Mobility support device, mobility support method, mobility support program, and mobility support system

Abstract

To provide a movement support device capable of excellently supporting a movement of a mobile body such as a vehicle.SOLUTION: An acquisition section 41 acquires a photographed image obtained by photographing a landscape in at least a travel direction of each mobile body and position information indicating a photographing position of the photographed image, which are transmitted from the mobile body. An incident detection section 44 detects an occurring incident by analyzing the photographed images acquired by the acquisition section 41. An information provision section 49 notifies the mobile bodies of an effect that an incident detected by the incident detection section 44 is occurring. Thus, the mobile body closer to an incident occurrence point can avoid the incident in advance before arriving at the incident occurrence point, thereby excellently supporting the movement of the mobile body.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a mobility assistance device, a mobility assistance method, a mobility assistance program, and a mobility assistance system. [Background technology]

[0002] As a conventional technology related to a mobility assistance device, for example, Patent Document 1 (JP 2018-097789 A) discloses a vehicle information system. This vehicle information system includes multiple on-board devices that acquire vehicle information including vehicle model information for multiple vehicles, including one or more vehicles for each of two or more different vehicle models. The vehicle information system also includes a vehicle information server having a server-side communication unit that acquires vehicle information for each vehicle from the multiple on-board devices, a server-side memory unit that stores the acquired vehicle information, and a vehicle information group generation unit that associates the vehicle information for each vehicle model from the vehicle information for each vehicle and generates one or more vehicle-specific vehicle information groups. The vehicle information system also includes a client terminal that acquires from the vehicle information server a selected vehicle-specific vehicle information group consisting of one or more vehicle-specific vehicle information groups selected in response to a request from each vehicle-specific vehicle information group, and displays the acquired selected vehicle-specific vehicle information group on a display unit. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-097789 Summary of the Invention [Problem to be solved by the invention]

[0004] However, there is room for further improvement in such vehicle information systems in terms of the configuration for providing mobility support for moving bodies such as vehicles.

[0005] The present invention has been made in consideration of the above circumstances, and aims to provide a mobility assistance device, a mobility assistance method, a mobility assistance program, and a mobility assistance system that can provide good mobility assistance for moving bodies such as vehicles. [Means for solving the problem]

[0006] In order to achieve the above-mentioned object, the mobility assistance device of the present invention has an acquisition unit that acquires captured images of scenery in at least the direction of travel of the mobile body and location information indicating the capture location of the captured images, which are transmitted from the mobile body; a detection unit that detects an incident that has occurred by analyzing the acquired captured images; and a notification unit that notifies the mobile body that the detected incident has occurred.

[0007] In addition, in order to achieve the above-mentioned object, the mobility assistance method of the present invention includes an acquisition step in which an acquisition unit acquires an image of the scenery in at least the direction of travel of the mobile body and location information indicating the image capture location of the image, which are transmitted from the mobile body; a detection step in which a detection unit detects an incident that has occurred by analyzing the image acquired in the acquisition step; and a notification step in which a notification unit notifies the mobile body that the incident detected in the detection step has occurred.

[0008] In addition, in order to achieve the above-mentioned object, the mobility assistance program of the present invention is characterized by causing a computer to function as an acquisition unit that acquires captured images of scenery in at least the direction of travel of the mobile body and location information indicating the capture location of the captured images, which are sent from the mobile body; a detection unit that detects an incident that has occurred by analyzing the acquired captured images; and a notification unit that notifies the mobile body that a detected incident has occurred.

[0009] In addition, in order to achieve the above-mentioned object, the mobility assistance system of the present invention includes a mobility assistance device that includes a mobile body that transmits an image of at least the scenery in the direction of travel and location information indicating the image capture location of the image, an acquisition unit that acquires the image and location information transmitted from the mobile body, a detection unit that detects an incident that has occurred by analyzing the acquired image, and a notification unit that notifies the mobile body that the detected incident has occurred. [Effects of the Invention]

[0010] The present invention has an effect of being able to provide good movement support for a moving body such as a vehicle. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram showing the system configuration of a driving assistance system according to a first embodiment of the present invention. [Figure 2] FIG. 2 is a functional block diagram of each function realized by the control unit of the center device operating based on the driving support program. [Figure 3] FIG. 3 is a flowchart showing the flow of operations performed by the center device to store data transmitted from each vehicle. [Figure 4] FIG. 4 is a flowchart showing the flow of the virtual space map creation operation. [Figure 5] FIG. 5 is a diagram illustrating an example of a virtual space map. [Figure 6] FIG. 6 is a flowchart showing the flow of a notification process of an occurring incident in the output control unit. [Figure 7] FIG. 7 is a schematic diagram of the driving assistance system according to the first embodiment. [Figure 8] FIG. 8 is a diagram illustrating a system configuration of a driving assistance system according to the second embodiment. [Figure 9] FIG. 9 is a functional block diagram of each function of the center device in the second embodiment. [Figure 10]FIG. 10 is a flowchart showing the flow of the operation of storing learning data of incidents. [Figure 11] FIG. 11 is a schematic diagram showing an incident learning operation of the center device in the second embodiment. [Figure 12] FIG. 12 is a diagram for explaining the operation of registering a location where an incident is expected to occur in the virtual space map. [Figure 13] FIG. 13 is a flowchart showing the flow of the notification operation of the predicted point of occurrence of an incident. [Figure 14] FIG. 14 is a schematic diagram of the notification operation of the predicted point of occurrence of an incident. [Figure 15] FIG. 15 is another schematic diagram of the notification operation of the predicted point of occurrence of an incident. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. However, the present invention is not limited to these embodiments. Furthermore, the components in the following embodiments include those that are easily replaceable by those skilled in the art, or those that are substantially the same.

[0013] [First embodiment] (System Configuration) First, Fig. 1 is a diagram showing the system configuration of a driving assistance system 1 according to a first embodiment, which is an application example of the present invention. This driving assistance system 1 includes a driving assistance device 3 provided in each vehicle 2, such as a public transportation facility such as a passenger car, a freight truck, a bus, or a personal mobility vehicle, and a center device 4 that provides each vehicle 2 with driving assistance information, such as road conditions corresponding to the traveling direction of the vehicle 2. The driving assistance devices 3 of each vehicle 2 and the center device 4 are connected to each other via a wireless base station 5 and a network 6. The driving assistance system 1 is an example of a mobility assistance system. The vehicle 2 is an example of a mobile object. The center device 4 is an example of a mobility assistance device.

[0014] The wireless base station 5 may be, for example, a pole-shaped wireless communication device installed along a road, or a wireless communication device installed on the roof of a building or the like that enables wireless communication over a wide area, such as a radius of several kilometers. The network 6 may be, for example, a wide area network such as the Internet.

[0015] A server device 7 of the traffic information center is also connected to the network 6. A memory unit 19 of the server device 7 of the traffic information center stores general-purpose data indicating the current road conditions at various locations, etc. The center device 4 can obtain this data from the server device 19 of the traffic information center.

[0016] As will be described later, the center device 4 takes into consideration general-purpose data acquired from the server device 19 of the traffic information center and video data transmitted from the driving assistance device 3 of each vehicle 2. The center device 4 then detects the occurrence point of an "incident," which is some kind of event that the driver should be notified of, such as an accident, a fallen object, or a traffic jam, and transmits driving assistance information to vehicles 2 traveling in a direction approaching the detected incident occurrence point.

[0017] (Configuration of driving assistance device) The driving assistance device 3 provided in each vehicle 2 has a location information acquisition unit 11 that acquires the current location of the vehicle 2 using, for example, a GPS (Global Positioning System) sensor, and a camera unit 12 that captures an image of at least the scenery ahead of the vehicle 2. The driving assistance device 3 also has a display unit 12 that displays driving assistance information provided from the center device 4, and a control unit 14 that controls the operation of each unit of the driving assistance device 3. The driving assistance device 3 also has a memory unit 15 that stores a driving assistance program, and a wireless communication unit 16 that performs wireless communication with the wireless base station 5.

[0018] The control unit 14 of the driving assistance device 3 operates based on a driving assistance program stored in the memory unit 15, and transmits captured images (moving images or still images, hereinafter referred to as video data) of the scenery in the traveling direction (forward) of the vehicle captured by the camera unit 12, as well as position information, to the center device 4 via the wireless communication unit 16. Note that, together with the image of the scenery in front of the vehicle, video data of the scenery to the left and right of the vehicle and / or video data of the scenery behind the vehicle may also be transmitted to the center device 4. The position information is information indicating the position of the vehicle 2 (= image capture position).

[0019] Furthermore, the control unit 14 of the driving assistance device 3 operates based on a driving assistance program stored in the memory unit 15, thereby controlling the display unit 13 to display the driving assistance information received from the center device 4. As will be described in detail later, in the case of the driving assistance system 1 of the first embodiment, the center device 4 collects and analyzes video data of scenery captured by the driving assistance device 3 of each vehicle 2, and detects the occurrence point of an "incident," which is some kind of event that the driver should be notified of, such as an accident, fallen object, or traffic congestion. The center device 4 then provides driving assistance information, including information about the occurrence of an incident and detour routes, to vehicles approaching this incident occurrence point.

[0020] The control unit 14 of the driving assistance device 3 controls the display of the driving assistance information received from the center device 4 on the display unit 13. This allows the driver to recognize that an incident has occurred in the direction of travel of the vehicle before reaching the point where the incident has occurred, and to take appropriate measures such as detouring.

[0021] (Configuration of center equipment) The center device 4 has a memory unit 21 in which a driving assistance program and map data are stored, and which is also equipped with a first memory unit 24 that stores, as accumulated data, images of the scenery ahead and other data captured and transmitted by each vehicle 2. The center device 4 also has a control unit 22 that controls the operation of each unit of the center device 4, and a communication unit 23 that communicates with the driving assistance device 3 of each vehicle 2.

[0022] 2 is a functional block diagram of each function realized by the control unit 22 of the center device 4 operating based on the driving assistance program. As shown in this Fig. 2, the control unit 22 realizes each function of an analysis unit 31, a virtual space map creation unit 32, and an output control unit 33 by executing the driving assistance program.

[0023] The analysis unit 31 includes an acquisition unit 41, a memory control unit 42, a traffic condition processing unit 43, and an incident detection unit 44 (an example of a detection unit). The acquisition unit 41 acquires position information and video data from the driving assistance device 3 of each vehicle 2. The memory control unit 42 stores the position information and video data acquired from the driving assistance device 3 of each vehicle 2 in the first memory unit 24 as accumulated data.

[0024] The traffic condition processing unit 43 detects the current road conditions and the like based on the general-purpose data acquired from the traffic center server device 19. The incident detection unit 43 analyzes the accumulated data stored in the first storage unit 24 and also refers to the general-purpose data acquired from the traffic center server device 19 to detect whether an incident has occurred and the point at which the incident has occurred.

[0025] The virtual space map creation unit 32 arranges the video data and position information from each vehicle 2 at the same position as the actual position on the map data, forms an actual image in the virtual space, and creates a virtual space similar to the actual scenery. Then, a virtual space map is created on this virtual space map, in which the occurrence points of incidents detected by the incident detection unit 43 are arranged.

[0026] The output control unit 33 includes a trigger detection unit 47, an information collection unit 48, and an information provision unit 49. The trigger detection unit 47 detects, as a trigger, when the distance between the vehicle 2 traveling toward the incident point and the incident occurrence point becomes equal to or less than a predetermined value, or when there is a request from the vehicle 2 to acquire incident information. The information collection unit 48 collects information such as the incident occurrence point, details, and detour route to be provided to each vehicle 2. The information provision unit 49 (an example of a notification unit) transmits (provides) the incident information formed by the information collection unit 48 to a predetermined vehicle via the communication unit 23.

[0027] In this example, the analysis unit 31 to the output control unit 33 are realized by software using a driving assistance program, but all or part of these may be realized by hardware such as an IC (Integrated Circuit).

[0028] The driving assistance program may be provided by being recorded in the form of file information in an installable or executable format on a computer-readable recording medium such as a CD-ROM or a flexible disk (FD).The driving assistance program may be provided by being recorded on a computer-readable recording medium such as a CD-R, a DVD (Digital Versatile Disk), a Blu-ray (registered trademark) disk, or a semiconductor memory.The driving assistance program may be provided by being installed via a network such as the Internet.The driving assistance program may be provided by being pre-installed in a ROM or the like within a device.

[0029] (Data accumulation operation) Fig. 3 is a flowchart showing the flow of operations for storing data transmitted from each vehicle 2 in the center device 4. The control unit 22 of the center device 4 reads a driving assistance program stored in the memory unit 21, thereby starting the processing shown in the flowchart of Fig. 3. When the processing shown in the flowchart of Fig. 3 starts, the acquisition unit 41 shown in Fig. 2 acquires, via the network 6, the position information of each vehicle 2 and video data (which may be moving images or still images) captured by the camera unit 12 of each vehicle 2, which are transmitted from the driving assistance device 3 of each vehicle 2 (steps S1 and S2).

[0030] That is, each vehicle 2 captures images of the surrounding scenery including the direction of travel and the oncoming traffic lane, and transmits the image data together with the position information of the vehicle 2 to the center device 4 via the network 6. The center device 4 acquires and stores the position information and image data constantly transmitted from each vehicle 2.

[0031] The storage control unit 42 associates the video data acquired from each vehicle 2 with the position information and controls storage of the data in the first storage unit 24 of the storage unit 21 as accumulated data (step S3). The center device 4 repeats this storage operation every time it acquires position information and video data from each vehicle 2. As a result, the video data corresponding to the traveling position of each vehicle 2 is stored as accumulated data in the first storage unit 24.

[0032] (Virtual space map creation) When the accumulated data is stored in the first storage unit 24 in this manner, the virtual space map creation unit 32 shown in FIG. 2 learns the accumulated data based on artificial intelligence (AI) and creates a virtual space map that shows the current road conditions at each location, etc. FIG. 4 is a flowchart showing the flow of the virtual space map creation operation by the virtual space map creation unit 32. The control unit 22 of the center device 4 operates based on a driving assistance program, and the processing shown in the flowchart of FIG. 4 is started. When the processing shown in the flowchart of FIG. 4 is started, the virtual space map creation unit 32 shown in FIG. 2 acquires the accumulated data stored in the first storage unit 24 (step S11). In addition, the virtual space map creation unit 32 acquires map data stored in the storage unit 21 (step S12).

[0033] 2 acquires general-purpose data indicating the current traffic conditions at each location and whether or not an incident such as an accident has occurred, for example, from the server device 7 of the traffic information center shown in FIG. 1. The traffic condition processing unit 43 performs data processing on the general-purpose data to reflect the data on the virtual space map. The virtual space map creation unit 32 grasps the current traffic conditions at each location based on the general-purpose data that has been subjected to such data processing (step S13).

[0034] Next, the incident detection unit 44 shown in FIG. 2 detects an incident by analyzing the accumulated data (step S14). As an example, the incident detection unit 44 · Whether or not an incident occurred; - Whether or not traffic congestion occurs, How many cars are stuck in the traffic jam from the beginning to the end? -How fast each car is moving (or stopped) during the traffic jam Lane restrictions or road closures? Whether the emergency vehicle has arrived or not Road conditions (scattered cargo, snow accumulation, chemicals flowing, etc.), etc. are detected.

[0035] Furthermore, if a digital tachograph device is provided in the vehicle 2, the incident detection unit 44 detects incidents by acquiring information such as sudden braking, sudden acceleration, and sudden steering, thereby enabling incident detection to be performed more simply and with higher accuracy.

[0036] When detecting an incident, the incident detection unit 44 determines whether the detected incident satisfies a predetermined condition (step S15).

[0037] That is, in step S15, the incident detection unit 44 determines whether the detected incident is an incident that requires notification to each vehicle 2, such as a traffic jam of 1 km or more or an accident currently being handled (determines the importance of the incident). If the detected incident is not important enough to require notification to each vehicle 2 (if the incident does not satisfy the predetermined condition: step S15: No), the virtual space map creation unit 32 ends the processing of the flowchart in Fig. 4 without reflecting the detected incident in the virtual map.

[0038] On the other hand, if an incident that requires notification to each vehicle 2 is detected (if an incident that meets or exceeds a predetermined condition is detected: Step S15: Yes), the incident detection unit 44 detects the location where the detected incident is occurring (incident occurrence point) based on the accumulated data (Step S16).

[0039] Then, the virtual space map creation unit 32 creates a virtual space map that reflects the current traffic conditions and incident occurrence points at each location that are grasped based on the general-purpose data acquired from the traffic information center in step S13 (step S17).

[0040] 5 is a diagram showing an example of a virtual space map created in this way. The virtual space map creation unit 32 creates a real image in the virtual space by arranging the video data transmitted from each vehicle 2 at the same position as the real position on the map data based on the position information (latitude, longitude, direction). This makes it possible to create a virtual space map that is similar to the real scenery.

[0041] (Incident occurrence notification behavior) Next, the driving assistance system 1 of the first embodiment notifies each vehicle 2 of an occurring incident based on the virtual space map created in this way. Figure 6 is a flowchart showing the flow of the notification process of an occurring incident in the output control unit 33 shown in Figure 2. The process of the flowchart in Figure 6 starts when the above-mentioned virtual space map is created. In step S21, the trigger detection unit 47 of the output control unit 33 determines whether or not an output request trigger of any vehicle 2 has been detected.

[0042] As an example, when the driver operates the driving assistance device 3, a request for acquiring incident information is transmitted to the center device 4. Receipt of the request for acquiring incident information at the center device 4 can be regarded as the above-mentioned "output request trigger." Furthermore, the center device 4 is aware of the current position of each vehicle 2 based on the position information transmitted from each vehicle 2 together with the video data. Therefore, detection of a vehicle 2 whose distance to the incident occurrence point is less than a predetermined distance can be regarded as the above-mentioned "output request trigger."

[0043] Next, when such an output request trigger is detected, the information collection unit 48 refers to the virtual space map and confirms the incident occurrence point corresponding to the current position of the vehicle (step S22). Then, the information collection unit 48 collects various information related to the incident occurring at the confirmed incident occurrence point (step S23). At this time, the information collection unit 48 also takes into consideration general-purpose data indicating the current road conditions and the like provided by the traffic information center 7.

[0044] Although this is merely one example, specifically, the information collection unit 48 collects information related to the incident, such as the type of incident occurring, such as an accident, construction work, falling objects, or traffic congestion, and in the case of traffic congestion, the distance of the traffic congestion and information indicating detour routes.

[0045] Then, the information providing unit 49 of the output control unit 33 shown in FIG. 2 notifies the driving assistance device 3 of the vehicle 2 that detected the above-mentioned "output request trigger" of the incident occurrence point and information related to the incident (step S24).

[0046] Here, when a traffic jam occurs, the information collection unit 48 detects a detour route corresponding to the destination of the vehicles in the traffic jam, and at this time, it also predicts the congestion on the detour route based on the number of vehicles in the traffic jam and the number of routes on the detour route, etc., and recommends a detour route that will allow the vehicle to reach the destination in the shortest time.

[0047] Furthermore, the information collection unit 48 notifies a vehicle to which an emergency vehicle is approaching of information indicating the direction of the emergency vehicle (information indicating the direction from which the emergency vehicle is approaching). Furthermore, when there are multiple lanes, the information collection unit 48 notifies each vehicle 2 of information to assist the emergency vehicle in smoothly traveling, such as "move to the right turn lane" for a vehicle in the right lane of a three-lane road.

[0048] Fig. 7 is a schematic diagram of the driving assistance system 1 of the first embodiment. In Fig. 7, the vehicles indicated by diagonal lines, i.e., vehicle A, vehicle C, and vehicle F, are vehicles equipped with a driving assistance device 3. The vehicles not indicated by diagonal lines, i.e., vehicle B, vehicle D, and vehicle E, are vehicles not equipped with a driving assistance device 3.

[0049] Vehicles A, C, and F equipped with the driving assistance device 3 constantly transmit video data of at least the scenery ahead of vehicle 2, captured by the camera unit 12, together with location information, to a so-called cloud-based center device 4 (data upload; see the dotted arrow in FIG. 7). The center device 4 stores the video data received from vehicles A, C, and F in a first storage unit 24 in association with the location information. The center device 4 also analyzes the video data stored in the first storage unit 24 in an analysis unit 31, and creates a virtual space map including an incident occurrence point IP in a virtual space map creation unit 32.

[0050] Then, the center device 4 notifies the vehicle 2 that detected the above-mentioned "output request trigger" of the incident occurrence point IP and information related to the incident (see the solid arrow in FIG. 7 ), among vehicles A, C, and F in which the driving assistance device 3 is installed. The incident occurrence point IP and information related to the incident are displayed on the display units 13 of vehicles A, C, and F in which the driving assistance device 3 is installed.

[0051] This allows the driver of vehicle 2 that detects the "output request trigger" to know whether an incident has occurred, such as the occurrence of an accident, the occurrence of a fallen object, whether passage is possible, whether a traffic jam has occurred, and the distance of the traffic jam, before reaching the incident point. Furthermore, if a detour exists, such incident information is also provided, which includes information indicating the detour. This allows the driver to consider in advance how to avoid the incident by using a detour.

[0052] 7, the situation of the incident can be analyzed based on not only information from vehicle C in the same lane as vehicle A and traveling in the same direction, but also information from oncoming vehicle F in the oncoming lane, traveling ahead in the direction of travel. Therefore, the virtual space map creation unit 32 can create a virtual space map that captures the situation of the incident occurrence point IP from a bird's-eye view. This makes it possible to grasp, for example, whether or not an emergency vehicle has arrived ahead of the incident occurrence point IP, the number of vehicles in traffic (the length of the traffic jam), and the like, and to provide incident occurrence information that shows the situation of the incident in more detail.

[0053] (Effects of the first embodiment) As is clear from the above explanation, in the driving assistance system 1 of the first embodiment, the center device 4 collects captured images of the scenery outside each vehicle 2 together with location information to form incident occurrence information indicating whether or not an incident has occurred. The center device 4 then provides the incident occurrence information to a vehicle that has made an incident acquisition request or to a vehicle that is close to the incident occurrence point.

[0054] This allows vehicles 2 that are close to the incident occurrence point to share incident occurrence information, making it possible to avoid incidents in advance and create smooth road conditions.

[0055] Furthermore, the driving assistance system 1 of the first embodiment does not require the installation of infrastructure equipment such as incident sensing equipment, nor does it require the installation of new on-board equipment in the vehicle 2, and can be configured inexpensively and simply using existing on-board equipment (cameras, etc.).

[0056] Furthermore, the virtual space map creation unit 32 can create a virtual space map that captures the situation at the incident occurrence point IP from a bird's-eye view. This makes it possible to grasp, for example, the situation ahead of the incident occurrence point IP, whether an emergency vehicle has arrived, the number of vehicles in traffic (length of traffic jam) from the incident occurrence point IP, and the like, and to provide incident occurrence information that shows the situation of the incident in more detail.

[0057] (Modification of the first embodiment) In the above description of the first embodiment, the center device 4 analyzes the occurrence of incidents on roads. However, the center device 4 may analyze road conditions, such as the congestion of sidewalks and the presence or absence of parked vehicles, based on the video data transmitted from the vehicles 2, and provide the results to each vehicle 2.

[0058] In addition, although the device to which the information is provided is the driving assistance device 3 installed in the vehicle 2, the information may also be provided to a portable device (which may be a personal computer device) such as a smartphone of the driver or passenger.

[0059] 2, the analysis unit 31 may be provided on the driving assistance device 3 side of each vehicle 2, and each vehicle may analyze whether or not the above-mentioned incident has occurred, and the analysis results may be transmitted to the center device 4 and shared with surrounding vehicles. In this case, the calculation load on the center device 4 can be significantly reduced.

[0060] Alternatively, the incident detection unit 44 may divide the virtual space map into several divided areas and detect an incident for each divided area. In this case, the trigger detection unit 47 detects whether or not the above-mentioned "output request trigger" exists for each divided area, and the information provision unit 49 provides incident occurrence information to a vehicle 2 in which an "output request trigger" is detected within the divided area. That is, the information provision unit 49 determines the current location of the vehicle 2 based on the location information, and provides the above-mentioned notification to a vehicle 2 that has become located in the divided area in which an incident has been detected. In this way, incident detection and provision of incident occurrence information are performed for each divided area, thereby reducing the computational load on the center device 4.

[0061] [Second embodiment] Next, a driving assistance system according to a second embodiment of the present invention will be described. The example of the first embodiment described above is an example in which the approximate current road conditions are analyzed and shared with each vehicle 2. In contrast, the example of the second embodiment is an example in which incidents that have occurred in the past and the circumstances under which they occurred are learned, and when a situation similar to the circumstances under which an incident occurred occurs, the occurrence of an incident is predicted and notified to the vehicle 2, thereby preventing the occurrence of an incident.

[0062] The first embodiment described above and the second embodiment described below differ only in this respect, so only the differences between the two will be explained below, and redundant explanations will be omitted.

[0063] (System configuration of the second embodiment) FIG. 8 is a diagram showing the system configuration of a driving assistance system 50 according to the second embodiment. In contrast to the first embodiment described above, in the second embodiment, the center device 4 includes a first storage unit 24 and a second storage unit 25 in the storage unit 21. As described above, the first storage unit 24 stores accumulated data including video data and location information from each vehicle 2. In contrast, the second storage unit 25 stores incident learning data that has learned about past incidents and the circumstances under which they occurred. In the case of the driving assistance system 50 according to the second embodiment, an incident is predicted based on this incident learning data, and the target vehicle 2 is notified of the occurrence.

[0064] In the second embodiment, various environmental information such as time information such as date and time, weather information, seasonal information, points where traffic jams frequently occur, and locations where birds and animals appear is acquired via one or more information server devices 8. The center device 4 performs learning taking such environmental information into consideration to form incident learning data and store it in the second storage unit 25. The center device 4 also takes such environmental information into consideration to predict the occurrence of an incident and notifies the target vehicle 2 of the occurrence.

[0065] (Configuration of Center Device in Second Embodiment) 9 is a functional block diagram of the functions of the center device 4 in the second embodiment, which are realized by the control unit 22 of the center device 4 operating based on the driving assistance program. As shown in this Fig. 9, the control unit 22 executes the driving assistance program to realize the functions of the above-mentioned analysis unit 31, virtual space map creation unit 32, and output control unit 33, as well as the function of the learning and memory control unit 34.

[0066] The learning and memory control unit 34 includes an acquisition unit 61, a probability calculation unit 62, and a memory control unit 63. When learning about an incident, the acquisition unit 61 acquires stored data from the first memory unit 24. When learning about an incident, the acquisition unit 61 also acquires general-purpose data from the server device 7 of the traffic information center and acquires environmental information from the information server device 8.

[0067] The probability calculation unit 62 (an example of a calculation unit) calculates the occurrence probability of an incident. The memory control unit 63 controls and stores information indicating incidents whose occurrence probability is equal to or greater than a predetermined value, together with environmental information, in the second memory unit 25 as learning data.

[0068] (Accumulation of learning data) 10 is a flowchart showing the flow of the operation of storing learning data of an incident. In the flowchart of FIG. 10, when it is time to learn an incident, the control unit 22 starts processing based on the driving assistance program. In step S31, the acquisition unit 61 of the learning and memory control unit 34 acquires the position information and video data of each vehicle 2, which are stored data transmitted from the driving assistance device 3 of each vehicle 2 and stored in the first memory unit 24. Also in step S31, the acquisition unit 61 acquires the above-mentioned general-purpose data from the server device 7 of the traffic information center, and acquires environmental information from the information server device 8.

[0069] As an example, environmental information may include: Date, time, day of the week, time period: Date, time, day of the week, time period, rush hour, dusk, early morning or night, etc. Weather: sunlight (position of the sun), cloudy, rain, snow, etc. Road conditions: good, wet, snowy, etc. Visibility conditions: afternoon sun at dusk, fog, etc. Seasonal timing: construction periods, moving season, year-end and New Year party season, weekends, long holidays, new school entrance season, etc. Locations: Complex branching roads, roads with a lot of street parking, store entrances and exits, bus routes, narrow roads, school routes, bus stops with a lot of accidents, railroad crossings that don't open, points where accidents frequently occur, near schools or kindergartens, points where traffic jams frequently occur, blind spots, places where birds and animals appear, etc. The above various information is acquired from the server device 7 or the information server device 8 at the traffic center.

[0070] Next, in step S32, the probability calculation unit 62 calculates the occurrence probability of the incident that has occurred for each environment. The memory control unit 63 determines whether the occurrence probability of the incident calculated by the probability calculation unit 62 is equal to or greater than a predetermined value (step S33). If the occurrence probability of the incident calculated by the probability calculation unit 62 is less than a predetermined value (step S33: No), the memory control unit 63 does not store information about the incident and ends the processing of the flowchart in FIG. 10.

[0071] In contrast, if the probability of occurrence of the incident calculated by the probability calculation unit 62 is greater than or equal to a predetermined value (step S33: Yes), the memory control unit 63 stores environmental information indicating the content, location, and environment of the incident whose probability of occurrence is greater than or equal to a predetermined value in the second memory unit 25 in step S34.

[0072] Fig. 11 is a schematic diagram showing the flow of the learning operation for such incidents. As shown in Fig. 11, information indicating incidents with a predetermined occurrence probability or higher is stored in second storage unit 25 along with a unique identification number and environmental information such as date, time, day of the week, location, and weather.

[0073] (Registering predicted incident locations on a virtual space map) Next, the virtual space map creation unit 32 creates a virtual space map in which locations where incidents are predicted to occur due to a high probability of occurrence in the past are registered for each divided area, as shown in Fig. 12. In the example of Fig. 12, a predetermined geographical area is divided into four divided areas, area A1 to area A4. If there is a location in area A1 to area A4 where an incident is predicted to occur with a high probability, the virtual space map creation unit 32 registers this location as a predicted location where the incident is predicted to occur.

[0074] That is, there are no locations in areas A1 and A4 where an incident is predicted to occur, and therefore the virtual space map creation unit 32 does not register locations in areas A1 and A4 where an incident is predicted to occur.

[0075] On the other hand, suppose that there is a tunnel in area A2, where accidents and other incidents have occurred multiple times in the past. Therefore, the virtual space map creation unit 32 registers this tunnel as the location of an incident of alert level 3, for example. When an incident occurs in a tunnel, the virtual space map creation unit 32 also registers the location of the incident, adding environmental information such as the date, time, weather, and road conditions.

[0076] As a result, the location of the incident is registered on the virtual space map along with the conditions for the incident to occur. To explain further, for example, if an incident such as an accident has occurred in a tunnel in the past at night on a rainy day, the environmental information "at night on a rainy day" is added, and the location of the tunnel is registered on the virtual space map as a location where an incident is predicted to occur. Therefore, the conditions for the incident to occur are clarified before the location where an incident is predicted to occur is registered.

[0077] Similarly, suppose that there is a construction site in area A3, and that construction traffic congestion incidents have occurred multiple times in the past on the road in front of this construction site. Therefore, the virtual space map creation unit 32 registers the road in front of this construction site as the location of an incident of alert level 5, for example. In addition, the virtual space map creation unit 32 registers the location of the incident, adding environmental information such as the date, time, weather, and road conditions when a construction traffic congestion incident occurred on the road in front of the construction site.

[0078] For example, suppose that in the past, construction traffic congestion did not occur on rainy days on the road in front of a construction site, but did occur on sunny and cloudy days between 2:00 PM and 5:00 PM. In this case, the environmental information "2:00 PM to 5:00 PM on sunny and cloudy days" is added, and the location of the road in front of the construction site is registered on the virtual space map as a location where an incident is predicted to occur. Therefore, the conditions for incident occurrence are clarified, and then locations where incidents are predicted to occur are registered.

[0079] (Notification behavior based on predicted location of incident) Next, based on the virtual space map created in this way, the output control unit 33 notifies the vehicle 2 that detected the trigger as described above that an incident is predicted to occur. That is, when the environment at the time of notification matches the incident occurrence condition, the output control unit 33 notifies the vehicle 2 that is located in the divided area including the incident occurrence position that an incident is predicted to occur. FIG. 13 is a flowchart showing the flow of such an incident prediction notification operation. The trigger detection unit 47 of the output control unit 33 shown in FIG. 9 determines whether the vehicle is located within a predetermined distance from the point where the incident is predicted to occur and whether the current environment matches the incident occurrence condition (step S41). Note that in step S41, the trigger detection unit 47 may also determine whether there is a request for incident information from the vehicle 2 and whether the current environment matches the incident occurrence condition.

[0080] That is, the trigger detection unit 47 constantly monitors whether the vehicle 2 is located within a predetermined distance, such as within a 50-meter radius, from the point where an incident is predicted to occur (step S41). When the vehicle 2 is located within the predetermined distance, such as within a 50-meter radius, from the point where an incident is predicted to occur and the current environment matches the conditions for the occurrence of the incident, such as a rainy evening (step S41: Yes), the information provision unit 49 notifies the vehicle 2 that it is approaching the point where an incident is predicted to occur and that caution is required (step S42). This notification is displayed on the display unit 13 of the vehicle 2 (or may be output as audio).

[0081] 14 and 15 are schematic diagrams of the notification operation of such a predicted incident occurrence point. In the example of Fig. 14, many traffic accidents have occurred in front of a crosswalk in the past during the dim light of the evening on rainy days, and this crosswalk is registered on the virtual space map as a point IP where a traffic accident incident is predicted to occur. Also, vehicle A and vehicle D are equipped with driving assistance devices 3, which are capable of receiving notifications of predicted incidents.

[0082] Suppose vehicle A and vehicle B have entered within a radius of, for example, 50 meters from a crosswalk where traffic accidents frequently occur, as shown in FIG. 15. Suppose the current environment is a dimly lit time slot in the evening on a rainy day, matching the conditions of a traffic accident that occurred at that crosswalk in the past. In this case, information provider 49 notifies vehicle A and vehicle B that they are approaching point IP where a past incident occurred, and that an incident is predicted to occur, so that they should drive with caution. This allows the drivers of vehicle A and vehicle B to drive their vehicles while paying attention to the crosswalk where an incident is predicted to occur, thereby preventing incidents from occurring.

[0083] (Effects of the second embodiment) As is clear from the above description, the driving assistance system 50 of the second embodiment stores incident learning data that learns the locations and conditions under which incidents have occurred in the past in the second storage unit 25. Then, when the current environment matches the conditions under which an incident occurred, the driving assistance system 50 notifies a vehicle that is located within a predetermined distance from the location where the incident occurred that an incident has occurred in the past and that caution is required when driving.

[0084] This not only provides the same effects as the first embodiment described above, but also allows the driver to drive the vehicle while paying attention to areas where incidents are expected to occur, thereby preventing incidents from occurring in advance.

[0085] Furthermore, by predicting and notifying the occurrence of an incident based on incidents with a predetermined or higher occurrence probability, it is possible to notify incidents that truly deserve notification.

[0086] Furthermore, the virtual space map creation unit 32 divides a predetermined geographical range into multiple divided areas (for example, areas A1 to A4), and creates a virtual space map for each divided area that reflects incidents and occurrence conditions. This allows incident prediction processing, notification processing, etc. to be performed for each divided area, thereby reducing the calculation load on the center device 4.

[0087] In addition, traffic accidents can be predicted and drivers can be alerted to ensure road safety.

[0088] In addition, traffic congestion can be predicted on roads where time periods are useful for prediction, such as bus routes or entrances and exits to popular stores, and traffic congestion can be alleviated.

[0089] In addition, for dangerous bus stops or railroad crossings that do not appear dangerous but are frequent sites of accidents, the system can warn drivers who are not familiar with driving at those locations, leading to improved traffic safety.

[0090] In addition, by predicting incidents on routes near schools, kindergartens, or daycare centers, traffic accidents involving children can be reduced.

[0091] In addition, by informing drivers of places where accidents frequently occur, such as blind spots that are difficult to see visually, it is possible to reduce the number of accidents.

[0092] In addition, birds and animals pass through similar points called animal trails, but these trails are invisible to humans. For this reason, by informing people of areas where bird and animal accidents frequently occur, it is possible to reduce bird and animal damage.

[0093] The present invention is not limited to the above-described embodiment, and various modifications are possible within the scope of the claims.

[0094] For example, in the above-described embodiments, vehicle 2 is used as an example of a moving body, and image data captured by vehicle 2 is shared with surrounding vehicles that analyze road conditions. However, for example, a robot traveling within a factory may be used as the moving body, and the presence or absence of an incident inside or outside the factory may be detected by analyzing image data and position information captured by a camera device attached to the robot, and the robot's traveling control may be performed based on the detection results.

[0095] Alternatively, for example, a mobile terminal device owned by each user may be used as the mobile object, and video data captured by this mobile terminal device may be collected by the center device 4 to analyze the congestion situation on the sidewalk, allowing information to be shared among surrounding users.

[0096] In either case, the same effects as those described above can be achieved, such as being able to recognize the occurrence of an incident in advance and avoiding congestion and collisions between robots or humans.

[0097] The results of incident analysis may also be applied to driving assistance for vehicles equipped with autonomous driving functions.

[0098] Furthermore, the driving assistance systems 1 and 50 of the embodiments may be configured by appropriately combining the components of the above-described embodiments and modifications. [Explanation of symbols]

[0099] 1. Driving assistance systems 2 vehicles 3 Driving assistance devices 4. Center equipment 5. Wireless base stations 6 Network 7 Traffic Information Center 8 Information server device 11 Location information acquisition section 12 Camera Section 13 Display section 14 Control Unit 15 Storage section 16. Radio Communication Department 21 Memory section 22 Control Unit 23 Communications Department 24 First memory unit 25 Second memory section 31 Analysis Department 32 Virtual Space Map Creation Department 33 Output control section 34 Learning and memory control section 41 Acquisition Department 42 Memory control unit 43 Traffic Condition Processing Unit 44 Incident detection unit 47 Trigger detection section 48 Information Gathering Department 49 Information provision department 61 Acquisition Department 62 Probability Calculation Section 63 Memory control unit

Claims

1. an acquisition unit that acquires captured images of scenery at least in the moving direction of the moving body, transmitted from the moving body, and location information indicating the capturing positions of the captured images; a detection unit that detects an incident by analyzing the acquired captured image; a virtual space map creation unit that creates a virtual space map as a real image in a virtual space by arranging the captured image at the same position as the actual position on map information based on the location information, and reflects the detected incident and its occurrence position on the virtual space map; a notification unit that notifies the mobile object that the incident has occurred based on the virtual space map; A mobility assistance device having the same.

2. The notification unit grasps the current location of the mobile body based on the location information, and sends the notification to a mobile body that is located within a predetermined distance from the location where the incident occurred on the virtual space map, or sends the notification to a mobile body that has transmitted a request to obtain the notification. The mobility support device according to claim 1 .

3. the detection unit divides a predetermined geographical range of the virtual space map into a plurality of divided areas and detects the incident for each divided area; The notification unit grasps a current location of the mobile object based on the location information, and issues the notification to the mobile object that has become located in the divided area in which the incident was detected. The movement support device according to claim 2 .

4. a memory control unit that stores the incident detected by the detection unit in a memory unit together with occurrence conditions that indicate an environment at the time of occurrence of the incident, When the environment at the time of issuing the notification matches the occurrence condition, the notification unit issues a notification predicting the occurrence of an incident to a moving body that has become located within a predetermined distance from the position where the incident occurred on the virtual space map or a moving body that has transmitted a request to receive the notification. The movement support device according to claim 2 .

5. the virtual space map creation unit divides a predetermined geographical range into a plurality of divided areas, and creates the virtual space map for each divided area that reflects the incident and the occurrence condition; The notification unit issues the notification to a moving object that is located in the divided area including the location where the incident occurred, when the environment at the time of issuing the notification matches the occurrence condition. The movement support device according to claim 4,

6. an acquiring step in which an acquiring unit acquires captured images of scenery at least in the traveling direction of the moving body, transmitted from the moving body, and position information indicating the capturing positions of the captured images; a detection step in which a detection unit analyzes the captured image acquired in the acquisition step to detect an occurring incident; a virtual space map creation unit creating a virtual space map as a real image in a virtual space by arranging the captured image at the same position as the real position on map information based on the position information, and reflecting the detected incident and the occurrence position on the virtual space map; a notification step in which a notification unit notifies the mobile object that the incident has occurred based on the virtual space map; A mobility assistance method comprising:

7. Computer, an acquisition unit that acquires captured images of scenery at least in the moving direction of the moving body, transmitted from the moving body, and location information indicating the capturing positions of the captured images; a detection unit that detects an incident by analyzing the acquired captured image; a virtual space map creation unit that creates a virtual space map as a real image in a virtual space by arranging the captured image at the same position as the actual position on map information based on the location information, and reflects the detected incident and its occurrence position on the virtual space map; functioning as a notification unit that notifies the mobile object that the incident has occurred based on the virtual space map; A mobility assistance program featuring:

8. a mobile object that transmits captured images of at least a scene in the traveling direction and position information indicating the capturing position of the captured images; an acquisition unit that acquires the captured image and the location information transmitted from the moving object; a detection unit that detects an incident by analyzing the acquired captured image; a virtual space map creation unit that creates a virtual space map as a real image in a virtual space by arranging the captured image at the same position as the actual position on map information based on the location information, and reflects the detected incident and its occurrence position on the virtual space map; a notification unit that notifies the moving object that the incident has occurred based on the virtual space map; and A mobility assistance system having:

Images