal to or greater than a threshold (step S14). Specifically, the control unit 19 determines whether the ratio of matching items is equal to or greater than a predetermined value (for example, 70%, 80%, 85%).

[0147] If the similarity is equal to or greater than the threshold (step S14; YES), the control system S outputs a warning (step S15). Specifically, the control unit 19 extracts the pre-event encounter information with the greatest similarity from the pre-event encounter information with similarities equal to or greater than the threshold. The control unit 19 determines the event type information of the pre-event encounter information with the greatest similarity. The control unit 19 generates a warning based on the event type and outputs it to the speaker unit 17 and the display unit 12. For example, the warning content may be "There is a risk of a head-on collision ahead. Slow down and watch out for vehicles jumping out from the right."

[0148] If the similarity is less than the threshold value (step S14; NO), the control system S returns to the processing of step S11.

[0149] As described above, according to the operation of the embodiment, when pre-event encounter information similar to the vehicle's current information exists, the output means of the vehicle 7 is operated, so that information can be output as accurately as possible in advance for situations where a similar traffic event is likely to be encountered. As a result, warnings and the like can be issued even in locations where no event has occurred. When the vehicle's current information, including the vehicle state and surrounding conditions, of the vehicle 7 meets similarity criteria for an event such as an accident that actually occurred in the past, it can be determined that an event has occurred for the vehicle 7. In other words, since the population data of the event can be increased compared to when comparing events that occurred in the same location, the occurrence of the event can be determined with higher accuracy.

[0150] Furthermore, since pre-event information is collected from a predetermined time before an event is encountered, it is possible to determine the extent to which an event has occurred in advance.

[0151] Furthermore, when the current information of the subject vehicle is obtained based at least on the subject vehicle surroundings information and subject vehicle state information indicating the current driving conditions of the vehicle 7, and the multiple pieces of pre-event information are obtained based at least on the event-encounter vehicle surroundings information and event-encounter vehicle state information indicating the driving conditions of the vehicle 5 that encountered a traffic event a predetermined time before the event was encountered, as the subject vehicle state information and event-encounter vehicle state information increase, the amount of information to be judged as similar increases, and more accurate information can be output.

[0152] Furthermore, the host vehicle state information includes host vehicle driving information relating to the driving speed, direction of travel, and distance to intersection c2 near vehicle 7, and the event-encountered vehicle state information includes event-encountered vehicle driving information relating to the driving speed, direction of travel, and distance to intersection c1 near the event-encountered vehicle, and similarity with the host vehicle current information is calculated based at least on the result of comparing the host vehicle driving information with the event-encountered vehicle driving information, and when information that satisfies a predetermined similarity standard is present, the output means of vehicle 7 is operated, and more information is judged to be similar, enabling more accurate information to be output. Furthermore, by comparing each item of the host vehicle pre-information and the pre-event encounter information, similarity can be calculated with high accuracy.

[0153] In addition, the vehicle surroundings information includes the vehicle surroundings road attributes relating to the road on which the vehicle 7 is traveling and other roads connected to intersection c2 near the vehicle 7, and the event-encountered vehicle surroundings information includes the event-encountered vehicle surroundings road attributes relating to the road on which the event-encountered vehicle 5 was traveling and other roads connected to intersection c1 near the event-encountered vehicle 5. The similarity with the vehicle current information is calculated based at least on the result of matching the vehicle surroundings road attributes with the event-encountered vehicle surroundings road attributes, and when information that satisfies the predetermined similarity criteria is present, when the output means of the vehicle 7 is operated, the amount of information to be judged as similar increases, enabling more accurate information to be output.

[0154] In addition, the vehicle surroundings information includes vehicle object information relating to the attributes of an object (e.g., vehicle T2) approaching an intersection c2 near the vehicle 7 and the distance of the object to the intersection c2, and the event-encountered vehicle surroundings information includes event-encountered vehicle object information relating to the attributes of an object approaching an intersection near the event-encountered vehicle 5 and the distance of the object (e.g., vehicle T1) to the intersection, and when the similarity with the vehicle current information is calculated based at least on the result of matching the vehicle object information with the event-encountered vehicle object information, and when information that satisfies the predetermined similarity criteria is present, the output means of vehicle 7 is operated so that more information is judged to be similar, enabling more accurate information to be output.

[0155] Furthermore, as the own vehicle current information, own vehicle driving tendency information relating to the driving tendency of the driver of vehicle 7 is further acquired, and as pre-event information, event-encountering vehicle driving tendency information relating to the driving tendency of the driver of event-encountering vehicle 5 is further acquired, and the similarity with the own vehicle current information is calculated based at least on the result of comparing the own vehicle driving tendency information with the event-encountering vehicle driving tendency information, and when information that satisfies the predetermined similarity criteria is present, when the output means of vehicle 7 is operated, the amount of information to be judged as similar increases, and more accurate information can be output.

[0156] Furthermore, if event type information relating to the type of event corresponding to the pre-event encounter information is further acquired, and when there is information among the multiple pieces of pre-event encounter information that satisfies a similarity standard set in advance for the host vehicle current information, a warning based on the event type information corresponding to the pre-event encounter information that has the highest similarity to the host vehicle current information is issued by the notification means of the vehicle 7 (the display unit 12 and the speaker unit 17 of the vehicle 7), it is possible to notify the driver in advance of information about an event that the vehicle 7 is likely to encounter. In this way, by determining whether or not there is an event case with a similarity score equal to or greater than a predetermined value, it is possible to notify the driver of a state in which an event is likely to be encountered when there is an event case that has a high similarity to the host vehicle current information, such as the current state of the host vehicle 7 and surrounding conditions.

[0157] Furthermore, when a portion of the plurality of pieces of pre-event information and a portion of the corresponding information of the vehicle's current information satisfy a preset similarity criterion, the output means of the vehicle 7 is operated, and the number of items to be compared can be narrowed down, thereby improving the processing speed of the comparison. In order to quickly determine whether the similarity criterion is satisfied, the number of items may be narrowed down even further. For example, if the event scene is determined using only the items of the surrounding environment, the occurrence of the event can be reported based on event cases in which the type and layout of the road ahead are similar.

[0158] To speed up the judgment process, it is possible to make the match of specific elements a necessary condition, and then filter the event cases to determine whether they meet the similarity criteria. This reduces the number of events to be matched, allowing for faster judgment.

[0159] The event scene data for determination may be stored in advance in the in-vehicle terminal device 10. This allows the in-vehicle terminal device 10 to independently determine whether an event has been encountered without communicating with the information processing server device 20.

[0160] Furthermore, the database 22a may store event scene data for determination that is generated by categorizing event cases into various categories by human visual inspection or the like.

[0161] Alternatively, the in-vehicle terminal device 10 of the vehicle 7 may create host vehicle current information based on the current vehicle state information, surrounding situation information, etc. of the host vehicle, and continuously transmit this to the information processing server device 20, which may then compare the event scene data for determination with the host vehicle current information to determine whether the similarity criteria are met. If there is an event case whose similarity is equal to or greater than a predetermined value, the information processing server device 20 generates a warning message based on the type of event corresponding to the event case and transmits it to the in-vehicle terminal device 10 of the vehicle 7. The information processing server device 20 then transmits a control signal to the in-vehicle terminal device 10 to cause the in-vehicle device to output this warning message from the display unit 12 and speaker unit 17. In this case, the processing load on the in-vehicle terminal device 10 can be reduced.

[0162] Furthermore, the in-vehicle terminal device 10 may constantly transmit images from the camera unit 13 and information output by the various sensors of the sensor unit 15 to the server, and the information processing server device 20 may detect road attributes and surrounding objects based on this information, then create current vehicle information, and compare the event scene data for determination with the current vehicle information to determine whether or not they satisfy similarity criteria. In this case, the processing load on the in-vehicle terminal device 10 can be further reduced.

[0163] In addition to in-vehicle car navigation systems, the present invention may also be used in in-vehicle drive recorders, vehicle operation management systems, vehicle telematics insurance, etc. [Explanation of symbols]

[0164] 1: Control device 5, 7: Vehicle 1a: 1st acquisition means 1b:Second acquisition means 1c: Control means 10: In-vehicle terminal device (control device) 19: Control unit (first acquisition means, second acquisition means, control means) 20: Information processing server device (control device) 25: Control unit (first acquisition means, second acquisition means, control means) S: Control system

Claims

[Claim 1] a first acquisition means for acquiring current vehicle information based at least on surrounding information of the vehicle, the surrounding information indicating a surrounding situation of the vehicle; a second acquisition means for acquiring a plurality of pre-event encounter information for a plurality of event-encountered vehicles that have encountered a traffic event, the pre-event encounter information being based at least on event-encountered vehicle surrounding information that indicates the surrounding conditions of the event-encountered vehicles a predetermined time before the event was encountered; a control means for operating an output means of the vehicle when information that satisfies a predetermined similarity criterion for the host vehicle current information is present in the plurality of pre-event information; A control device comprising:

Images