Traffic safety support system and computer program

Abstract

To predict a risk to occur among a part of many traffic participants with a few loads.SOLUTION: A cooperation support device comprises: a prediction unit which predicts future of a plurality of traffic participants; and a cooperation support information notification unit by which a notification object determined from among the plurality of traffic participants is notified of. The prediction unit comprises: a group classification unit which divides the plurality of traffic participants into movement groups G1 to G9 and acquires movement group information including positions, shapes, and movement vectors of the respective movement groups G1 to G9; a first prediction unit which predicts presence / absence of collision among the respective movement groups G1 to G9 on the basis of the movement group information and specifies a collision site in movement groups predicted to collide; and a second prediction unit which determines two or more specific traffic participants from among the plurality of traffic participants on the basis of the collision site and predicts presence / absence of collision among the specific traffic participants when it is predicted to collide by the first prediction unit 622.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present invention relates to a traffic safety support system and a computer program, and more particularly to a traffic safety support system and a computer program that support the safe movement of traffic participants as people or mobile objects. [Background technology]

[0002] In public transportation, various traffic participants, such as moving objects such as four-wheeled automobiles, motorcycles, and bicycles, as well as pedestrians, move at different speeds based on their own will. As a technology for improving the safety and convenience of such traffic participants in public transportation, for example, Patent Document 1 discloses a driving safety device that supports safe driving by vehicle drivers.

[0003] In the driving safety device shown in Patent Document 1, an on-board sensor mounted on the vehicle detects objects around the vehicle, and among the detected objects, a moving object approaching the travel path of the vehicle is determined, and if it is determined that the determined moving object has a possibility of colliding with the vehicle, a notification is given to the driver of the vehicle. In particular, in this invention, when there are multiple moving objects, the multiple moving objects are divided into groups, and the driver is notified once for each group. As a result, when there are multiple moving objects approaching the vehicle, a notification is given for each group, which reduces the annoyance felt by the driver. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2011-76527 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the invention shown in Patent Document 1, the degree of danger is predicted based on information about the surrounding environment acquired by on-board sensors such as a camera or radar mounted on the vehicle, and therefore potential risks that exist outside the detection range of the on-board sensors cannot be grasped. Therefore, in order to provide appropriate support for such potential risks, it is conceivable to aggregate information about traffic participants present in a specified target traffic area in a server communicably connected to each traffic participant, and to obtain an overview of the flow of traffic participants in this target traffic area from the server.

[0006] However, if the huge number of traffic participants in the target traffic area are aggregated on a server in this manner, the processing load on the server will increase, and there is a risk that it will not be possible to provide appropriate assistance to each traffic participant in the target traffic area in real time.

[0007] The present invention aims to provide a traffic safety support system and computer program capable of predicting risks occurring among a portion of a large number of traffic participants in a target traffic area with a small processing load. [Means for solving the problem]

[0008] (1) The traffic safety support system of the present invention comprises a recognition unit that recognizes traffic participants as people or moving bodies in a target traffic area and acquires recognition information regarding each traffic participant; a prediction unit that predicts the future of multiple traffic participants recognized by the recognition unit based on the recognition information; and a notification unit that determines a notification target from among the multiple traffic participants based on the prediction result by the prediction unit and issues a notification to the notification target. The recognition unit acquires information including a position and movement vector of each traffic participant as the recognition information, and the prediction unit comprises a classification unit that divides the multiple traffic participants recognized by the recognition unit into multiple movement groups based on the recognition information and acquires movement group information including the position, shape, and movement vector of each movement group; a first prediction unit that predicts the presence or absence of a collision between each movement group based on the movement group information and identifies a collision site in the movement group predicted to collide; and a second prediction unit that, when a collision is predicted by the first prediction unit, determines two or more specific traffic participants from the multiple traffic participants based on the collision site and predicts the presence or absence of a collision between the specific traffic participants.

[0009] (2) In this case, it is preferable that the traffic safety support system further includes a driving subject information acquisition unit that acquires status information correlated with the driving ability of the driving subject of the moving body recognized as a traffic participant by the recognition unit, and the second prediction unit predicts whether or not a collision will occur between the prediction targets based on the recognition information and the status information for the specific traffic participant.

[0010] (3) In this case, it is preferable that the prediction unit further includes a third prediction unit which predicts a risk to traffic participants present around the specific traffic participant when a collision avoidance action is taken by at least one of the two or more specific traffic participants predicted to collide by the second prediction unit.

[0011] (4) In this case, it is preferable that the notification unit issues a first notification to the specific traffic participant as a first notification target, and issues a second notification having a lower notification intensity than the first notification to traffic participants other than the specific traffic participant among those belonging to the moving group predicted to collide by the first prediction unit as a second notification target.

[0012] (5) In this case, it is preferable that the notification unit lowers the notification intensity of the second notification as the distance between the specific traffic participant and the second notification target increases.

[0013] (6) In this case, it is preferable that the notification unit issues a first notification to the specific traffic participant as a first notification target, issues a second notification having a lower notification intensity than the first notification to traffic participants other than the specific traffic participant among those belonging to a moving group predicted to collide by the first prediction unit as a second notification target, and issues a third notification having a lower notification intensity than the first notification to traffic participants predicted to be at risk by the third prediction unit as a third notification target. Effect of the Invention

[0014] (1) In a traffic safety support system, a recognition unit recognizes traffic participants in a target traffic area and acquires recognition information of each traffic participant, a prediction unit predicts the future of the traffic participants based on the recognition information, and a notification unit determines a notification target from among a plurality of traffic participants based on a prediction result by the prediction unit and issues a notification. In particular, in the present invention, a classification unit of the prediction unit divides the recognized plurality of traffic participants into a plurality of moving groups and acquires moving group information including a position, a shape, and a moving vector of each moving group, a first prediction unit of the prediction unit predicts whether or not a collision will occur between each moving group based on the moving group information and identifies a collision site in the moving group predicted to collide, and a second prediction unit of the prediction unit determines two or more specific traffic participants from among the plurality of traffic participants based on the collision site when a collision is predicted by the first prediction unit, and predicts whether or not a collision will occur between the specific traffic participants. Therefore, according to the present invention, specific traffic participants to be predicted in more detail from among multiple traffic participants are narrowed down by processing in the first prediction unit, and the presence or absence of a collision between these specific traffic participants can be predicted by processing in the second prediction unit, so that the risk of a collision occurring between some of the many traffic participants present in a target traffic area can be predicted with a low processing load, thereby supporting safe traffic in the target traffic area.

[0015] (2) In the traffic safety support system, the driving subject information acquisition unit acquires status information correlated with the driving ability of the driving subject of the mobile body, and the second prediction unit predicts the presence or absence of a collision between the predicted targets based on the recognition information and status information for the specific traffic participants. That is, in the present invention, for the specific traffic participants narrowed down from multiple traffic participants by the processing in the first prediction unit, the presence or absence of a collision is predicted taking into account each of their status information, thereby making it possible to predict the presence or absence of a collision between the specific traffic participants with a small processing load and high accuracy, and thus supporting safe traffic in the target traffic area.

[0016] (3) In the traffic safety support system, the third prediction unit of the prediction unit predicts a risk to traffic participants present around a specific traffic participant when the specific traffic participant, among two or more specific traffic participants predicted to collide by the second prediction unit, takes a collision avoidance action. Therefore, according to the present invention, the future of a traffic participant can be predicted taking into account a collision avoidance action that may be taken by the specific traffic participant, thereby supporting safe traffic in a target traffic area.

[0017] (4) In the traffic safety support system, the notification unit issues a first notification to the specific traffic participant, and issues a second notification having a notification intensity lower than that of the first notification to traffic participants other than the specific traffic participant among traffic participants belonging to a moving group predicted to collide by the first prediction unit. Thus, according to the present invention, it is possible to cause the specific traffic participants to take appropriate collision avoidance actions via the first notification, while causing the traffic participants other than the specific traffic participants to take actions to avoid a chain reaction risk that may occur due to a collision between the specific traffic participants. Also, according to the present invention, by lowering the notification intensity of the second notification than that of the first notification, it is possible to suppress the annoyance felt by traffic participants other than the specific traffic participants.

[0018] (5) In the traffic safety support system, the notification unit reduces the notification intensity of the second notification as the distance between the specific traffic participant and the second notification target increases. This makes it possible to reduce annoyance felt by traffic participants other than the specific traffic participant.

[0019] (6) In the traffic safety support system, the notification unit issues a first notification to the specific traffic participant, issues a second notification with a notification intensity lower than the first notification to traffic participants other than the specific traffic participant among traffic participants belonging to a moving group predicted to collide by the first prediction unit, and issues a third notification with a notification intensity lower than the first notification to traffic participants predicted to be at risk by the third prediction unit. Thus, according to the present invention, it is possible to cause the specific traffic participants to take appropriate collision avoidance action via the first notification, while causing traffic participants other than the specific traffic participants and traffic participants predicted to be at risk by the third prediction unit to take action to avoid a chain reaction risk that may occur due to a collision between the specific traffic participants. Also, according to the present invention, by lowering the notification intensity of the second notification and the third notification than the first notification, it is possible to suppress the annoyance felt by traffic participants other than the specific traffic participants. [Brief description of the drawings]

[0020] [Figure 1] 1 is a diagram showing a configuration of a traffic safety support system according to an embodiment of the present invention and a part of a target traffic area supported by the traffic safety support system. [Diagram 2] 1 is a block diagram showing a configuration of a collaborative support device and a plurality of area terminals communicably connected to the collaborative support device. [Figure 3A] 1 is a block diagram showing a configuration of a notification device mounted on a four-wheeled automobile; [Figure 3B] 1 is a block diagram showing a configuration of a notification device mounted on a motorcycle. [Figure 3C] 1 is a block diagram showing a configuration of a notification device mounted on a portable information processing terminal carried by a pedestrian; [Figure 4] FIG. 11 is a functional block diagram showing a specific configuration of a prediction unit. [Diagram 5] FIG. 2 is a diagram illustrating an example of a monitoring area. [Figure 6] 4 is a diagram showing an example of a prediction result of a first prediction unit. FIG. [Figure 7]10 is a flowchart showing a specific procedure of a traffic safety support process. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Hereinafter, a traffic safety support system according to an embodiment of the present invention will be described with reference to the drawings.

[0022] FIG. 1 is a diagram showing a schematic configuration of a traffic safety support system 1 according to this embodiment and a part of a target traffic area 9 in which traffic participants who are targets of support by this traffic safety support system 1 exist.

[0023] The traffic safety support system 1 recognizes pedestrians 4, which are people, and moving bodies such as four-wheeled vehicles 2 and motorcycles 3, which are moving bodies within the target traffic area 9, as individual traffic participants, and notifies each traffic participant of support information generated through this recognition, thereby supporting the safe and smooth traffic of each traffic participant in the target traffic area 9 by encouraging communication between each traffic participant moving based on their own will (specifically, for example, mutual recognition between each traffic participant) and recognition of the surrounding traffic environment.

[0024] Fig. 1 illustrates a case where a target traffic area 9 is the vicinity of an intersection 52 in an urban area, which includes a roadway 51, an intersection 52, a sidewalk 53, and a traffic light 54 as traffic infrastructure facilities. Fig. 1 illustrates a case where a total of seven four-wheeled automobiles 2 and a total of two motorcycles 3 are moving on the roadway 51 and the intersection 52, and a total of three pairs of pedestrians 4 are moving on the sidewalk 53 and the intersection 52. Fig. 1 also illustrates a case where a total of three infrastructure cameras 56 are installed.

[0025] The traffic safety support system 1 comprises a group of on-board devices 20 (including on-board devices mounted on the four-wheeled automobiles 2 as well as a portable information processing terminal held or worn by the driver of the four-wheeled automobile 2) that moves with each four-wheeled automobile 2, a group of on-board devices 30 (including on-board devices mounted on the motorcycles 3 as well as a portable information processing terminal held or worn by the driver of the motorcycle 3) that moves with each motorcycle 3, a portable information processing terminal 40 held or worn by each pedestrian 4, a plurality of infrastructure cameras 56 installed in the target traffic area 9, a signal control device 55 that controls traffic lights 54, and a collaboration support device 6 that is communicatively connected to a plurality of terminals (hereinafter simply referred to as "area terminals") present in the target traffic area 9, such as the groups of on-board devices 20, 30, the portable information processing terminal 40, the infrastructure cameras 56, and the signal control device 55.

[0026] The cooperative support device 6 is composed of one or more computers communicatively connected to the above-mentioned multiple area terminals via a base station 57. More specifically, the cooperative support device 6 is composed of a server connected to the multiple area terminals via the base station 57, a network core, and the Internet, an edge server connected to the multiple area terminals via the base station 57 and a MEC (Mulch-access Edge Computing) core, etc.

[0027] FIG. 2 is a block diagram showing the configuration of the collaboration support device 6 and a plurality of area terminals connected to the collaboration support device 6 so as to be able to communicate with each other.

[0028] The group of on-board devices 20 mounted on four-wheeled vehicles 2 in the target traffic area 9 includes, for example, an on-board driving assistance device 21 that assists the driver in driving, a notification device 22 that notifies the driver of various information, a driving subject state sensor 23 that detects the state of the driver while driving, an on-board communication device 24 that wirelessly communicates between the vehicle and the collaborative assistance device 6 or other vehicles in the vicinity of the vehicle, and a portable information processing terminal 25 owned or worn by the driver.

[0029] The in-vehicle driving assistance device 21 includes an external sensor unit, a vehicle state sensor, a navigation device, and a driving assistance ECU. The external sensor unit includes an external camera unit that captures the surroundings of the vehicle, a plurality of in-vehicle external sensors mounted on the vehicle, such as a radar unit and a LIDAR (Light Detection and Ranging (LIDAR)) unit that detect objects outside the vehicle by using electromagnetic waves, and an external recognition device that acquires information about the surrounding state of the vehicle by performing sensor fusion processing on the detection results of the in-vehicle external sensors. The vehicle state sensor is composed of sensors that acquire information about the running state of the vehicle, such as a vehicle speed sensor, an acceleration sensor, a steering angle sensor, a yaw rate sensor, a position sensor, and an orientation sensor. The navigation device includes, for example, a GNSS receiver that identifies the current position of the vehicle based on a signal received from a GNSS (Global Navigation Satellite System) satellite, a storage device that stores map information, and the like.

[0030] The driving assistance ECU executes driving assistance controls such as lane departure suppression control, lane change control, preceding vehicle following control, erroneous start suppression control, collision mitigation brake control, and collision avoidance control based on information acquired by the external sensor unit, the vehicle state sensor, the navigation device, etc. The driving assistance ECU also generates driving assistance information for assisting the driver in safe driving based on information acquired by the external sensor unit, the vehicle state sensor, the navigation device, etc., and transmits the information to the notification device 22.

[0031] Here, the driving assistance ECU starts a collision mitigation brake control that automatically operates the brake device of the vehicle so as to reduce damage caused by contact between the vehicle and the other moving object, on the condition that a moving object that may come into contact with the vehicle exists within a predetermined collision mitigation brake operating range centered on the vehicle. Also, the driving assistance ECU starts a collision avoidance control that automatically operates the steering device of the vehicle so as to avoid contact between the vehicle and the other moving object, on the condition that a moving object that may come into contact with the vehicle exists within a predetermined collision avoidance steering operating range centered on the vehicle. Hereinafter, the collision mitigation brake operating range and the collision avoidance steering operating range are collectively referred to as the "ADAS operating range."

[0032] The driver's subject state sensor 23 is composed of various devices that acquire time-dependent data of information correlated with the driver's driving ability while driving. The driver's subject state sensor 23 is composed of, for example, an in-vehicle camera that detects the direction of the driver's line of sight and whether or not the driver's eyes are open while driving, a seat belt sensor attached to the seat belt worn by the driver to detect the driver's pulse and whether or not the driver is breathing, a steering sensor attached to the steering wheel held by the driver to detect the driver's skin potential, an in-vehicle microphone that detects whether or not the driver is talking to a passenger, etc.

[0033] The in-vehicle communication device 24 has a function of transmitting information acquired by the driving assistance ECU (including information acquired by the external sensor unit, the vehicle status sensor, and the navigation device, etc., and control information related to driving assistance control currently being executed), and information related to the driving subject acquired by the driving subject status sensor 23, to the collaborative assistance device 6, and a function of receiving collaborative assistance information transmitted from the collaborative assistance device 6 and transmitting the received collaborative assistance information to the notification device 22.

[0034] The notification device 22 is composed of various devices that notify the driver of various information through the driver's hearing, vision, touch, etc. by operating a man-machine interface (hereinafter sometimes abbreviated as "HMI (Human Machine Interface)") in a manner determined based on the driving assistance information transmitted from the in-vehicle driving assistance device 21 and the collaborative assistance information transmitted from the collaborative assistance device 6.

[0035] Fig. 3A is a block diagram showing the configuration of the notification device 22 mounted on a four-wheeled vehicle. Note that Fig. 3A shows only the blocks of the notification device 22 that are related to control based on the collaboration support information transmitted from the collaboration support device 6.

[0036] The notification device 22 includes an HMI 220 that operates in a manner that can be recognized by the driver, and an HMI control device 225 that operates the HMI 220 based on the collaboration support information transmitted from the collaboration support device 6.

[0037] The HMI 220 includes an acoustic device 221 that operates in a manner that the driver can hear, a head-up display 222 that operates in a manner that the driver can see, and a seat belt control device 223 and a seat vibration device 224 that operate in a manner that the driver can feel through touch.

[0038] The sound device 221 includes a headrest speaker 221a that is provided on the headrest of the driver's seat where the driver sits and is capable of producing directional binaural sound, and a main speaker 221b that is provided near the driver's seat and the passenger seat. The headrest speaker 221a and the main speaker 221b produce sounds in response to commands from the HMI control device 225. The head-up display 222 displays an image in response to commands from the HMI control device 225 within the field of view of the driver while driving (for example, on the windshield). The seat belt control device 223 changes the tension of the seat belt worn by the driver in response to commands from the HMI control device 225. The seat vibration device 224 vibrates the seat where the driver sits with an amplitude and / or a vibration frequency in response to commands from the HMI control device 225.

[0039] The HMI control device 225 performs risk notification by operating the HMI 220 in a predetermined manner to make the driver aware of the presence of an imminent risk. As will be described later, the collaboration support information transmitted from the collaboration support device 6 to the four-wheeled vehicle 2 includes information on risk notification setting values ​​for turning on / off risk notification by the HMI control device 225 and setting the type of notification mode described later, information on a risk imminent to the driver (hereinafter also referred to as "risk information"), and the like.

[0040] The HMI control device 225 is capable of performing risk notification under a plurality of notification modes in which at least one of the operation target device and operation mode of the HMI 220 is different. More specifically, the HMI control device 225 is capable of performing risk notification under at least one of the following notification modes: a presence notification mode intended to make the driver aware of the existence of a potential risk, an analog notification mode intended to make the driver aware of the existence of an actualized risk and / or the degree of this risk, and a prediction support notification mode intended to notify the driver of useful information to avoid a predicted risk. For this reason, the risk notification setting value input to the HMI control device 225 is set to any one of the following values: "0" for setting the risk notification to off, "1" for setting the risk notification to on under the presence notification mode, "2" for setting the risk notification to on under the analog notification mode, "3" for setting the risk notification to on under the prediction support notification mode, "4" for setting the risk notification to on under the presence notification mode and the prediction support notification mode, and "5" for setting the risk notification to on under the analog notification mode and the prediction support notification mode.

[0041] The HMI control device 225 sets the risk notification to off when the risk notification setting value is "0." That is, the HMI control device 225 does not operate the HMI 220 when the risk notification setting value is "0."

[0042] When the risk notification setting value is "1", the HMI control device 225 sets the notification mode to the presence notification mode and turns on risk notification under the set notification mode.

[0043] If the risk notification setting value is "2", the HMI control device 225 sets the notification mode to the analog notification mode and turns on risk notification under the set notification mode.

[0044] If the risk notification setting value is "3", the HMI control device 225 sets the notification mode to the predictive assistance notification mode and turns on risk notification under the set notification mode.

[0045] When the risk notification setting value is "4", the HMI control device 225 sets the notification mode to the presence notification mode and the prediction assistance notification mode, and turns on risk notification under these set notification modes.

[0046] Furthermore, when the risk notification setting value is "5", the HMI control device 225 sets the notification mode to the analog notification mode and the predictive assistance notification mode, and turns on risk notification under these set notification modes.

[0047] Here, when the notification mode is set to the prediction support notification mode, the HMI control device 225 generates risk avoidance support information useful for the driver to avoid a risk approaching close to the driver based on the risk information transmitted from the collaboration support device 6, and activates the audio device 221 and the head-up display 222 of the HMI 220 in a manner that allows the driver to recognize the risk avoidance support information audibly or visually. Here, the risk avoidance support information includes information on the position of a traffic participant (hereinafter also referred to as a "risk target") that may come into contact with the vehicle, information on a point (hereinafter also referred to as a "risk occurrence point") where the vehicle and the risk target may come into contact, and information that alerts the driver to the risk target.

[0048] More specifically, when a motorcycle driven by an unhealthy rider is present ahead of a four-wheeled vehicle driven by a driver, the HMI control device 225 issues a message such as "Watch out for the dangerous right turn of the motorcycle" as risk avoidance support information for avoiding contact with the motorcycle by using the audio device 221 or displays it on the head-up display 222. In addition, at this time, the HMI control device 225 may display an image of an arrow pointing to the current position or predicted position of the motorcycle on the head-up display 222 as risk avoidance support information for avoiding contact with the motorcycle.

[0049] Furthermore, when the notification mode is set to the presence notification mode, the HMI control device 225 operates the HMI 220 in a manner that does not cause the driver to feel bothered, thereby allowing the driver to naturally recognize the presence of the risk target extracted from the risk information transmitted from the collaboration support device 6. In this manner, in the presence notification mode, in order to naturally cause the driver to recognize the presence of the risk target without causing the driver to feel bothered, it is preferable that the HMI control device 225 operates the headrest speaker 221a, which appeals to the driver's hearing, among the multiple devices included in the HMI 220. More specifically, when the notification mode is set to the presence notification mode, the HMI control device 225 causes the headrest speaker 221a to emit a familiar sound effect at a low volume using directional binaural sound directed toward the position of the risk target or the position of the risk occurrence point, thereby naturally directing the driver's gaze toward the position of the risk target or the risk occurrence point.

[0050] Furthermore, when the notification mode is set to the analog notification mode, the HMI control device 225 operates the HMI 220 in a manner different from the above-mentioned presence notification mode, thereby making the driver strongly aware of the presence of the risk object extracted from the risk information transmitted from the collaboration support device 6 and the degree of risk to the risk object. In this manner, in the analog notification mode, in order to make the driver strongly aware of the presence of the risk object, the HMI control device 225 operates the HMI 220 in a manner with a higher notification intensity than the manner determined in the presence notification mode. Here, the notification intensity refers to the strength that attracts the interest and attention of the driver. More specifically, when the notification mode is set to the analog notification mode, the HMI control device 225 causes the headrest speaker 221a and the main speaker 221b to emit a buzzer sound or a pulse sound at a volume higher than the sound effect emitted in the presence notification mode. These buzzer sounds and pulse sounds are sounds that the driver is not accustomed to hearing and are louder than the sound effect emitted in the presence notification mode, so the notification intensity is higher than the sound effect emitted in the presence notification mode.

[0051] In this embodiment, the HMI control device 225 will be described as activating the sound device 221 when the notification mode is set to the analog notification mode, but the present invention is not limited thereto. When the notification mode is set to the analog notification mode, the HMI control device 225 may activate the seat belt control device 223 to change the tension of the seat belt or activate the seat vibration device 224 to vibrate the seat instead of activating the sound device 221. In this way, the seat belt control device 223 and the seat vibration device 224 are activated in a manner that appeals to the driver's tactile sense, and therefore have a higher notification intensity than the sound effect sounded under the presence notification mode. Furthermore, when the notification mode is set to the analog notification mode, the HMI control device 225 may activate the sound device 221, the seat belt control device 223, and the seat vibration device 224 in combination.

[0052] In the analog notification mode as described above, in order to strongly make the driver aware of the risk level for the risk object in addition to the presence of the risk object, it is preferable that the HMI control device 225 changes the notification intensity according to the risk level for the risk object (for example, the collision prediction time for the risk object) extracted from the risk information transmitted from the collaboration support device 6. Specifically, the HMI control device 225 may increase the volume of the buzzer sound, increase the volume of the pulse sound, or shorten the interval between the pulse sounds to increase the notification intensity as the risk level increases (i.e., as the collision prediction time decreases). When the seat belt control device 223 is operated as described above, the HMI control device 225 may increase the tension of the seat belt and increase the notification intensity as the risk level increases. When the seat vibration device 224 is operated as described above, the HMI control device 225 may increase the amplitude of the seat vibration and increase the notification intensity as the risk level increases.

[0053] In addition, when the HMI control device 225 changes the notification intensity according to the degree of risk in this manner, it is preferable to operate the HMI 220 so that the notification intensity is maximized at the point when the above-mentioned driving assistance ECU starts to execute collision mitigation brake control or collision avoidance steering control, in other words, at the point when the risk object enters the ADAS operating range of the vehicle.

[0054] Returning to FIG. 2, the mobile information processing terminal 25 is, for example, a wearable terminal worn by the driver of the four-wheeled vehicle 2, a smartphone held by the driver, or the like. The wearable terminal has a function of measuring the driver's biological information, such as heart rate, blood pressure, and blood oxygen saturation, and transmitting the measurement data of the biological information to the cooperative support device 6, and a function of receiving cooperative support information transmitted from the cooperative support device 6 and notifying the driver of a message corresponding to the cooperative support information by an image, a voice, a warning sound, a melody, a vibration, or the like. The smartphone also has a function of transmitting information about the driver, such as the driver's position information, movement acceleration, and schedule information, to the cooperative support device 6, and a function of receiving cooperative support information transmitted from the cooperative support device 6, and notifying the driver of a message corresponding to the cooperative support information by an image, a voice, a warning sound, a melody, a vibration, or the like.

[0055] The group of on-board devices 30 mounted on motorcycles 3 in the target traffic area 9 includes, for example, an on-board driving assistance device 31 that assists the rider in driving, a notification device 32 that notifies the rider of various information, a rider status sensor 33 that detects the status of the rider while driving, an on-board communication device 34 that wirelessly communicates between the vehicle and the collaboration assistance device 6 or other vehicles in the vicinity of the vehicle, and a portable information processing terminal 35 owned or worn by the rider.

[0056] The in-vehicle driving assistance device 31 includes an external sensor unit, a vehicle state sensor, a navigation device, and a driving assistance ECU. The external sensor unit includes an external camera unit that captures the surroundings of the vehicle, a plurality of in-vehicle external sensors mounted on the vehicle, such as a radar unit or a lidar unit that detects objects outside the vehicle by using electromagnetic waves, and an external recognition device that acquires information about the surroundings of the vehicle by performing sensor fusion processing on the detection results of the in-vehicle external sensors. The vehicle state sensor is composed of sensors that acquire information about the running state of the vehicle, such as a vehicle speed sensor and a 5-axis or 6-axis inertial measurement unit. The navigation device includes, for example, a GNSS receiver that identifies the current position based on a signal received from a GNSS satellite, a storage device that stores map information, and the like.

[0057] The driving assistance ECU executes driving assistance controls such as lane keeping control, lane departure suppression control, lane change control, preceding vehicle following control, false start suppression control, and collision mitigation brake control based on information acquired by the external sensor unit, the vehicle state sensor, the navigation device, etc. The driving assistance ECU also generates driving assistance information for assisting the rider in safe driving based on information acquired by the external sensor unit, the vehicle state sensor, the navigation device, etc., and transmits the information to the notification device 32.

[0058] Here, the driving assistance ECU initiates collision mitigation brake control to automatically operate the vehicle's braking device to reduce damage caused by contact between the vehicle and the other moving object, provided that there is a moving object that may come into contact with the vehicle within a specified collision mitigation brake operation range (hereinafter referred to as the "ADAS operation range" together with the term defined for four-wheeled vehicle 2) centered on the vehicle.

[0059] The rider condition sensor 33 is composed of various devices that acquire information correlated with the driving ability of the rider while driving. The rider condition sensor 33 is composed of, for example, a seat sensor that is provided on the seat on which the rider sits and detects the rider's pulse, the presence or absence of breathing, and the like, and a helmet sensor that is provided on the helmet worn by the rider and detects the rider's pulse, the presence or absence of breathing, skin potential, and the like.

[0060] The in-vehicle communication device 34 has a function of transmitting information acquired by the driving assistance ECU (including information acquired by the external sensor unit, the vehicle status sensor, and the navigation device, etc., and control information related to driving assistance control currently being executed), and information related to the rider acquired by the rider status sensor 33, to the collaborative assistance device 6, and a function of receiving collaborative assistance information transmitted from the collaborative assistance device 6 and transmitting the received collaborative assistance information to the notification device 32.

[0061] The notification device 32 is composed of various devices that notify the rider of various information through the rider's hearing, vision, touch, etc. by operating the HMI in a predetermined manner based on the driving assistance information transmitted from the in-vehicle driving assistance device 21 and the collaborative assistance information transmitted from the collaborative assistance device 6.

[0062] Fig. 3B is a block diagram showing the configuration of the notification device 32 mounted on the motorcycle. Note that Fig. 3B shows only the blocks of the notification device 32 that are related to control based on the collaboration support information transmitted from the collaboration support device 6.

[0063] The notification device 32 includes an HMI 320 that operates in a manner that can be recognized by the rider, and an HMI control device 325 that operates the HMI 320 based on the collaboration support information transmitted from the collaboration support device 6.

[0064] The HMI 320 includes a head-mounted speaker 321 that operates in a manner that the rider can hear and perceive, and a head-up display 322 that operates in a manner that the rider can see.

[0065] The head-mounted speaker 321 is provided in a helmet worn by the rider and is capable of emitting directional binaural sound. The head-mounted speaker 321 emits sound in response to commands from the HMI control device 325. The head-up display 322 displays an image in response to commands from the HMI control device 325 within the field of view of the rider while driving (for example, on the helmet shield).

[0066] The HMI control device 325 performs risk notification by operating the HMI 320 in a defined manner to make the rider aware of the presence of a nearby risk. As will be described later, the cooperative support information transmitted from the cooperative support device 6 to the motorcycle 3 includes information on a risk notification setting value for setting on / off of risk notification by the HMI control device 325 and the type of notification mode, risk information on a risk approaching the rider, and the like.

[0067] The HMI control device 325 is capable of performing risk notification under a plurality of notification modes in which at least one of the operation target device and operation mode of the HMI 320 is different. More specifically, the HMI control device 325 is capable of performing risk notification under at least one of the following notification modes: a presence notification mode intended to make the rider aware of the presence of a potential risk, an analog notification mode intended to make the rider aware of the presence of an actualized risk and / or the degree of this risk, and a prediction support notification mode intended to notify the rider of useful information for avoiding a predicted risk. For this reason, the risk notification setting value input to the HMI control device 325 is set to any one of the following values: "0" for setting the risk notification off, "1" for setting the risk notification on under the presence notification mode, "2" for setting the risk notification on under the analog notification mode, "3" for setting the risk notification on under the prediction support notification mode, "4" for setting the risk notification on under the presence notification mode and the prediction support notification mode, and "5" for setting the risk notification on under the analog notification mode and the prediction support notification mode.

[0068] The HMI control device 325 sets the risk notification to off when the risk notification setting value is "0." That is, the HMI control device 325 does not operate the HMI 320 when the risk notification setting value is "0."

[0069] When the risk notification setting value is "1", the HMI control device 325 sets the notification mode to the presence notification mode and turns on risk notification under the set notification mode.

[0070] If the risk notification setting value is "2", the HMI control device 325 sets the notification mode to the analog notification mode and turns on risk notification under the set notification mode.

[0071] If the risk notification setting value is "3", the HMI control device 325 sets the notification mode to the predictive assistance notification mode and turns on risk notification under the set notification mode.

[0072] When the risk notification setting value is "4", the HMI control device 325 sets the notification mode to the presence notification mode and the prediction assistance notification mode, and turns on risk notification under these set notification modes.

[0073] Furthermore, when the risk notification setting value is "5", the HMI control device 325 sets the notification mode to the analog notification mode and the predictive assistance notification mode, and turns on risk notification under these set notification modes.

[0074] Here, when the notification mode is set to the predictive support notification mode, the HMI control device 325 generates risk avoidance support information that is useful for the rider to avoid an approaching risk based on the risk information transmitted from the collaboration support device 6, and activates the head-mounted speaker 321 and head-up display 322 of the HMI 320 in a manner that allows the rider to perceive this risk avoidance support information audibly and visually. Here, the risk avoidance support information includes information on the position of a risk object that may come into contact with the vehicle, information on the point where the risk occurs, and information that alerts the rider to the risk object.

[0075] More specifically, when there is a four-wheeled vehicle driven by an unhealthy driver ahead of the motorcycle driven by the rider, the HMI control device 325 issues a message such as "Watch out for the dangerous right turn of the four-wheeled vehicle" as risk avoidance support information for avoiding contact with the four-wheeled vehicle through the head-mounted speaker 321 or displays it on the head-up display 322. In addition, at this time, the HMI control device 325 may display an image of an arrow pointing to the current position or predicted position of the four-wheeled vehicle on the head-up display 322 as risk avoidance support information for avoiding contact with the four-wheeled vehicle.

[0076] Furthermore, when the notification mode is set to the presence notification mode, the HMI control device 325 operates the HMI 320 in a manner that does not cause the rider to feel bothered, thereby allowing the rider to naturally recognize the presence of the risk target extracted from the risk information transmitted from the collaboration support device 6. In this manner, in the presence notification mode, in order to naturally recognize the presence of the risk target without causing the rider to feel bothered, it is preferable that the HMI control device 325 operates the head-mounted speaker 321, which particularly appeals to the rider's hearing, among the multiple devices included in the HMI 320. More specifically, when the notification mode is set to the presence notification mode, the HMI control device 325 causes the head-mounted speaker 321 to emit a familiar sound effect at a low volume using directional binaural sound directed toward the position of the risk target or the position of the risk occurrence point, thereby naturally directing the rider's gaze toward the position of the risk target or the risk occurrence point.

[0077] Furthermore, when the notification mode is set to the analog notification mode, the HMI control device 325 operates the HMI 320 in a manner different from the above-mentioned presence notification mode, thereby making the rider strongly aware of the presence of a risk object extracted from the risk information transmitted from the collaboration support device 6 and the degree of risk to the risk object. In this manner, in the analog notification mode, in order to make the rider strongly aware of the presence of a risk object, the HMI control device 325 operates the HMI 320 in a manner with a higher notification intensity than the manner determined in the presence notification mode. More specifically, when the notification mode is set to the analog notification mode, the HMI control device 325 causes the head-mounted speaker 321 to emit a buzzer sound or a pulse sound with a volume higher than the sound effect emitted in the presence notification mode. These buzzer sounds and pulse sounds are sounds that are unfamiliar to the rider's ears and are louder than the sound effect emitted in the presence notification mode, so the notification intensity is higher than the sound effect emitted in the presence notification mode.

[0078] As described above, in the analog notification mode, in order to make the rider more aware of the presence of a risk object as well as the degree of risk associated with this risk object, it is preferable that the HMI control device 325 changes the notification intensity according to the degree of risk associated with the risk object (e.g., the predicted collision time for the risk object) extracted from the risk information transmitted from the collaboration support device 6. Specifically, the HMI control device 325 may increase the volume of the buzzer sound, increase the volume of the pulse sound, or shorten the interval between the pulse sounds, thereby increasing the notification intensity, as the risk degree increases (i.e., as the predicted collision time decreases).

[0079] In addition, when the HMI control device 325 changes the notification intensity according to the degree of risk in this manner, it is preferable to operate the HMI 320 so that the notification intensity is maximized at the point when the above-mentioned driving assistance ECU begins to execute the collision mitigation brake control, in other words, at the point when the risk object enters the ADAS operating range of the vehicle.

[0080] Returning to FIG. 2 , the mobile information processing terminal 40 owned or worn by the pedestrian 4 in the target traffic area 9 is composed of, for example, a wearable terminal worn by the pedestrian 4 or a smartphone owned by the pedestrian 4. The wearable terminal has a function of measuring biological information of the pedestrian 4, such as heart rate, blood pressure, and blood oxygen saturation, transmitting the measurement data of this biological information to the collaboration support device 6, and receiving collaboration support information transmitted from the collaboration support device 6. In addition, the smartphone has a function of transmitting pedestrian information related to the pedestrian 4, such as position information, movement acceleration, and schedule information of the pedestrian 4, to the collaboration support device 6, and receiving collaboration support information transmitted from the collaboration support device 6.

[0081] The mobile information processing terminal 40 also includes a notification device 42 that notifies pedestrians of various information through their hearing, vision, touch, etc. by operating the HMI in a manner determined based on the received collaborative support information.

[0082] Fig. 3C is a block diagram showing the configuration of the notification device 42 mounted on the mobile information processing terminal 40. Note that Fig. 3C illustrates only the blocks of the notification device 42 that are particularly related to control based on the collaboration support information transmitted from the collaboration support device 6.

[0083] The notification device 42 includes an HMI 420 that operates in a manner that can be recognized by a pedestrian, and an HMI control device 425 that operates the HMI 420 based on the collaboration support information transmitted from the collaboration support device 6.

[0084] The HMI 420 includes a speaker 421 that operates in a manner that is audible to pedestrians, and a vibration device 424 that operates in a manner that is tactile to pedestrians.

[0085] The speaker 421 produces a sound in response to a command from the HMI control device 425. The vibration device 424 vibrates the main body of the portable information processing terminal 40 with an amplitude and / or a frequency in a manner in response to a command from the HMI control device 425.

[0086] As will be explained later, the collaborative support information transmitted from the collaborative support device 6 to the portable information processing terminal 40 carried by the pedestrian includes information regarding risk notification setting values ​​for turning risk notification on / off by the HMI control device 425 and setting the type of notification mode, as well as risk information regarding risks approaching the pedestrian.

[0087] The HMI control device 425 is capable of performing risk notification under a plurality of notification modes that differ in at least one of the operation target device and operation mode of the HMI 420. More specifically, the HMI control device 425 is capable of performing risk notification under at least one of the following notification modes: a presence notification mode intended to make pedestrians aware of the presence of a potential risk, and an analog notification mode intended to make pedestrians aware of the presence of an actual risk and / or the degree of this risk. For this reason, the risk notification setting value input to the HMI control device 425 is set to any one of the following values: "0" that sets the risk notification by the HMI control device 425 to off, "1" that sets the risk notification by the HMI control device 425 to on and sets the notification mode to the presence notification mode, and "2" that sets the risk notification by the HMI control device 425 to on and sets the notification mode to the analog notification mode.

[0088] The HMI control device 425 sets the risk notification to off when the risk notification setting value is "0." That is, the HMI control device 425 does not operate the HMI 420 when the risk notification setting value is "0."

[0089] When the risk notification setting value is "1", the HMI control device 425 sets the notification mode to the presence notification mode and turns on risk notification under the set notification mode.

[0090] Furthermore, when the risk notification setting value is "2", the HMI control device 425 sets the notification mode to the analog notification mode and turns on risk notification under the set notification mode.

[0091] Here, when the notification mode is set to the presence notification mode, the HMI control device 425 operates the HMI 420 in a manner that does not annoy the pedestrian, thereby allowing the pedestrian to naturally recognize the presence of a risk target extracted from the risk information transmitted from the collaboration support device 6. More specifically, when the notification mode is set to the presence notification mode, the HMI control device 425 operates the vibration device 424 to vibrate the main body of the portable information processing terminal 40 at a predetermined amplitude and frequency.

[0092] Furthermore, when the notification mode is set to the analog notification mode, the HMI control device 425 operates the HMI 420 in a manner different from the above-mentioned presence notification mode, thereby making the pedestrian more aware of the presence of a risk condition extracted from the risk information transmitted from the collaboration support device 6 and the degree of risk to this risk object. In this manner, in the analog notification mode, in order to make the pedestrian more aware of the presence of a risk object, the HMI control device 425 operates the HMI 420 in a manner with a higher notification intensity than the manner determined in the presence notification mode. More specifically, when the notification mode is set to the analog notification mode, the HMI control device 425 makes the speaker 421 emit a buzzer sound, a pulse sound, a message indicating the presence of a risk, or the like.

[0093] As described above, in the analog notification mode, in order to make the pedestrian more aware of the presence of a risk object as well as the degree of risk to this risk object, it is preferable that the HMI control device 425 changes the notification intensity according to the degree of risk to the risk object (e.g., the predicted collision time to the risk object) extracted from the risk information transmitted from the collaboration support device 6. Specifically, the HMI control device 425 may increase the volume of the buzzer sound, increase the volume of the pulse sound, shorten the interval between the pulse sounds, increase the volume of the message, or change the content of the message as the risk degree increases (i.e., the predicted collision time decreases), thereby increasing the notification intensity.

[0094] Returning to Figure 2, the infrastructure camera 56 captures images of traffic infrastructure facilities including roads, intersections, and sidewalks in the target traffic area, as well as moving objects and pedestrians moving on these roads, intersections, sidewalks, etc., and transmits the obtained image information to the collaborative support device 6.

[0095] The signal control device 55 controls traffic lights and transmits to the collaboration support device 6 traffic light status information regarding the current lighting color of traffic lights installed in the target traffic area and the timing for changing the lighting color.

[0096] The collaboration support device 6 is a computer that supports safe and smooth traffic of traffic participants in the target traffic area by generating collaboration support information for each traffic participant to be supported, based on information acquired from multiple area terminals present in the target traffic area as described above, for encouraging communication between traffic participants and awareness of the surrounding traffic environment, and notifying each traffic participant of the information. Note that in this embodiment, the collaboration support device 6 supports traffic participants among the multiple traffic participants present in the target traffic area who are equipped with a means (e.g., the in-vehicle device group 20, 30, the mobile information processing terminal 40, the notification device 22, 32, 42) that receives the collaboration support information generated by the collaboration support device 6 and operates an HMI in a mode determined based on the received collaboration support information.

[0097] The collaborative assistance device 6 includes a target traffic area recognition unit 60 that recognizes people and moving objects in a target traffic area as individual traffic participants, a driving subject information acquisition unit 61 that acquires driving subject state information correlated with the driving ability of the driving subject of the moving object recognized as a traffic participant by the target traffic area recognition unit 60, a prediction unit 62 that predicts the future of multiple traffic participants in the target traffic area, a collaborative assistance information notification unit 65 that transmits collaborative assistance information generated for each individual traffic participant recognized as an assistance target by the target traffic area recognition unit 60, a traffic environment database 67 that accumulates information about the traffic environment in the target traffic area, and a driving history database 68 that accumulates information about the past driving history of pre-registered driving subjects.

[0098] The traffic environment database 67 stores information related to the traffic environment of traffic participants in a target traffic area, such as map information of the target traffic area registered in advance (e.g., road width, number of lanes, speed limit, sidewalk width, presence or absence of guardrails between the roadway and sidewalk, and location of crosswalks) and risk area information related to particularly high-risk areas within the target traffic area. Hereinafter, the information stored in the traffic environment database 67 is also referred to as registered traffic environment information.

[0099] The driving history database 68 stores information on the past driving history of a previously registered driver in association with the registration number of a mobile object owned by the driver. Therefore, if the registration number of a recognized mobile object can be identified by the target traffic area recognition unit 60 described later, the driving history database 68 can be searched based on the registration number to obtain the past driving history of the driver of the recognized mobile object. Hereinafter, the information stored in the driving history database 68 is also referred to as registered driving history information.

[0100] The target traffic area recognition unit 60 recognizes recognition objects including each traffic participant, which is a person or a moving object, in the target traffic area and the traffic environment of each traffic participant in the target traffic area, based on information transmitted from the above-mentioned area terminals (the vehicle-mounted device group 20, 30, the mobile information processing terminal 40, the infrastructure camera 56, and the signal control device 55) in the target traffic area and registered traffic environment information read from the traffic environment database 67, and obtains recognition information regarding these recognition objects.

[0101] Here, the information transmitted from the on-board driving support device 21 and the on-board communication device 24 included in the on-board device group 20 to the target traffic area recognition unit 60, and the information transmitted from the on-board driving support device 31 and the on-board communication device 34 included in the on-board device group 30 to the target traffic area recognition unit 60 include information on the state of traffic participants and traffic environment around the vehicle acquired by the external sensor unit, and information on the state of the vehicle as a traffic participant acquired by the vehicle state sensor, navigation device, etc. The information transmitted from the mobile information processing terminal 40 to the target traffic area recognition unit 60 includes information on the state of pedestrians as a traffic participant, such as position and movement acceleration. The image information transmitted from the infrastructure camera 56 to the target traffic area recognition unit 60 includes information on each traffic participant and its traffic environment, such as the appearance of traffic infrastructure facilities such as roadways, intersections, and sidewalks in the target traffic area, and the appearance of traffic participants moving in the target traffic area. The traffic light status information transmitted from the signal control device 55 to the target traffic area recognition unit 60 includes information on the traffic environment of each traffic participant, such as the current lighting color of the traffic light and the timing of changing the lighting color. In addition, the registered traffic environment information that the target traffic area recognition unit 60 reads from the traffic environment database 67 includes information on the traffic environment of each traffic participant, such as map information of the target traffic area and risk area information.

[0102] Therefore, based on the information transmitted from these area terminals, the target traffic area recognition unit 60 can obtain the recognition information of each traffic participant (hereinafter also referred to as "traffic participant recognition information"), such as the position in the target traffic area of ​​each traffic participant in the target traffic area, the movement vector (i.e., a vector extending along the movement direction and having a length proportional to the movement speed), the movement acceleration, the vehicle type of the moving body, the vehicle class of the moving body, the registration number of the moving body, the number of pedestrians, the age group of the pedestrians, etc. Based on the information transmitted from these area terminals, the target traffic area recognition unit 60 can also obtain the recognition information of the traffic environment of each traffic participant in the target traffic area (hereinafter also referred to as "traffic environment recognition information"), such as the width of the roadway, the number of lanes, the speed limit, the width of the sidewalk, the presence or absence of a guardrail between the roadway and the sidewalk, the lighting color of the traffic light and its switching timing, and risk area information, etc.

[0103] The target traffic area recognition unit 60 transmits the traffic participant recognition information and traffic environment recognition information acquired as described above to the driving subject information acquisition unit 61, the prediction unit 62, the collaboration support information notification unit 65, and the like.

[0104] The driving subject information acquisition unit 61 acquires driving subject state information and driving subject characteristic information that are correlated with the current driving ability of the driving subject of the mobile body recognized as a traffic participant by the target traffic area recognition unit 60 based on information transmitted from the above-mentioned area terminals (particularly, the vehicle-mounted device groups 20, 30) in the target traffic area and registered driving history information read from the driving history database 68.

[0105] More specifically, when the driver of a four-wheeled vehicle recognized as a traffic participant by the target traffic area recognition unit 60 is a human, the driver subject information acquisition unit 61 acquires information transmitted from the on-board device group 20 mounted on the four-wheeled vehicle as driver subject state information of the driver. Also, when the driver of a motorcycle recognized as a traffic participant by the target traffic area recognition unit 60 is a human, the driver subject information acquisition unit 61 acquires information transmitted from the on-board device group 30 mounted on the motorcycle as driver subject state information of the rider.

[0106] Here, the information transmitted from the driver's state sensor 23 and the vehicle-mounted communication device 24 included in the vehicle-mounted device group 20 to the driver's information acquisition unit 61 includes time-based data on the driver's appearance such as the direction of the driver's gaze and whether or not the driver's eyes are open while driving, biological information such as pulse, whether or not breathing, and skin potential, and voice information such as whether or not the driver is talking, and includes information that is correlated with the driver's driving ability while driving. The information transmitted from the rider's state sensor 33 and the vehicle-mounted communication device 34 included in the vehicle-mounted device group 30 to the driver's information acquisition unit 61 includes time-based data on the rider's biological information such as pulse, whether or not breathing, and skin potential, and includes information that is correlated with the driver's driving ability while driving. The information transmitted from the mobile information processing terminals 25 and 35 included in the vehicle-mounted device groups 20 and 30 to the driver's information acquisition unit 61 includes the driver's and rider's personal schedule information. For example, when the driver or rider is driving a moving object under a tight schedule, the driver or rider may become impatient and his or her driving ability may decrease. For this reason, the driver's and rider's personal schedule information can be said to be information that is correlated with his or her own driving ability.

[0107] The driving subject information acquisition unit 61 acquires driving subject characteristic information regarding the driving subject's characteristics (e.g., excessive sudden lane changes, excessive sudden acceleration / deceleration, etc.) that are correlated with the driving subject's current driving ability while driving, by using both or either of the driving subject state information for the driving subject acquired by the above procedure and the registered driving history information read from the driving history database 68.

[0108] The driver subject information acquisition unit 61 transmits the driver subject state information and driver subject characteristic information of the driver acquired as described above to the prediction unit 62, the cooperation support information notification unit 65, and the like.

[0109] The prediction unit 62 extracts a portion of the target traffic area as a monitoring area, and predicts the future risks of multiple traffic participants in this monitoring area based on the traffic participant recognition information and traffic environment recognition information acquired by the target traffic area recognition unit 60, and the driving subject state information and driving subject characteristic information acquired by the driving subject information acquisition unit 61.

[0110] Here, the target traffic area is a relatively wide traffic area determined by, for example, a city, town, or village. In contrast, the monitoring area is a traffic area that a four-wheeled vehicle can pass through in about several tens of seconds when traveling at the legal speed, such as an intersection or near a specific facility. In other words, the monitoring area is narrower than the target traffic area, but wider than the ADAS operation range of the driving assistance ECU installed in each moving object.

[0111] FIG. 4 is a functional block diagram showing a specific configuration of the prediction unit 62. As shown in FIG. The prediction unit 62 includes a group classification section 621, a first prediction section 622, a second prediction section 623, and a third prediction section 624, and uses these to predict the future of a plurality of prediction targets in the monitoring area.

[0112] The group classification unit 621 classifies a plurality of traffic participants existing in a monitoring area into a plurality of moving groups based on the traffic participant recognition information and the traffic environment recognition information, and acquires moving group information for each moving group. Here, a specific procedure for classifying a plurality of traffic participants into a plurality of moving groups in the group classification unit 621 will be described with reference to FIG. 5.

[0113] Fig. 5 is a diagram showing an example of a monitoring area 90. The monitoring area 90 shown in Fig. 5 includes a two-lane road 91, a three-lane road 92 which is the opposite lane of the road 91, a median strip 93 provided between the roads 91 and 92, and a side road 94 which has two lanes on each side and connects to the road 92. Fig. 5 shows a case in which a total of four four-wheeled automobiles 95a-95d are traveling on the road 91, a total of fourteen four-wheeled automobiles 96a-96n and a total of two motorcycles 97a-97b are traveling on the road 92, and a total of two four-wheeled automobiles 98a-98b are traveling on the side road 94. In the following description, a traffic area where so-called left-hand traffic is required (i.e., a traffic area where vehicles must travel on the left side of the center of the road) is used as an example, but the present invention is not limited thereto. That is, the present invention is also applicable to traffic areas where traffic is required to keep to the right (that is, traffic areas where vehicles must keep to the right of the center of the road).

[0114] The group classification unit 621 acquires traffic participant recognition information of the four-wheeled vehicles 95a-95d, 96a-96n, 98a-98b and the motorcycles 97a-97b that are recognized as traffic participants existing in the monitoring area 90 by the target traffic area recognition unit 60, and traffic environment recognition information of the monitoring area 90, and divides the multiple traffic participants into movement groups G1, G2, G3, G4, G5, G6, G7, G8, and G9 whose number is less than the total number of the traffic participants (22 in the example of FIG. 5) based on the recognition information. Here, each movement group is composed of one or more traffic participants that move in a single mass. Therefore, the group classification unit 621 classifies one or more traffic participants that exist within a predetermined range and have approximately the same movement vector into one movement group.

[0115] Therefore, in the example shown in Figure 5, the 22 traffic participants present within the monitoring area 90 are divided into nine mobile groups G1 to G9: mobile group G1 consisting of two four-wheeled vehicles 95a to 95b, mobile group G2 consisting of two four-wheeled vehicles 95c to 95d, mobile group G3 consisting of one four-wheeled vehicle 96a and two motorcycles 97a to 97b, mobile group G4 consisting of three four-wheeled vehicles 96b to 96d, mobile group G5 consisting of three four-wheeled vehicles 96e to 96g, mobile group G6 consisting of three four-wheeled vehicles 96h to 96j, mobile group G7 consisting of three four-wheeled vehicles 96l to 96n, mobile group G8 consisting of one four-wheeled vehicle 96k, and mobile group G9 consisting of two four-wheeled vehicles 98a to 98b.

[0116] After dividing the traffic participants into multiple moving groups by the above procedure, the group classification unit 621 acquires moving group information for each moving group. Here, the moving group information includes the position of the moving group, the shape of the moving group (i.e., the distribution shape of the multiple traffic participants that make up the moving group), and the moving vector of the moving group.

[0117] Returning to Fig. 4, the first prediction unit 622 predicts whether or not a collision will occur between the moving groups by estimating the position of each moving group in the future after a predetermined time based on the traffic environment recognition information of the monitoring area 90 and the moving group information acquired by the group classification unit 621, and identifies a collision site in the moving groups predicted to collide. Here, the procedure of the first prediction unit 622 to determine whether or not a collision will occur between the moving groups and identify the collision site will be described with reference to Fig. 6.

[0118] Fig. 6 is a diagram showing an example of a prediction result of the first prediction unit 622. More specifically, Fig. 6 is a diagram showing the position of each moving group in the future after a predetermined time, which is estimated by the first prediction unit 622 based on the traffic environment recognition information and the moving group information.

[0119] In the example shown in Fig. 6, the first prediction unit 622 predicts that a collision will occur between the moving groups G6 and G8, and between the moving groups G7 and G9, after a predetermined time from the state shown in Fig. 5. More specifically, the first prediction unit 622 predicts that the moving group G8, which moves at a speed faster than the moving group G6 at the time shown in Fig. 5, will collide with the moving group G6 in front of it, and that the moving group G9, which moves without slowing down near the intersection, will collide with the moving group G7 entering the intersection. The first prediction unit 622 also uses the above prediction results to identify collision sites in the moving groups G6, G7, G8, and G9 predicted to collide. In the example shown in Figure 6, the first prediction unit 622 identifies the rear end of moving group G6 (i.e., the portion where four-wheeled vehicle 96j is located), the front end of moving group G8 (i.e., the portion where four-wheeled vehicle 96k is located), the front end of moving group G7 (i.e., the portion where four-wheeled vehicle 96l is located), and the front end of moving group G9 (i.e., the portion where four-wheeled vehicle 98a is located) as the collision sites.

[0120] Returning to Figure 4, when the first prediction unit 622 predicts that at least one moving group will collide, the second prediction unit 623 determines two or more specific traffic participants from among the multiple traffic participants present in the monitoring area based on the collision location identified by the first prediction unit 622, and predicts whether or not a collision will occur between these specific traffic participants.

[0121] More specifically, the second prediction unit 623 determines, as the specific traffic participants, the traffic participants that are located closest to the collision site from among the traffic participants that constitute the moving groups predicted to collide by the first prediction unit 622. Therefore, in the example shown in Figures 5 and 6, the second prediction unit 623 determines, as the specific traffic participants, a four-wheeled vehicle 96j in the moving group G6, a four-wheeled vehicle 96k in the moving group G8, a four-wheeled vehicle 96l in the moving group G7, and a four-wheeled vehicle 98a in the moving group G9.

[0122] Next, the second prediction unit 623 obtains the traffic environment recognition information of the monitoring area, and the traffic participant recognition information, driving subject state information, and driving subject characteristic information for the determined specific traffic participant, and predicts whether or not there will be a future collision between the specific traffic participants based on this information. That is, the second prediction unit 623 can take into account the surrounding recognition state of the driver of each specific traffic participant by using the driving subject information and driving subject characteristic information not used by the first prediction unit 622, so that it is possible to predict whether or not there will be a future collision between the specific traffic participants with higher accuracy than the first prediction unit 622. Therefore, in the example shown in Figures 5 and 6, the second prediction unit 623 predicts whether or not there will be a future collision between the four-wheeled vehicle 96j and the four-wheeled vehicle 96k, and whether or not there will be a future collision between the four-wheeled vehicle 96l and the four-wheeled vehicle 98a based on the traffic environment recognition information, the traffic participant recognition information, the driving subject state information, and the driving subject characteristic information.

[0123] When the second prediction unit 623 predicts that a collision will occur between at least one pair of specific traffic participants, the third prediction unit 624 predicts whether or not there is a risk to traffic participants present around the specific traffic participants due to a collision avoidance action to avoid the predicted collision in at least one of the two or more specific traffic participants. Here, the collision avoidance action includes avoidance actions mainly performed by the driver (e.g., sudden braking and sudden steering), as well as collision mitigation braking and collision avoidance steering mainly performed by the driving assistance ECU. Therefore, in the example shown in FIG. 5 and FIG. 6, when the third prediction unit 624 predicts that, for example, the four-wheeled vehicle 96k may suddenly steer to the right to avoid a collision with the four-wheeled vehicle 96j, it predicts that a rear-end collision risk will occur for the four-wheeled vehicle 96g. Furthermore, when the third prediction unit 624 predicts that, for example, the four-wheeled vehicle 98a may activate a collision mitigation brake to avoid a collision with the four-wheeled vehicle 96l, it predicts that a rear-end collision risk will occur for the four-wheeled vehicle 98b traveling behind the four-wheeled vehicle 98a.

[0124] The collaborative assistance information notification unit 65 determines notification targets from among the multiple traffic participants recognized as assistance targets by the target traffic area recognition unit 60 based on the recognition information acquired by the target traffic area recognition unit 60, the driving subject information acquired by the driving subject information acquisition unit 61, and the prediction results for the monitoring area by the prediction unit 62, and issues notifications to these notification targets.

[0125] As described above, the support target has means (e.g., the in-vehicle device group 20, 30, the portable information processing terminal 40, the notification device 22, 32, 42) for operating the HMI in a manner determined based on the collaboration support information transmitted from the collaboration support device 6. Therefore, the collaboration support information notification unit 65 transmits the collaboration support information generated for each notification target to each notification target and performs notification by activating each HMI.

[0126] First, the collaboration support information notification unit 65 determines a plurality of notification targets from among a plurality of traffic participants present in the monitoring area based on the prediction result for the monitoring area by the prediction unit 62. More specifically, the collaboration support information notification unit 65 determines a specific traffic participant predicted to collide by the second prediction unit 623 as a first notification target, determines a traffic participant other than the first notification target among traffic participants belonging to a moving group predicted to collide by the first prediction unit 622 as a second notification target, and determines a traffic participant other than the first and second notification targets among traffic participants predicted to have some risk by the third prediction unit 624 as a third notification target. That is, in the example shown in Fig. 5 and Fig. 6, the collaboration support information notification unit 65 determines four-wheeled vehicles 96j, 96k, 96l, and 98a as the first notification targets, four-wheeled vehicles 96h, 96i, 96m, 96n, and 98b as the second notification targets, and a four-wheeled vehicle 96g as the third notification target.

[0127] Next, the collaboration support information notification unit 65 sets the risk notification setting value to "2" or "5" for the first notification target to start risk notification in the analog notification mode. Also, the collaboration support information notification unit 65 sets the risk notification setting value to "1" or "4" for the second and third notification targets to start risk notification in the presence notification mode, which has a lower notification intensity than the analog notification mode.

[0128] In addition, after setting the risk notification setting value for each notification target using the above procedure, the collaborative support information notification unit 65 transmits collaborative support information to each notification target, which includes information regarding the risk notification setting value and risk information regarding risks that are approaching each notification target.

[0129] In this embodiment, the collaboration support information notifying unit 65 sets the risk notification setting value so that risk notification is performed in the presence notification mode for the second and third notification targets, but the present invention is not limited to this. More specifically, the notification intensity of the notification performed for the second and third notification targets may be changed according to the distance between the second and third notification targets and the first notification target. In other words, the notification intensity may be lowered as the distance between the second and third notification targets and the first notification target increases.

[0130] Fig. 7 is a flowchart showing a specific procedure of a traffic safety support process for supporting safe traffic in a target traffic area of ​​multiple traffic participants by the collaboration support device 6. Each step shown in the flowchart of Fig. 7 is realized by the collaboration support device 6 executing a computer program stored in a storage medium (not shown).

[0131] First, in step ST1, the collaboration support device 6 determines a monitoring area from the target traffic area, and proceeds to step ST2. In step ST2, the collaboration support device 6 recognizes traffic participants present in the monitoring area, and further obtains traffic participant recognition information including the position and movement vector of each traffic participant, and proceeds to step ST3. Next, in step ST3, the collaboration support device 6 obtains driving subject state information and driving subject characteristic information of the multiple traffic participants recognized in step ST2, and proceeds to step ST4.

[0132] Next, in step ST4, the collaboration support device 6 divides the multiple traffic participants present in the monitoring area into multiple moving groups based on the traffic participant recognition information acquired in step ST2, acquires moving group information for each moving group, and proceeds to step ST5. In step ST5, the collaboration support device 6 predicts the presence or absence of a future collision between each moving group based on the moving group information, identifies a collision site in each moving group, and proceeds to step ST6.

[0133] In step ST6, if a collision is predicted between the moving groups in step ST5, the collaboration support device 6 determines two or more specific traffic participants based on the collision location. Also in step ST6, the collaboration support device 6 predicts whether or not there will be a collision between the specific traffic participants based on the traffic participant recognition information, the driver subject state information, and the driver subject characteristic information, and proceeds to step ST7.

[0134] In step ST7, if a collision is predicted between specific traffic participants in step ST7, the collaboration support device 6 predicts whether or not there is a risk to traffic participants around the specific traffic participant due to collision avoidance action being taken by at least one of these two or more specific traffic participants to avoid the predicted collision, and proceeds to step ST8.

[0135] In step ST8, the cooperation support device 6 determines notification targets from among a plurality of traffic participants in the monitoring area based on the prediction results in steps ST5 to ST7, notifies each notification target, and returns to step ST1.

[0136] Although one embodiment of the present invention has been described above, the present invention is not limited to this embodiment. The detailed configuration may be appropriately changed within the scope of the spirit of the present invention. [Explanation of symbols]

[0137] 1. Traffic safety support system 9. Target traffic area 2…Four-wheeled vehicle (transport participant) 20…In-vehicle equipment group 3…Motorcycle (transport participant) 30…In-vehicle equipment group 4. Pedestrians (traffic participants) 40...Portable information processing terminal 6…Coordination support device 60…Target traffic area recognition unit (recognition unit) 61...Driver information acquisition unit 62…Prediction unit 621...Group Classification Department (Classification Department) 622…First Prediction Section 623…Second Prediction Section 624…Third Prediction Section 65... Collaborative support information notification unit (notification unit)

Claims

1. a recognition unit for recognizing traffic participants as persons or moving objects in a target traffic area and obtaining recognition information about each traffic participant; a prediction unit for predicting futures of a plurality of traffic participants recognized by the recognition unit based on the recognition information; A traffic safety support system including: a notification unit that determines a notification target from among a plurality of traffic participants based on a prediction result by the prediction unit, and notifies the notification target, The recognition unit obtains information including a position and a movement vector of each traffic participant as the recognition information; The prediction unit comprises: a classification unit for dividing the plurality of traffic participants recognized by the recognition unit into a plurality of movement groups based on the recognition information, and acquiring movement group information including a position, a shape, and a movement vector of each movement group; a first prediction unit that predicts whether or not there will be a collision between each of the moving groups based on the moving group information and identifies a collision site in the moving group predicted to collide; a second prediction unit that, when a collision is predicted by the first prediction unit, determines two or more specific traffic participants from among the plurality of traffic participants based on the collision location, and predicts whether or not a collision will occur between the specific traffic participants; A traffic safety support system characterized in that, when a collision is predicted by the second prediction unit, the notification unit determines two or more of the specific traffic participants as first notification targets and issues a first notification to these first notification targets.

2. a driving subject information acquisition unit for acquiring state information correlated with a driving ability of a driving subject of a moving object recognized as a traffic participant by the recognition unit, The traffic safety support system according to claim 1 , wherein the second prediction unit predicts whether or not a collision will occur between the predicted targets based on the recognition information and the state information for the specific traffic participant.

3. The traffic safety support system according to claim 1, characterized in that the prediction unit further includes a third prediction unit that predicts a risk to traffic participants present around a specific traffic participant when a collision avoidance action is taken by at least one of the two or more specific traffic participants predicted to collide by the second prediction unit.

4. The notification unit: The traffic safety support system according to claim 1, characterized in that a second notification having a lower notification intensity than the first notification is made to traffic participants other than the specific traffic participant among those belonging to a moving group predicted to collide by the first prediction unit.

5. The traffic safety support system according to claim 4 , wherein the notification unit reduces a notification intensity of the second notification as a distance between the specific traffic participant and the second notification target increases.

6. The notification unit: a second notification having a lower notification intensity than the first notification is made to traffic participants other than the specific traffic participant among the traffic participants belonging to the moving group predicted to collide by the first prediction unit as a second notification target; The traffic safety support system according to claim 3, characterized in that a third notification having a lower notification intensity than the first notification is made to traffic participants predicted to be at risk by the third prediction unit.

7. a recognition unit for recognizing traffic participants as persons or moving objects in a target traffic area and obtaining recognition information about each traffic participant; a prediction unit for predicting futures of a plurality of traffic participants recognized by the recognition unit based on the recognition information, A recognition step of acquiring information including a position and a movement vector of each traffic participant as the recognition information; a classification step of dividing the plurality of traffic participants recognized by the recognition step into a plurality of movement groups based on the recognition information, and acquiring movement group information including a position, a shape, and a movement vector of each movement group; a first prediction step of predicting whether or not there will be a collision between each of the moving groups based on the moving group information and identifying a collision site in the moving group predicted to collide; a second prediction step of determining two or more specific traffic participants from among the plurality of traffic participants based on the collision location when a collision is predicted by the first prediction step, and predicting whether or not a collision will occur between the specific traffic participants; and a notification step of determining two or more of the specific traffic participants as first notification targets when a collision is predicted in the second prediction step, and issuing a first notification to these first notification targets.

8. A recognition unit for recognizing traffic participants as persons or moving objects in a target traffic area and obtaining recognition information about each traffic participant; a prediction unit for predicting futures of a plurality of traffic participants recognized by the recognition unit based on the recognition information; A traffic safety support system including: a notification unit that determines a notification target from among a plurality of traffic participants based on a prediction result by the prediction unit, and notifies the notification target, The recognition unit obtains information including a position and a movement vector of each traffic participant as the recognition information; The prediction unit comprises: a classification unit for dividing the plurality of traffic participants recognized by the recognition unit into a plurality of movement groups based on the recognition information, and acquiring movement group information including a position, a shape, and a movement vector of each movement group; a first prediction unit that predicts whether or not there will be a collision between each of the moving groups based on the moving group information and identifies a collision site in the moving group predicted to collide; a second prediction unit that, when a collision is predicted by the first prediction unit, determines two or more specific traffic participants from among the plurality of traffic participants based on the collision location, and predicts whether or not a collision will occur between the specific traffic participants; A traffic safety support system characterized in that, when a collision is predicted by the first and second prediction units, the notification unit determines a plurality of traffic participants belonging to the moving group predicted to collide by the first prediction unit as the notification targets, and notifies these notification targets.

9. A recognition unit for recognizing traffic participants as persons or moving objects in a target traffic area and obtaining recognition information about each traffic participant; a prediction unit for predicting futures of a plurality of traffic participants recognized by the recognition unit based on the recognition information, A recognition step of acquiring information including a position and a movement vector of each traffic participant as the recognition information; a classification step of dividing the plurality of traffic participants recognized by the recognition step into a plurality of movement groups based on the recognition information, and acquiring movement group information including a position, a shape, and a movement vector of each movement group; a first prediction step of predicting whether or not there will be a collision between each of the moving groups based on the moving group information and identifying a collision site in the moving group predicted to collide; a second prediction step of determining two or more specific traffic participants from among the plurality of traffic participants based on the collision location when a collision is predicted by the first prediction step, and predicting whether or not a collision will occur between the specific traffic participants; and a notification step of determining, when a collision is predicted in the first and second prediction steps, a plurality of traffic participants belonging to the movement group predicted to collide in the first prediction step as notification targets, and notifying these notification targets.

10. A recognition unit for recognizing traffic participants as persons or moving objects in a target traffic area and obtaining recognition information about each traffic participant; a prediction unit for predicting futures of a plurality of traffic participants recognized by the recognition unit based on the recognition information; A traffic safety support system including: a notification unit that determines a notification target from among a plurality of traffic participants based on a prediction result by the prediction unit, and notifies the notification target, The recognition unit obtains information including a position and a movement vector of each traffic participant as the recognition information; The prediction unit comprises: a classification unit for dividing the plurality of traffic participants recognized by the recognition unit into a plurality of movement groups based on the recognition information, and acquiring movement group information including a position, a shape, and a movement vector of each movement group; a first prediction unit that predicts whether or not there will be a collision between each of the moving groups based on the moving group information and identifies a collision site in the moving group predicted to collide; a second prediction unit that, when a collision is predicted by the first prediction unit, determines two or more specific traffic participants from among the plurality of traffic participants based on the collision location, and predicts whether or not a collision will occur between the specific traffic participants; The notification unit: A first notification is made to the specific traffic participant as a first notification target; a second notification having a lower notification intensity than the first notification is made to traffic participants other than the specific traffic participant among the traffic participants belonging to the moving group predicted to collide by the first prediction unit as a second notification target; A traffic safety support system, characterized in that the longer the distance between the specific traffic participant and the second notification target, the lower the notification intensity of the second notification.

11. A recognition unit for recognizing traffic participants as persons or moving objects in a target traffic area and obtaining recognition information about each traffic participant; a prediction unit for predicting futures of a plurality of traffic participants recognized by the recognition unit based on the recognition information; A traffic safety support system including: a notification unit that determines a notification target from among a plurality of traffic participants based on a prediction result by the prediction unit, and notifies the notification target, The recognition unit obtains information including a position and a movement vector of each traffic participant as the recognition information; The prediction unit comprises: a classification unit for dividing the plurality of traffic participants recognized by the recognition unit into a plurality of movement groups based on the recognition information, and acquiring movement group information including a position, a shape, and a movement vector of each movement group; a first prediction unit that predicts whether or not there will be a collision between each of the moving groups based on the moving group information and identifies a collision site in the moving group predicted to collide; a second prediction unit that, when a collision is predicted by the first prediction unit, determines two or more specific traffic participants from among the plurality of traffic participants based on the collision location, and predicts whether or not a collision occurs between the specific traffic participants; a third prediction unit that predicts a risk to traffic participants present around a specific traffic participant when a collision avoidance action is taken by at least one of the two or more specific traffic participants predicted to collide by the second prediction unit, The notification unit: A first notification is made to the specific traffic participant as a first notification target; a second notification having a lower notification intensity than the first notification is made to traffic participants other than the specific traffic participant among the traffic participants belonging to the moving group predicted to collide by the first prediction unit as a second notification target; A traffic safety support system characterized in that a third notification having a lower notification intensity than the first notification is made to traffic participants predicted to be at risk by the third prediction unit as a third notification target.

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