WO2019198449A1 - Information provision system, mobile terminal, information provision device, information provision method, and computer program - Google Patents

Information provision system, mobile terminal, information provision device, information provision method, and computer program Download PDF

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Publication number
WO2019198449A1
WO2019198449A1 PCT/JP2019/011739 JP2019011739W WO2019198449A1 WO 2019198449 A1 WO2019198449 A1 WO 2019198449A1 JP 2019011739 W JP2019011739 W JP 2019011739W WO 2019198449 A1 WO2019198449 A1 WO 2019198449A1
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WIPO (PCT)
Prior art keywords
information
vehicle
mobile
evaluation value
pedestrian
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PCT/JP2019/011739
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French (fr)
Japanese (ja)
Inventor
良明 林
Original Assignee
住友電気工業株式会社
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Application filed by 住友電気工業株式会社 filed Critical 住友電気工業株式会社
Priority to JP2020513152A priority Critical patent/JPWO2019198449A1/en
Publication of WO2019198449A1 publication Critical patent/WO2019198449A1/en

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968Systems involving transmission of navigation instructions to the vehicle
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/123Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
    • G08G1/133Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams within the vehicle ; Indicators inside the vehicles or at stops
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/16Anti-collision systems

Definitions

  • the present invention relates to an information providing system, a mobile terminal, an information providing apparatus, an information providing method, and a computer program.
  • This application claims priority based on Japanese Patent Application No. 2018-074446 filed on Apr. 10, 2018, and incorporates all the content described in the above Japanese application.
  • Patent Document 1 discloses a transportation system that informs the host vehicle of information on other vehicles.
  • An information providing system includes a mobile terminal mounted on at least a part of one or more moving objects located in a predetermined area, and the one or more movements in the map information of the area.
  • a calculation unit for obtaining an evaluation value of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals based on dynamic map information on which dynamic information about the body is superimposed; and the predicted traffic situation of each of the mobile terminals Determining whether to notify the mobile terminal whether or not to notify the mobile terminal based on the evaluation value, and notification for notifying the mobile terminal of the predicted traffic situation based on the determination result of the determination unit And a section.
  • a mobile terminal is a mobile terminal that receives the predicted traffic situation from the information providing system and outputs the predicted traffic situation to a user.
  • An information providing method is an information providing method for providing information to a mobile terminal, and includes dynamic information related to the one or more mobile objects in map information of an area where the one or more mobile objects are located.
  • a determination step for determining for each mobile terminal based on the evaluation value whether or not to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals, and based on the determination result of the determination unit
  • a notification step of notifying the mobile terminal of the predicted traffic situation is notifying the mobile terminal of the predicted traffic situation.
  • a computer program is a computer program for causing a computer to execute an information providing process for providing information to a mobile terminal, and is a map of an area where one or a plurality of moving objects are located on the computer. Predicting the traffic situation of each of the mobile terminals mounted on at least a part of the one or more mobile objects based on the dynamic map information in which the dynamic information about the one or more mobile objects is superimposed on the information
  • a notification step of notifying the mobile terminal of the predicted traffic situation based on a determination result of the determination unit It is an eye of the computer program.
  • An information providing apparatus is based on dynamic map information in which dynamic information about the one or more moving objects is superimposed on map information of an area where the one or more moving objects are located.
  • a calculation unit for obtaining an evaluation value of a predicted traffic situation that is a prediction result of a traffic situation of each mobile terminal mounted on at least a part of the one or more mobile objects, and the predicted traffic situation of each of the mobile terminals A determination unit that determines, for each mobile terminal, whether to notify the mobile terminal based on the evaluation value.
  • FIG. 1 is a schematic diagram illustrating an overall configuration of a wireless communication system according to an embodiment.
  • FIG. 2 is a block diagram illustrating an example of an internal configuration of the edge server and the core server.
  • FIG. 3 is a block diagram illustrating an example of an internal configuration of a vehicle-mounted device in which a communication terminal is mounted.
  • FIG. 4 is a block diagram illustrating an example of the internal configuration of the pedestrian terminal.
  • FIG. 5 is a block diagram illustrating an example of an internal configuration of a roadside sensor equipped with a wireless communication device that is a communication terminal.
  • FIG. 6 is an overall configuration diagram of the information providing system according to the present embodiment.
  • FIG. 7 is a sequence diagram illustrating an example of dynamic information update processing and distribution processing.
  • FIG. 8 is a functional block diagram of the edge server showing functions for providing the predicted traffic situation.
  • FIG. 9 is a diagram illustrating an example of a mobile object database.
  • FIG. 10 is a flowchart illustrating an example of a calculation process of the evaluation value of the predicted traffic situation by the calculation unit.
  • FIG. 11 is a flowchart showing an example of the vehicle calculation process in step S55 in FIG.
  • FIG. 12 is a flowchart illustrating an example of a pedestrian situation determination process in FIG. 11.
  • FIG. 13 is a flowchart showing an example of the pedestrian calculation process in FIG.
  • FIG. 14 is a diagram illustrating an example of an evaluation value database.
  • FIG. 15 is a flowchart illustrating an example of determination processing by the determination unit.
  • FIG. 10 is a flowchart illustrating an example of a calculation process of the evaluation value of the predicted traffic situation by the calculation unit.
  • FIG. 11 is a flowchart showing an example of the vehicle calculation process in step S55 in FIG.
  • FIG. 16 is a diagram illustrating a situation around an intersection according to scenario 1.
  • FIG. 17 is a diagram illustrating a situation around an intersection according to scenario 2.
  • FIG. 18 is a diagram illustrating a situation around an intersection according to scenario 3.
  • FIG. 19 is a diagram illustrating a situation around an intersection according to scenario 4.
  • FIG. 20 is a diagram illustrating a situation around an intersection according to scenario 5.
  • FIG. 21 is a diagram illustrating a situation around an intersection according to scenario 6.
  • FIG. FIG. 22 is a diagram illustrating an aspect of information provision executed by a system according to another embodiment.
  • the central device of the system is configured to determine the presence / absence of an abnormal event in each vehicle based on the vehicle information obtained from each vehicle and to notify the determination result to each vehicle.
  • the above conventional example it is configured to notify the result of the occurrence of an abnormal event.
  • the traffic situation of each moving body such as the presence or absence of the possibility of collision between the moving bodies using such a system is described.
  • the relationship between each vehicle is diverse, and when providing the information on the predicted traffic situation to each vehicle, the information given to each vehicle is provided if it is provided without selecting the information obtained. The amount becomes enormous and is not preferable from the viewpoint of the load applied to the system.
  • This disclosure has been made in view of such circumstances, and aims to provide a technology that can appropriately provide necessary information.
  • An information providing system includes a mobile terminal mounted on at least a part of one or a plurality of mobile objects located in a predetermined area, and the map information of the area including the 1 or Based on dynamic map information on which dynamic information on a plurality of moving objects is superimposed, a calculation unit that obtains an estimated value of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals, and each of the mobile terminals A determination unit that determines for each mobile terminal whether or not to notify the mobile terminal of the predicted traffic situation based on the evaluation value, and the mobile terminal based on the determination result of the determination unit A notification unit for notifying.
  • the notification unit notifies the predicted traffic situation to a mobile terminal determined to be notified by the determination unit among the mobile terminals. In this case, it is possible to provide information only to mobile terminals that are determined to require information on the predicted traffic situation based on the evaluation value.
  • the predicted traffic situation includes a target mobile unit equipped with a mobile terminal for which the evaluation value is calculated by the calculation unit, and the target mobile unit among the one or more mobile units. It is a prediction result of collision prediction with other mobile bodies other than the body, and the calculation unit performs the collision prediction for each of the mobile terminals based on the dynamic map information, and based on the prediction result
  • the evaluation value is preferably obtained as a value for evaluating the safety level of each mobile terminal. In this case, it is possible to obtain an evaluation value related to the safety degree based on the prediction of the collision between the mobile terminal and the mobile object.
  • the calculation unit identifies a moving body predicted to collide with the target moving body among the other moving bodies based on the prediction result, and It is preferable to obtain the evaluation value based on the prediction result related to the moving body predicted to collide. In this case, it is possible to obtain an evaluation value related to the degree of safety based on the collision prediction of the moving body predicted to collide.
  • the calculation unit when the calculation unit is a pedestrian when one of the target moving body and the moving body predicted to collide with the target moving body is a pedestrian, It is preferable to add an adjustment value according to the situation to the evaluation value. In this case, the situation unique to the pedestrian can be reflected in the execution determination of information provision to the mobile terminal.
  • the calculation unit determines whether or not there is a blind spot factor that causes a blind spot between the target moving body and a moving body that is predicted to collide with the target moving body.
  • the determination result of the presence / absence of the blind spot factor may be added to the evaluation value. In this case, the presence / absence of the blind spot factor can be reflected in the determination of execution of information provision to the mobile terminal.
  • the information providing system further includes a control unit that controls the mobile terminal so that the predicted traffic situation is output to a user of the mobile terminal, and the control unit
  • the output mode of the predicted traffic situation may be controlled to be different depending on the attribute of the moving body predicted to collide. In this case, it can output to a user in the output mode according to the characteristic of each attribute of the moving body estimated to collide.
  • the predicted traffic situation is information indicating whether or not a future movement of the mobile terminal for which the evaluation value is obtained by the calculation unit is a comfortable movement
  • the calculation The unit evaluates the future mobility comfort of each of the mobile terminals based on the dynamic map information, and obtains the evaluation value based on the future mobility comfort of each of the mobile terminals. Also good. In this case, an evaluation value regarding the comfort of each mobile terminal can be obtained.
  • the mobile terminal which is other embodiment receives the said predicted traffic condition from any one information provision system of said (1) to (8), and outputs the said predicted traffic condition to a user It is.
  • an information providing method is an information providing method for providing information to a mobile terminal.
  • the one or more information is provided.
  • an evaluation of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals mounted on at least a part of the one or more mobile bodies
  • a calculation step for obtaining a value a determination step for determining whether or not to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals based on the evaluation value, and determination by the determination unit
  • a computer program is a computer program for causing a computer to execute an information providing process for providing information to a mobile terminal, and one or a plurality of moving objects are located in the computer.
  • the traffic of each of the mobile terminals mounted on at least a part of the one or more mobile objects based on the dynamic map information in which the dynamic information about the one or more mobile objects is superimposed on the map information of the area
  • a determination step of determining, and a notification step of notifying the mobile terminal of the predicted traffic situation based on a determination result of the determination unit Is a computer program for causing.
  • the information providing apparatus includes dynamic map information in which dynamic information regarding the one or more moving objects is superimposed on map information of an area where the one or more moving objects are located.
  • a computing unit that obtains an evaluation value of a predicted traffic situation that is a prediction result of a traffic situation of each of the mobile terminals mounted on at least a part of the one or more mobile objects, and the predicted traffic of each of the mobile terminals
  • a determination unit that determines, for each mobile terminal, whether or not to notify the mobile terminal of a situation based on the evaluation value.
  • FIG. 1 is a schematic diagram illustrating an overall configuration of a wireless communication system according to an embodiment.
  • a wireless communication system includes a plurality of communication terminals 1A to 1D capable of wireless communication, one or more base stations 2 that wirelessly communicate with communication terminals 1A to 1D, and wired or wirelessly to base station 2. It includes one or more edge servers 3 that communicate with each other and one or more core servers 4 that communicate with the edge servers 3 in a wired or wireless manner.
  • Communication terminals 1A to 1D are also referred to as communication terminals 1 as representative.
  • the core server 4 is installed in the core data center (DC) of the core network.
  • the edge server 3 is installed in a distributed data center (DC) of a metro network.
  • a metro network is a communication network constructed for each city, for example. Each metro network is connected to a core network.
  • the base station 2 is communicably connected to any edge server 3 of the distributed data center included in the metro network.
  • the core server 4 is communicably connected to the core network.
  • the edge server 3 is communicably connected to the metro network. Therefore, the core server 4 can communicate with the edge server 3 and the base station 2 belonging to each metro network via the core network and the metro network.
  • the base station 2 includes at least one of a macro cell base station, a micro cell base station, and a pico cell base station.
  • the edge server 3 and the core server 4 are general-purpose servers capable of SDN (Software-Defined Networking).
  • the base station 2 and a relay device such as a repeater (not shown) are transport devices capable of SDN. Therefore, a plurality of virtual networks (network slices) S1 to S4 satisfying conflicting service request conditions such as low-latency communication and large-capacity communication can be defined as physical devices of the wireless communication system by network virtualization technology.
  • the above-mentioned network virtualization technology is a basic concept of “5th generation mobile communication system” (hereinafter abbreviated as “5G”), which is currently being standardized. Therefore, the wireless communication system according to the present embodiment is compliant with 5G, for example.
  • the radio communication system according to the present embodiment may be a mobile communication system capable of defining a plurality of network slices (hereinafter also referred to as “slices”) S1 to S4 according to predetermined service request conditions such as a delay time. What is necessary is just and it is not limited to 5G.
  • the hierarchy of slices to be defined is not limited to four, but may be five or more.
  • each network slice S1 to S4 is defined as follows.
  • the slice S1 is a network slice defined so that the communication terminals 1A to 1D communicate directly.
  • the communication terminals 1A to 1D that directly communicate in the slice S1 are also referred to as “node N1”.
  • the slice S2 is a network slice defined so that the communication terminals 1A to 1D communicate with the base station 2.
  • the highest communication node in the slice S2 (base station 2 in the illustrated example) is also referred to as “node N2”.
  • the slice S3 is a network slice defined so that the communication terminals 1A to 1D communicate with the edge server 3 via the base station 2.
  • the highest communication node (edge server 3 in the example) in the slice S3 is also referred to as “node N3”.
  • the node N2 becomes a relay node. That is, data communication is performed through an uplink path of node N1 ⁇ node N2 ⁇ node N3 and a downlink path of node N3 ⁇ node N2 ⁇ node N1.
  • the slice S4 is a network slice defined so that the communication terminals 1A to 1D communicate with the core server 4 via the base station 2 and the edge server 3.
  • the highest communication node in the slice S4 (core server 4 in the figure) is also referred to as “node N4”.
  • the node N2 and the node N3 are relay nodes. That is, data communication is performed by the uplink path of node N1 ⁇ node N2 ⁇ node N3 ⁇ node N4 and the downlink path of node N4 ⁇ node N3 ⁇ node N2 ⁇ node N1.
  • the routing does not use the edge server 3 as a relay node.
  • data communication is performed through the uplink path of node N1 ⁇ node N2 ⁇ node N4 and the downlink path of node N4 ⁇ node N2 ⁇ node N1.
  • the communication terminal 1A is a wireless communication device mounted on the vehicle 5.
  • the vehicles 5 include not only ordinary passenger cars but also public vehicles such as route buses and emergency vehicles.
  • the vehicle 5 may be a two-wheeled vehicle (motorcycle) as well as a four-wheeled vehicle.
  • the drive system of the vehicle 5 may be any of engine drive, electric motor drive, and hybrid system.
  • the driving method of the vehicle 5 may be any of normal driving in which the passenger performs operations such as acceleration / deceleration and steering of the steering wheel, and automatic driving in which the operation is performed by software.
  • the communication terminal 1 ⁇ / b> A of the vehicle 5 may be an existing wireless communication device in the vehicle 5, or may be a portable terminal brought into the vehicle 5 by a passenger.
  • the passenger's mobile terminal is temporarily connected to the in-vehicle LAN (Local Area Network) of the vehicle 5 to become an in-vehicle wireless communication device.
  • LAN Local Area Network
  • the communication terminal 1B is a portable terminal (pedestrian terminal) carried by the pedestrian 7.
  • the pedestrian 7 is a person who moves on foot such as outdoors on roads and parking lots and indoors such as in buildings and underground shopping streets.
  • the pedestrian 7 includes not only a person walking but also a person who rides on a bicycle having no power source.
  • the communication terminal 1 ⁇ / b> C is a wireless communication device mounted on the roadside sensor 8.
  • the roadside sensor 8 is an image type vehicle detector installed on the road, a security camera installed outdoors or indoors, and the like.
  • the communication terminal 1D is a wireless communication device mounted on the traffic signal controller 9 at the intersection.
  • FIG. 2 is a block diagram illustrating an example of the internal configuration of the edge server 3 and the core server 4.
  • the edge server 3 includes a control unit 31 including a CPU (Central Processing Unit), a ROM (Read Only Memory) 32, a RAM (Random Access Memory) 33, a storage unit 34, and a communication unit 35. including.
  • a CPU Central Processing Unit
  • ROM Read Only Memory
  • RAM Random Access Memory
  • the control unit 31 reads one or more programs stored in advance in the ROM 32 into the RAM 33 and executes them, thereby controlling the operation of each hardware and communicating the computer device with the core server 4 or the base station 2. It functions as the edge server 3.
  • the RAM 33 is composed of a volatile memory element such as SRAM (Static RAM) or DRAM (Dynamic RAM), and temporarily stores a program executed by the control unit 31 and data necessary for the execution.
  • SRAM Static RAM
  • DRAM Dynamic RAM
  • the storage unit 34 includes a non-volatile memory element such as a flash memory or an EEPROM (Electrically Erasable Programmable Read Only Memory), or a magnetic storage device such as a hard disk.
  • a non-volatile memory element such as a flash memory or an EEPROM (Electrically Erasable Programmable Read Only Memory), or a magnetic storage device such as a hard disk.
  • the communication unit 35 has a function of communicating with the core server 4 and the base station 2 via the metro network.
  • the communication unit 35 transmits the information given from the control unit 31 to the external device via the metro network and gives the information received via the metro network to the control unit 31.
  • the storage unit 34 stores a dynamic information map (hereinafter also simply referred to as “map”) M1 as dynamic map information.
  • the map M1 is an aggregate (virtual database) of data in which dynamic information that changes every moment is superimposed on a high-definition digital map that is static information.
  • the information constituting the map M1 includes the following “dynamic information” and “static information”.
  • “Dynamic information” refers to dynamic data that requires a delay time of 1 second or less.
  • the position information and signal information of mobile bodies (such as vehicles and pedestrians) that are utilized as ITS (Intelligent Transport Systems) prefetch information correspond to dynamic information.
  • the position information of the moving body included in the dynamic information does not have a wireless communication function in addition to the position information of the vehicle 5 and the pedestrian 7 that can perform wireless communication by having the communication terminals 1A and 1B. Position information of the vehicle 5 and the pedestrian 7 is also included.
  • Static information refers to static data that allows a delay time of one month or less.
  • road surface information, lane information, and three-dimensional structure data correspond to static information.
  • the control unit 31 of the edge server 3 updates the dynamic information of the map M1 stored in the storage unit 34 every predetermined update cycle (update process). Specifically, the control unit 31 collects, from each communication terminal 1A to 1D, various sensor information acquired by the vehicle 5, the roadside sensor 8, and the like within the service area of its own device at every predetermined update period. The dynamic information of the map M1 is updated based on the collected sensor information.
  • the control unit 31 When receiving the dynamic information request message from the communication terminal 1A, 1B of the predetermined user, the control unit 31 sends the latest dynamic information to the communication terminal 1A, 1B that is the transmission source of the request message for each predetermined distribution cycle. Distribute (distribution process). The control unit 31 collects traffic information and weather information of each location in the service area from the traffic control center and the private weather service support center, and updates the dynamic information or static information of the map M1 based on the collected information. May be.
  • the core server 4 includes a control unit 41 including a CPU, a ROM 42, a RAM 43, a storage unit 44, and a communication unit 45.
  • the control unit 41 reads one or more programs stored in advance in the ROM 32 into the RAM 43 and executes them to control the operation of each hardware and function as a core server 4 capable of communicating with the edge server 3.
  • the RAM 43 is composed of a volatile memory element such as SRAM or DRAM, and temporarily stores a program executed by the control unit 41 and data necessary for the execution.
  • the storage unit 44 is configured by a nonvolatile memory element such as a flash memory or an EEPROM, or a magnetic storage device such as a hard disk.
  • the communication unit 45 has a function of communicating with the edge server 3 and the base station 2 via the core network.
  • the communication unit 45 transmits information given from the control unit 41 to the external device via the core network, and gives information received via the core network to the control unit 41.
  • the storage unit 44 of the core server 4 stores an information map M2.
  • the data structure of the map M2 (data structure including dynamic information and static information) is the same as the data structure of the map M1.
  • the map M2 may be a map of the same service area as the map M1 of the specific edge server 3, or may be a wider area map in which the maps M1 held by the plurality of edge servers 3 are integrated.
  • control unit 41 of the core server 4 updates the dynamic information of the map M2 stored in the storage unit 44, and the distribution process of distributing the dynamic information in response to the request message. And may be performed. That is, the control unit 41 can perform update processing and distribution processing based on the map M2 of the own device independently of the edge server 3. That is, the control unit 41 can independently execute dynamic information update processing and distribution processing based on the map M2 of its own device separately from the edge server 3.
  • the core server 4 belonging to the slice S4 has a longer communication delay time with the communication terminals 1A to 1D than the edge server 3 belonging to the slice S3. For this reason, even if the core server 4 independently updates the dynamic information of the map M2, it is inferior in real time as compared to the dynamic information of the map M1 managed by the edge server 3. Therefore, for example, it is preferable that the control unit 31 of the edge server 3 and the control unit 41 of the core server 4 perform dynamic information update processing and distribution processing in a distributed manner according to the priority defined for each predetermined area. .
  • FIG. 3 is a block diagram illustrating an example of an internal configuration of the in-vehicle device 50 of the vehicle 5 on which the communication terminal 1A is mounted.
  • an in-vehicle device 50 mounted on a vehicle 5 includes a control unit (ECU: Electronic Control Unit) 51, a GPS receiver 52, a vehicle speed sensor 53, a gyro sensor 54, a storage unit 55, a display 56, a speaker. 57, an input device 58, an in-vehicle camera 59, a radar sensor 60, and a communication unit 61.
  • ECU Electronic Control Unit
  • the communication unit 61 is the communication terminal 1A described above (a wireless communication device capable of communication conforming to 5G). Therefore, the in-vehicle device 50 of the vehicle 5 can communicate with the edge server 3 as a kind of mobile terminal belonging to the slice S3. The in-vehicle device 50 of the vehicle 5 can also communicate with the core server 4 as a kind of mobile terminal belonging to the slice S4.
  • the control unit 51 is a computer device that performs route search of the vehicle 5, control of the other electronic devices 52 to 61, and the like.
  • the control unit 51 obtains the vehicle position of the host vehicle from GPS signals that the GPS receiver 52 periodically acquires. Further, the control unit 51 complements the vehicle position and direction based on the input signals of the vehicle speed sensor 53 and the gyro sensor 54, and grasps the accurate current position and direction of the vehicle 5.
  • the GPS receiver 52, the vehicle speed sensor 53, and the gyro sensor 54 are sensors that measure the current position, speed, and direction of the vehicle 5.
  • the storage unit 55 includes a map database.
  • the map database provides road map data to the control unit 51.
  • the road map data includes link data and node data, and is stored in a recording medium such as a DVD, a CD-ROM, a memory card, or an HDD.
  • the storage unit 55 reads out necessary road map data from the recording medium and provides it to the control unit 51.
  • the display 56 and the speaker 57 are output devices for notifying a user who is a passenger of the vehicle 5 of various information generated by the control unit 51. Specifically, the display 56 displays an input screen for route search, a map image around the host vehicle, route information to the destination, and the like. The speaker 57 outputs an announcement or the like for guiding the vehicle 5 to the destination. These output devices can also notify the passenger of the provision information received by the communication unit 61.
  • the input device 58 is a device for a passenger of the vehicle 5 to perform various input operations.
  • the input device 58 includes an operation switch provided on the handle, a touch panel provided on the joystick display 56, and a combination thereof.
  • the input device 58 may be a voice recognition device that accepts input by voice recognition of a passenger.
  • the input signal generated by the input device 58 is transmitted to the control unit 51.
  • the in-vehicle camera 59 is an image sensor that captures an image in front of the vehicle 5.
  • the in-vehicle camera 59 may be either monocular or compound eye.
  • the radar sensor 60 is a sensor that detects an object existing in front of or around the vehicle 5 by a millimeter wave radar, a LiDAR method, or the like. Based on the measurement data from the in-vehicle camera 59 and the radar sensor 60, the control unit 51 executes driving support control that outputs a warning to the occupant during driving to the display 56 or performs forced braking intervention. be able to.
  • the control unit 51 is configured by an arithmetic processing device such as a microcomputer that executes various control programs stored in the storage unit 55. As a function realized by executing the control program, the control unit 51 displays a map image on the display 56, a route from the departure point to the destination (including the position if there is a relay point). And various navigation functions such as a function of guiding the vehicle 5 to the destination according to the calculated route.
  • an arithmetic processing device such as a microcomputer that executes various control programs stored in the storage unit 55.
  • the control unit 51 displays a map image on the display 56, a route from the departure point to the destination (including the position if there is a relay point).
  • various navigation functions such as a function of guiding the vehicle 5 to the destination according to the calculated route.
  • the control unit 51 Based on the measurement data of at least one of the in-vehicle camera 59 and the radar sensor 60, the control unit 51 performs object recognition processing for recognizing an object in front of or around the host vehicle, and measurement for calculating a distance to the recognized object. And a function of executing distance processing.
  • the control unit 51 can calculate the position information of the object recognized by the object recognition process from the distance calculated by the distance measurement process and the sensor position of the host vehicle.
  • the control unit 51 can execute the following processes in communication with the edge server 3 (which may be the core server 4). 1) Request message transmission processing 2) Dynamic information reception processing 3) Change point information generation processing 4) Change point information transmission processing
  • the request message transmission process is a process of transmitting, to the edge server 3, a control packet for requesting distribution of dynamic information of the map M1 that is sequentially updated by the edge server 3.
  • the control packet includes the vehicle ID of the host vehicle.
  • the dynamic information receiving process is a process of receiving the dynamic information distributed by the edge server 3 to the own apparatus.
  • the change point information generation process by the control unit 51 calculates the change between the information from the comparison result between the received dynamic information and the sensor information of the host vehicle at the time of reception, and information on the difference between the two pieces of information. This is a process for generating change point information.
  • the change point information generated by the control unit 51 is, for example, the following information examples a1 to a2.
  • Information example a1 Change point information regarding a recognized object
  • the control unit 51 detects an object X (a moving object such as a vehicle or a pedestrian and an obstacle) that is not included in the received dynamic information by its own object recognition processing. In such a case, the detected image data of the object X and the position information are used as change point information.
  • the control unit 51 detects the detected object X And the difference value between the position information of the two are used as change point information.
  • Information example a2 Change point information regarding own vehicle
  • the control unit 51 deviates the position information of the own vehicle included in the received dynamic information from the vehicle position of the own vehicle calculated by the GPS signal by a predetermined threshold or more. If they are different, the difference value between them is used as change point information.
  • the control unit 51 determines the difference between the two. The value is used as change point information.
  • the control unit 51 When the change point information is generated as described above, the control unit 51 generates a communication packet addressed to the edge server 3 including the generated change point information and the vehicle ID of the host vehicle.
  • the change point information transmission process is a process of transmitting the communication packet including the change point information to the edge server 3.
  • the change point information transmission process is performed within the dynamic information distribution cycle by the edge server 3.
  • control unit 51 executes driving support control that causes the display 56 to output a warning for a driver who is driving or to perform forced braking intervention. You can also.
  • FIG. 4 is a block diagram illustrating an example of an internal configuration of the pedestrian terminal 70 (communication terminal 1B).
  • the pedestrian terminal 70 in FIG. 4 is a wireless communication device capable of communication processing based on 5G, for example. Therefore, the pedestrian terminal 70 can communicate with the edge server 3 as a kind of mobile terminal belonging to the slice S3.
  • the pedestrian terminal 70 can also communicate with the core server 4 as a kind of mobile terminal belonging to the slice S4.
  • pedestrian terminal 70 includes a control unit 71, a storage unit 72, a display unit 73, an operation unit 74, and a communication unit 75.
  • the communication unit 75 is a communication interface that wirelessly communicates with the base station 2 of the carrier that provides the 5G service.
  • the communication unit 75 converts the RF signal from the base station 2 into a digital signal and outputs it to the control unit 71. Further, the communication unit 75 converts the digital signal input from the control unit 71 into an RF signal and transmits the RF signal to the base station 2.
  • the control unit 71 includes a CPU, a ROM, and a RAM.
  • the control unit 71 reads out and executes the program stored in the storage unit 72 and controls the overall operation of the pedestrian terminal 70.
  • the storage unit 72 is configured by a hard disk, a non-volatile memory, or the like, and stores various computer programs and data.
  • the storage unit 72 stores a mobile ID that is identification information of the pedestrian terminal 70.
  • the mobile ID is, for example, a unique user ID or MAC address of the carrier contractor.
  • the storage unit 72 stores various application software arbitrarily installed by the user.
  • the application software stored in the storage unit 72 includes, for example, application software for receiving an information providing service for receiving dynamic information of the map M1 through communication with the edge server 3 (or the core server 4). .
  • the operation unit 74 includes various operation buttons and a touch panel function of the display unit 73.
  • the operation unit 74 outputs an operation signal corresponding to a user operation to the control unit 71.
  • the display unit 73 is, for example, a liquid crystal display.
  • the display unit 73 presents various information to the user. For example, the display unit 73 displays the image data of the information maps M1 and M2 transmitted from the servers 3 and 4 on the screen.
  • the control unit 71 uses the time synchronization function to acquire the current time from the GPS signal, the position detection function to measure the current position (latitude, longitude, and altitude) of the host vehicle from the GPS signal, and the direction sensor to determine the direction of the pedestrian 7. And a direction detection function for measuring.
  • the control unit 71 can execute the following processes in communication with the edge server 3 (which may be the core server 4). 1) Request message transmission processing 2) Dynamic information reception processing 3) Change point information generation processing 4) Change point information transmission processing
  • the request message transmission process is a process of transmitting, to the edge server 3, a control packet for requesting distribution of dynamic information of the map M1 that is sequentially updated by the edge server 3.
  • the control packet includes the mobile ID of the pedestrian terminal 70.
  • the dynamic information receiving process is a process of receiving the dynamic information distributed by the edge server 3 to the own apparatus.
  • the change point information generation process by the control unit 71 calculates the change between the received dynamic information and the sensor information of the host vehicle at the time of reception, and information on the difference between the two pieces of information. This is a process for generating change point information.
  • the change point information generated by the control unit 71 is, for example, the following information example.
  • the control unit 71 has a predetermined threshold value based on the position information of the own pedestrian 7 included in the received dynamic information and the position of the own pedestrian 7 calculated by the GPS signal. When there is a deviation, the difference value between the two is used as change point information. When the azimuth of the pedestrian 7 included in the received dynamic information and the azimuth of the pedestrian 7 calculated by the azimuth sensor are deviated by a predetermined threshold or more, the control unit 71 sets a difference value between the two. Change point information.
  • the control unit 71 When generating the change point information as described above, the control unit 71 generates a communication packet addressed to the edge server 3 including the generated change point information and the portable ID of the terminal 70 itself.
  • the change point information transmission process is a process of transmitting the communication packet including the change point information to the edge server 3.
  • the change point information transmission process is performed within the dynamic information distribution cycle by the edge server 3.
  • control unit 71 transmits the state information including the position and orientation information of the terminal 70 to the edge server 3 by performing the change point information generation process and the change point information transmission process.
  • FIG. 5 is a block diagram showing an example of the internal configuration of the roadside sensor 8 equipped with a wireless communication device that is the communication terminal 1C.
  • roadside sensor 8 includes a control unit 81, a storage unit 82, a roadside camera 83, a radar sensor 84, and a communication unit 85.
  • the communication unit 85 is the above-described communication terminal 1C, that is, a wireless communication device capable of communication processing based on, for example, 5G. Therefore, the roadside sensor 8 can communicate with the edge server 3 as a kind of fixed terminal belonging to the slice S3. The roadside sensor 8 can also communicate with the core server 4 as a kind of fixed terminal belonging to the slice S4.
  • the control unit 81 includes a CPU, a ROM, and a RAM.
  • the control unit 81 reads and executes the program stored in the storage unit 82 and controls the overall operation of the roadside sensor 8.
  • the storage unit 82 is configured by a hard disk, a non-volatile memory, or the like, and stores various computer programs and data.
  • the storage unit 82 stores a sensor ID that is identification information of the roadside sensor 8.
  • the sensor ID is, for example, a user ID unique to the owner of the roadside sensor 8 or a MAC address.
  • the roadside camera 83 is an image sensor that captures an image of a predetermined shooting area.
  • the roadside camera 83 may be either monocular or compound eye.
  • the radar sensor 60 is a sensor that detects an object existing in front of or around the vehicle 5 by a millimeter wave radar, a LiDAR method, or the like.
  • the control unit 81 transmits the captured video data and the like to the security administrator's computer device.
  • the control unit 81 transmits the captured video data and the like to the traffic control center.
  • the control unit 81 performs object recognition processing for recognizing an object in the shooting area based on at least one measurement data of the roadside camera 83 and the radar sensor 84, and distance measurement processing for calculating a distance to the recognized object. , Has a function of executing.
  • the control unit 51 can calculate the position information of the object recognized by the object recognition process from the distance calculated by the distance measurement process and the sensor position of the host vehicle.
  • the control unit 81 can execute the following processes in communication with the edge server 3 (which may be the core server 4). 1) Change point information generation process 2) Change point information transmission process
  • the change point information generation processing in the roadside sensor 8 is based on the comparison result between the previous sensor information and the current sensor information for each predetermined measurement cycle (for example, the dynamic information distribution cycle by the edge server 3). This is a process of calculating changes between sensor information and generating change point information that is information relating to differences between the two pieces of information.
  • the change point information generated by the roadside sensor 8 is, for example, the following information example b1.
  • the control unit 81 detects an object Y (a moving object such as a vehicle or a pedestrian and an obstacle) that has not been detected in the previous object recognition process by the current object recognition process. In such a case, the detected image data of the object Y and the position information are used as change point information.
  • the control unit 81 detects the detected object Y. And the difference value between them are used as change point information.
  • the control unit 81 When generating the change point information as described above, the control unit 81 generates a communication packet addressed to the edge server 3 including the generated change point information and the sensor ID of the own device.
  • the change point information transmission process is a process of transmitting the communication packet including the change point information in the data to the edge server 3.
  • the change point information transmission process is performed within the dynamic information distribution cycle by the edge server 3.
  • FIG. 6 is an overall configuration diagram of the information providing system according to the present embodiment.
  • the information providing system according to the present embodiment includes a large number of vehicles 5, pedestrian terminals 70, and roadside sensors 8 scattered in a service area (real world) of edge server 3 that is relatively wide.
  • these communication nodes include an edge server 3 that can perform wireless communication with low delay by communication based on 5G performed via the base station 2 and functions as an information providing apparatus. That is, the information providing system includes a part or all of the above-described wireless communication system.
  • the mobile body existing in the service area of the edge server 3 includes the vehicle 5 capable of wireless communication by mounting the communication terminal 1A and the in-vehicle device 50, and the pedestrian 7 carrying the pedestrian terminal 70. Also included are a vehicle 5 that does not have a wireless communication function and a pedestrian 7 that does not carry the pedestrian terminal 70.
  • the edge server 3 collects the above-described change point information at a predetermined cycle from the in-vehicle device 50 of the vehicle 5 in the service area, the pedestrian terminal 70, the roadside sensor 8, and the like (step S31).
  • the edge server 3 integrates the collected change point information by map matching (integration processing), and updates the dynamic information of the information map M1 being managed (step S32).
  • the edge server 3 transmits the latest dynamic information to the requesting communication node (step S33). Thereby, for example, the vehicle 5 that has received the dynamic information can use the dynamic information for driving assistance of the passenger.
  • the edge server 3 may transmit the map M1 updated in step S32 as dynamic information to the requesting communication node.
  • the vehicle 5 that has received the dynamic information detects the change point information with the sensor information of the vehicle based on the dynamic information, the vehicle 5 transmits the detected change point information to the edge server 3 (step S34).
  • change point information collection (step S31) ⁇ dynamic information update (step S32) ⁇ dynamic information distribution (step S33) ⁇ change point information detection by a vehicle (Step S34) ⁇ Information processing in each communication node circulates in the order of change point information collection (Step S31).
  • FIG. 6 illustrates an information providing system including only one edge server 3, the information providing system may include a plurality of edge servers 3, instead of the edge server 3, or in addition to the edge server 3.
  • One or a plurality of core servers 4 may be included.
  • the information map M1 managed by the edge server 3 may be a map in which at least dynamic information of an object is superimposed on map information such as a digital map. This also applies to the core server information map M2.
  • FIG. 7 is a sequence diagram illustrating an example of dynamic information update processing and distribution processing executed by the cooperation of the pedestrian terminal 70, the in-vehicle device 50 of the vehicle 5, the roadside sensor 8, and the edge server 3.
  • the execution subject is the pedestrian terminal 70, the in-vehicle device 50 of the vehicle 5, the roadside sensor 8, and the edge server 3, but the actual execution subject is the control units 71, 51, 81, 31. It is. 7, U1, U2,... Are dynamic information distribution cycles.
  • step S ⁇ b> 1 when the edge server 3 receives the dynamic information request message from the pedestrian terminal 70 and the in-vehicle device 50 of the vehicle 5 (step S ⁇ b> 1), the latest dynamic information at the time of reception is transmitted to the transmission source. To the pedestrian terminal 70 and the in-vehicle device 50 of the vehicle 5 (step S2).
  • the edge server 3 analyzes the received request message, and when the information indicating the request source included in the message is information indicating the communication terminal 1 registered in advance, Send dynamic information to the source.
  • step S1 If there is a request message from either one of the pedestrian terminal 70 and the in-vehicle device 50 in step S1, dynamic information is distributed only to one communication terminal that is the transmission source of the request message in step S2. Is done.
  • the pedestrian terminal 70 that has received the dynamic information distributed in step S2 generates change point information within the distribution cycle U1 (step S3), and transmits the generated change point information to the edge server 3 (step S6).
  • the vehicle-mounted device 50 that has received the dynamic information distributed in step S2 generates change point information from the comparison result between the dynamic information and its own sensor information within the distribution cycle U1 (step S4), and the generated change.
  • the point information is transmitted to the edge server 3 (step S6).
  • the roadside sensor 8 produces
  • the edge server 3 When the edge server 3 receives the change point information from the pedestrian terminal 70, the in-vehicle device 50, and the roadside sensor 8 within the update cycle U1, the edge server 3 updates the dynamic information reflecting the change point information (step S7). The updated dynamic information is distributed to the pedestrian terminal 70 and the in-vehicle device 50 (step S8).
  • step S6 when only the in-vehicle device 50 generates change point information within the distribution cycle U1, only the change point information generated by the in-vehicle device 50 in step S4 is transmitted to the edge server 3 (step S6), and the change point The dynamic information that reflects only the information is updated (step S7). If the pedestrian terminal 70, the in-vehicle device 50, and the roadside sensor 8 do not perform change point information within the distribution cycle U1, the processes of steps S3 to S7 are not executed, and the dynamic information for the previous transmission is transmitted. The same dynamic information as (Step S2) is distributed to the pedestrian terminal 70 and the in-vehicle device 50 (Step S8). Thus, the edge server 3 updates the dynamic information in step S7 based on the change point information transmitted within the distribution cycle U1.
  • the pedestrian terminal 70 that has received the dynamic information distributed in step S8 generates change point information within the distribution cycle U2 (step S9), and transmits the generated change point information to the edge server 3 (step S12). ).
  • the in-vehicle device 50 that has received the dynamic information distributed in step S8 generates change point information from the comparison result between the dynamic information and its own sensor information within the distribution cycle U2 (step S10), and the generated change.
  • the point information is transmitted to the edge server 3 (step S12). Moreover, if the roadside sensor 8 produces
  • the edge server 3 When receiving the change point information from the in-vehicle device 50 and the roadside sensor 8 within the distribution cycle U2, the edge server 3 updates the dynamic information reflecting the change point information (step S13), and the updated dynamic information. Is distributed to the pedestrian terminal 70 and the vehicle-mounted device 50 (step S14). Thus, the edge server 3 updates the dynamic information in step S13 based on the change point information transmitted within the distribution cycle U2.
  • step S14 is performed until either the dynamic information distribution stop request message is received from both the pedestrian terminal 70 and the vehicle 5 or the communication between the pedestrian terminal 70 and the vehicle 5 is interrupted. And the same sequence is repeated.
  • the information providing system of the present embodiment has a function of providing information related to the predicted traffic situation to the pedestrian terminal 70 mounted on one or a plurality of moving bodies located in the service area and the in-vehicle device 50 of the vehicle 5.
  • the predicted traffic situation indicates a result of predicting a future traffic situation.
  • FIG. 8 is a functional block diagram of the edge server 3 showing functions for providing the predicted traffic situation.
  • the control unit 31 of the edge server 3 functionally includes a calculation unit 31a, a determination unit 31b, a notification unit 31c, and a detection unit 31d. Each of these functions is realized by the control unit 31 executing a program stored in the storage unit 34.
  • the calculation unit 31a is a mobile terminal (pedestrian terminal 70 and on-vehicle device) mounted on a mobile body (pedestrian 7, vehicle 5) located in the service area represented by the dynamic information map M1.
  • Device 50 It has a function of predicting each traffic situation and obtaining an evaluation value of the predicted traffic situation.
  • the computing unit 31a refers to a mobile database 34a (described later) in which information obtained from the dynamic information map M1 is registered, and obtains an estimated value of the predicted traffic situation.
  • the determination unit 31b has a function of determining, based on the evaluation value, whether to notify the mobile terminal (the pedestrian terminal 70 and the in-vehicle device 50) information regarding the predicted traffic situation of each mobile terminal. Yes.
  • the notification unit 31c has a function of notifying the mobile terminal of information related to the predicted traffic situation based on the determination result of the determination unit 31b.
  • the detection unit 31d detects a plurality of moving bodies (pedestrian 7 and vehicle 5) whose position information is included in the dynamic information of the dynamic information map M1, and the moving body information indicating the status of each moving body. It has the function to generate.
  • FIG. 9 is a diagram illustrating an example of the mobile object database 34a.
  • the moving body information generated by the detection unit 31d is registered in the moving body database 34a.
  • the mobile database 34a is managed and updated by the detection unit 31d.
  • the detection unit 31d refers to the dynamic information map M1, and when the position information of a new moving body (pedestrian 7, vehicle 5) is registered in the dynamic information, the moving body ID is given to the moving body, The mobile body information corresponding to the mobile body ID is generated and registered in the mobile body database 34a.
  • the detection unit 31d detects a moving body whose position information is registered in the dynamic information map M1, and assigns a moving body ID to each moving body to generate moving body information.
  • the moving body information includes information such as information on presence / absence of a communication function, vehicle ID (mobile ID), moving body attribute information, position information, direction information indicating a moving direction, and speed information indicating a moving speed.
  • the attribute information is information indicating the type of the moving object, for example, information indicating whether the moving object is a vehicle or a pedestrian.
  • attribute information contains the information which shows whether it is an adult or a child, and the information which shows the direction of a body, when a moving body is a pedestrian.
  • the attribute information includes information indicating whether or not the pedestrian is a crutch or wheelchair user, information indicating the appearance of the color or type of clothes, information indicating whether or not the user is a walking smartphone, and the like. Also good.
  • the mobile body database 34a is provided with columns for registering mobile body IDs, information on presence / absence of communication functions, vehicle ID (mobile ID), mobile body attribute information, position information, direction information, and speed information. ing.
  • the detecting unit 31d refers to the dynamic information map M1 and generates moving body information for each moving body.
  • the detection unit 31d includes information on the presence or absence of a communication function included in the dynamic information map M1, the vehicle ID (mobile ID), and the position information among the mobile body information. Get as it is.
  • the detection unit 31d refers to the image data of the moving object captured by the camera or the like included in the dynamic information map M1, determines the attribute of each moving object, and generates attribute information based on the determination To do.
  • the detection unit 31d calculates based on the temporal change of the position information of each moving object included in the dynamic information map M1.
  • the detection unit 31d repeatedly generates the mobile body information of each mobile body and registers the mobile body information in the mobile body database 34a, and updates the mobile body database 34a as needed. Thereby, the moving body information registered in the moving body database 34a is maintained in the latest information.
  • evaluation value database 34b in FIG. 8 is a database for registering the evaluation value of the predicted traffic situation obtained by the calculation unit 31a.
  • the evaluation value database 34b will be described later.
  • FIG. 10 is a flowchart illustrating an example of a calculation process of the evaluation value of the predicted traffic situation by the calculation unit 31a.
  • the computing unit 31a reads the mobile object database 34a (step S51), and specifies a mobile object having a communication function as an evaluation target (step S52).
  • Information relating to the predicted traffic situation can be provided to a mobile body having the pedestrian terminal 70 and the in-vehicle device 50. Therefore, the calculating part 31a specifies the mobile body which has the pedestrian terminal 70 and the vehicle-mounted apparatus 50 as an evaluation object which calculates
  • the evaluation object is a movement having the pedestrian terminal 70 or the in-vehicle device 50 that is the evaluation object in addition to the pedestrian terminal 70 or the in-vehicle device 50 that is carried or mounted on the moving body. It may refer to the body (target moving body).
  • the calculation unit 31a performs evaluation value calculation processing (step S53).
  • the calculation unit 31a sequentially executes the process for each of the specified evaluation targets, and repeats the process until it is processed for all the evaluation targets.
  • the calculation unit 31a first determines whether or not the attribute to be evaluated is a vehicle (step S54).
  • step S54 When it is determined that the attribute to be evaluated is a vehicle (step S54), the calculation unit 31a proceeds to step S55 and performs a calculation process for the vehicle. The calculation unit 31a obtains an evaluation value to be evaluated in the vehicle calculation process (step S55).
  • FIG. 11 is a flowchart showing an example of the vehicle calculation process in step S55 in FIG.
  • the calculation unit 31a identifies a moving body (another moving body) other than the evaluation target (step S61), and a collision between the evaluation target (target moving body) and a moving body other than the evaluation target.
  • the predicted time is calculated for each mobile object other than the evaluation target (step S62).
  • the calculation unit 31a refers to the moving object database 34a and the evaluation object and the moving object other than the evaluation object collide with each other from the position information, the azimuth information, and the speed information of the evaluation object and the moving object other than the evaluation object.
  • the estimated collision time is obtained.
  • the calculation unit 31a sets the collision prediction time to an extremely large predetermined value (for example, 5 minutes).
  • the calculation unit 31a sets the collision prediction time to the predetermined value even when the calculated collision prediction time is equal to or longer than the predetermined value.
  • the calculation unit 31a predicts a collision between the evaluation object and a mobile body other than the evaluation object based on the dynamic information map M1, and obtains a collision prediction time as a prediction result (predicted traffic situation) of the collision prediction. .
  • the computing unit 31a identifies the mobile body having the shortest predicted collision time among the predicted collision times calculated for each of the mobile bodies other than the evaluation target as a collision prediction target (step S63).
  • the calculating part 31a specifies the mobile body of the shortest collision prediction time as a collision prediction object.
  • the computing unit 31a obtains an evaluation value of the prediction result (collision prediction result) based on the collision prediction time between the evaluation object and the collision prediction object (step S64).
  • the calculation unit 31a obtains an evaluation value of the prediction result according to the following rule with respect to the collision prediction time.
  • the setting is as follows, but the present invention is not limited to this.
  • the evaluation value is set such that the larger the value, the higher the factor that hinders the safety of the evaluation target. That is, the evaluation value is a value for evaluating the degree of safety of each evaluation object.
  • the calculation unit 31a sets “0” as the evaluation value for the moving body other than the collision prediction target.
  • the calculation unit 31a obtains an evaluation value for each moving object based on the collision prediction time that is a prediction result of the collision prediction between the evaluation object and the moving object other than the evaluation object. Thereby, the evaluation value of the collision prediction between the evaluation object and the moving object other than the evaluation object can be obtained.
  • the calculation unit 31a selects a mobile body (collision prediction target) that is predicted to collide with the evaluation target among the mobile bodies other than the evaluation target based on the collision prediction time that is a prediction result of the collision prediction. And an evaluation value is obtained based on the collision prediction time for the collision prediction target. Thereby, it is possible to obtain an evaluation value related to a collision prediction of an evaluation target predicted to collide.
  • step S65 determines whether or not there is a blind spot factor that causes a blind spot between the evaluation target and the collision prediction target.
  • the presence or absence of a blind spot factor between the evaluation target and the collision prediction target is determined by the calculation unit 31a referring to the dynamic information map M1.
  • the computing unit 31a refers to the dynamic information map M1 and determines the presence or absence of a building or other moving body that blocks the prospects of both between the evaluation target and the collision prediction target. When such a building or other moving body exists between the evaluation target and the collision prediction target, the calculation unit 31a determines that there is a blind spot factor between the evaluation target and the collision prediction target. On the other hand, if there is nothing that blocks the line of sight between the evaluation target and the collision prediction target, the calculation unit 31a determines that there is no blind spot factor.
  • step S65 If it is determined in step S65 that there is a blind spot factor between the evaluation target and the collision prediction target, the computing unit 31a adds to the evaluation value obtained in step S64 (step S66), and proceeds to step S67. On the other hand, when it is determined that there is no blind spot factor between the evaluation target and the collision prediction target (step S65), the calculation unit 31a proceeds to step S67 without performing addition to the evaluation value.
  • the evaluation value is set such that the larger the value, the higher the factor that hinders the safety of the evaluation target.
  • the calculating part 31a adds to an evaluation value.
  • the added value added to the evaluation value in step S66 is “100”, for example. This added value is an example and is not limited to this. The same applies to the added values shown below.
  • the calculation unit 31a determines the presence / absence of a blind spot factor that causes a blind spot between the evaluation target and the collision prediction target, and adds the determination result of the presence / absence of the blind spot factor to the evaluation value.
  • the presence / absence of the blind spot factor can be reflected in the evaluation value, and can be reflected in the execution determination of providing information to the evaluation target described later.
  • step S67 the calculation unit 31a determines whether or not the collision prediction target is a pedestrian (step S67).
  • the collision prediction target the moving body
  • step S68 determines the situation of the pedestrian 7 that is the collision prediction target, and finishes the process.
  • the collision prediction target (the moving body) is not the pedestrian 7
  • the collision prediction target is the vehicle 5
  • the calculation unit 31 a finishes the vehicle calculation process without determining the situation of the pedestrian 7.
  • FIG. 12 is a flowchart showing an example of the situation determination process for the pedestrian 7 in FIG.
  • the calculation unit 31 a determines whether or not the pedestrian 7 subject to collision prediction is walking on a pedestrian crossing or a sidewalk (step S ⁇ b> 71). Whether or not the pedestrian 7 subject to collision prediction is walking on a pedestrian crossing or a sidewalk is determined by referring to the dynamic information map M1 by the calculation unit 31a.
  • the computing unit 31a compares the position information of the pedestrian crossing and the sidewalk included in the static information of the dynamic information map M1 with the position information of the pedestrian 7, so that the pedestrian 7 walks the pedestrian crossing or the sidewalk. It can be determined whether or not.
  • step S71 when it determines with the pedestrian 7 of collision prediction object not walking the pedestrian crossing or a sidewalk, the calculating part 31a adds to an evaluation value (step S72), and progresses to step S73.
  • step S71 when it determines with the pedestrian 7 of collision prediction object walking the pedestrian crossing or a sidewalk (step S71), the calculating part 31a progresses to step S73, without performing addition with respect to an evaluation value.
  • the calculating part 31a adds to an evaluation value. Note that the added value added to the evaluation value in step S72 is, for example, “100”.
  • the computing unit 31a determines whether or not the walking speed of the pedestrian 7 to be predicted for collision is slower than a predetermined value (step S73). Whether or not the walking speed of the pedestrian 7 subject to collision prediction is slower than a predetermined value can be determined by referring to the mobile database 34a.
  • the predetermined value to be compared with the walking speed is set, for example, every 3.6 km as a general pedestrian speed.
  • step S73 when it determines with the walking speed of the pedestrian 7 of collision prediction object being slower than predetermined value, the calculating part 31a adds to an evaluation value (step S74), and progresses to step S75.
  • step S74 when it determines with the walking speed of the pedestrian 7 of collision prediction object not being slower than predetermined value (step S73), the calculating part 31a progresses to step S75, without adding with respect to an evaluation value.
  • the pedestrian 7 subject to collision prediction when crossing a pedestrian crossing and the walking speed of the pedestrian 7 is slower than a predetermined value, the pedestrian 7 may not cross the pedestrian crossing during the green light. Considering the fact that there is, there is a safety hindrance factor in the evaluation target. Therefore, when it determines with the walking speed of the pedestrian 7 being slower than a predetermined value, the calculating part 31a adds to an evaluation value. Note that the added value added to the evaluation value in step S74 is, for example, “100”.
  • the computing unit 31a determines whether or not the attribute of the pedestrian 7 to be predicted for collision is a child (step S75). Whether or not the attribute of the pedestrian 7 to be predicted for collision is a child can be determined by referring to the mobile database 34a.
  • step S75 when it determines with the attribute of the pedestrian 7 of collision prediction object being a child, the calculating part 31a adds to an evaluation value (step S76), and progresses to step S77.
  • step S76 when it determines with the attribute of the pedestrian 7 of collision prediction object not being a child (step S75), the calculating part 31a progresses to step S77, without performing addition with respect to an evaluation value.
  • the calculation unit 31a adds to the evaluation value.
  • the added value added to the evaluation value in step S76 is “100”, for example.
  • the calculation unit 31a determines whether or not the pedestrian 7 subject to collision prediction is meandering (step S77). Whether or not the pedestrian 7 subject to collision prediction is meandering can be determined based on a time-dependent change in the position information of the moving body included in the moving body database 34a or the dynamic information map M1.
  • step S77 when it is determined that the pedestrian 7 subject to collision prediction is meandering, the calculation unit 31a adds the evaluation value (step S78), and proceeds to step S79.
  • step S78 when it determines with the pedestrian 7 of collision prediction object not meandering (step S77), the calculating part 31a progresses to step S79, without performing addition with respect to an evaluation value.
  • the calculating part 31a adds to an evaluation value.
  • the added value added to the evaluation value in step S78 is, for example, “100”.
  • the calculation unit 31a determines whether or not the pedestrian 7 to be predicted for collision is ignoring the signal (step S79). Whether or not the pedestrian 7 subject to collision prediction ignores the signal can be determined based on the signal information included in the dynamic information of the dynamic information map M1 and the position information of the moving body.
  • step S79 when it is determined that the pedestrian 7 subject to collision prediction ignores the signal, the calculation unit 31a adds to the evaluation value (step S80), and ends the vehicle calculation process (FIG. 11).
  • step S80 when it determines with the pedestrian 7 of collision prediction object not ignoring a signal (step S79), the calculating part 31a complete
  • the calculating part 31a adds to an evaluation value.
  • the addition value added to the evaluation value in step S79 is, for example, “100”.
  • the calculation unit 31a acquires the situation regarding the pedestrian 7, and adds the added value as the adjustment value according to the acquired situation of the pedestrian 7 to the evaluation value.
  • the calculation unit 31a performs the vehicle calculation process (step S55 in FIG. 10) to obtain the evaluation value to be evaluated.
  • step S54 when it is determined in step S54 in FIG. 10 that the attribute to be evaluated is not a vehicle (step S54), the calculation unit 31a proceeds to step S56 and performs a pedestrian calculation process.
  • the computing unit 31a obtains an evaluation value to be evaluated in the pedestrian computation process (step S56).
  • FIG. 13 is a flowchart showing an example of the pedestrian calculation process in FIG.
  • Step 61 to Step S ⁇ b> 66 are the same processes as those in FIG. 11 except for whether the evaluation target is a vehicle or a pedestrian. Therefore, description of step 61 to step S66 is omitted.
  • step S65 or step S66 the arithmetic unit 31a proceeds to step S82.
  • step 82 the calculation unit 31a determines whether or not the collision prediction target is a vehicle (step S82). When it determines with a collision prediction object (its mobile body) being a vehicle, the calculating part 31a progresses to step S83, performs the situation determination of the pedestrian 7 which is an evaluation object, and complete
  • the situation determination process of the pedestrian 7 to be evaluated is the same as in FIG.
  • the calculation unit 31a finishes the pedestrian calculation process without determining the situation of the evaluation target pedestrian 7.
  • the rule regarding the evaluation value according to the collision prediction time and the addition value added to the evaluation value by each determination are the calculation process for the vehicle in consideration of being a pedestrian. Set to a different value.
  • the calculation unit 31a determines whether or not the collision prediction target is a pedestrian in step S67 in FIG. 11 showing the vehicle calculation process, and only when the collision prediction target (the moving body) is the pedestrian 7. Then, the situation of the pedestrian 7 that is a collision prediction target is determined. Similarly, in step S82 in FIG. 13 showing the pedestrian calculation process, the calculation unit 31a determines whether or not the collision prediction target is a vehicle, and determines that the collision prediction target (the moving body) is a vehicle. Only when it does, the situation determination of the pedestrian 7 which is an evaluation object is performed.
  • the calculation unit 31a acquires the situation related to the pedestrian and acquires the acquired pedestrian. 7 is added to the evaluation value.
  • the situation unique to the pedestrian can be reflected in the evaluation value, and can be reflected in the execution determination for providing information to the evaluation target described later.
  • step S57 when the evaluation value of the evaluation target is obtained by the vehicle calculation process of step S55 or the pedestrian calculation process of step S56, the calculation unit 31a proceeds to step S57 and uses the calculated evaluation value as the evaluation value. Registration in the database 34b (step S57).
  • the calculation unit 31a sequentially performs the processing from step S54 to step S57 in FIG. 10 on the specified evaluation target, and repeats the processing until all the evaluation targets are processed.
  • the calculation unit 31a obtains evaluation values for all the specified evaluation targets and registers them in the database 34b, the calculation unit 31a returns to step S51 again and repeats the same processing.
  • the calculation unit 31a repeatedly calculates and registers the evaluation value of each specified evaluation target by repeating the calculation process, and updates the registration content of the evaluation value database 34b as needed.
  • FIG. 14 is a diagram illustrating an example of the evaluation value database 34b. As shown in FIG. 14, in the evaluation value database 34b, the mobile object ID to be evaluated and the evaluation values of mobile objects other than the evaluation object are registered in association with each other.
  • the evaluation value database 34b is provided with a mobile object ID field to be evaluated, a vehicle ID (mobile ID) field, and a mobile object evaluation value field other than the evaluation object.
  • the mobile object ID of the mobile object specified as the evaluation object is registered in the column of the evaluation object mobile object ID.
  • vehicle ID (mobile ID) the vehicle ID (mobile ID) of the mobile terminal pedestrian terminal 70 or the in-vehicle device 50 included in the mobile object to be evaluated is registered.
  • the column of the evaluation value of the mobile body other than the evaluation target includes a mobile body ID column of each mobile body other than the evaluation target.
  • the evaluation value of each of the plurality of mobile objects is registered in the column of the evaluation value of the mobile object other than the evaluation object.
  • the evaluation value for the moving object other than the collision prediction target is set to “0”. Therefore, a mobile body other than the evaluation target in which a value other than “0” is registered as the evaluation value of the mobile body other than the evaluation target indicates that the evaluation target is a collision prediction target.
  • the collision prediction object of each evaluation object can be specified by referring to the evaluation value database 34b.
  • FIG. 15 is a flowchart illustrating an example of a determination process performed by the determination unit 31b.
  • the determination unit 31b refers to the evaluation value database 34b and determines whether there is an evaluation target whose evaluation value is equal to or greater than a preset threshold value (step S85). If it determines with there being no evaluation object whose evaluation value is more than a threshold value in step S85, the determination part 31b will repeat step S85 further. Therefore, the determination unit 31b repeats Step S85 until it is determined that there is an evaluation target whose evaluation value is equal to or greater than the threshold value.
  • step S85 If it is determined in step S85 that there is an evaluation object whose evaluation value is equal to or greater than the threshold value, the determination unit 31b proceeds to step S86 and determines to notify the evaluation object of information related to the collision prediction result of the collision prediction object. Return to step S85.
  • the determination unit 31b refers to the evaluation value of each evaluation object, and if there are a plurality of evaluation objects whose evaluation values are equal to or greater than the threshold value, determines the notification of information related to the collision prediction result of the collision prediction object to all the evaluation objects. . As described above, the determination unit 31b determines, for each evaluation target, whether or not to notify the evaluation target of information related to the prediction result of each evaluation target based on the evaluation value.
  • whether or not to notify information related to the collision prediction result (information related to the predicted traffic situation) is determined for each of the evaluation targets (the pedestrian terminal 70, the in-vehicle device 50, or the mobile body having these). Since it determines for every evaluation object based on the evaluation value of a prediction result, required information can be appropriately provided to each evaluation object.
  • the dynamic information map M1 on which dynamic information on a plurality of moving objects is superimposed is used in order to obtain the evaluation value of the prediction result of the collision prediction of each evaluation target, there is also a moving object on which no mobile terminal is mounted.
  • the evaluation value of the predicted traffic situation can be obtained, and the traffic situation appropriately predicted for each evaluation target can be expressed as the evaluation value.
  • the information regarding the prediction result appropriately collided can be appropriately provided to each evaluation object.
  • the notification unit 31c determines the collision prediction result between the evaluation target and the collision prediction target to the evaluation target for which the determination unit 31b has determined the notification. Notify information about. Thereby, it is possible to provide information only to the mobile terminal that is determined to need information on the prediction result of the collision prediction based on the evaluation value.
  • the information related to the collision prediction result notified to the evaluation target by the notification unit 31c includes the attribute of the collision prediction target, the direction in which the collision prediction target approaches, the collision prediction time, and the like.
  • the mobile terminal (the pedestrian terminal 70 and the in-vehicle device 50) to be evaluated that has received the notification by the notification unit 31c outputs information on the notified prediction result to the user of the mobile terminal.
  • FIG. 16 is a diagram illustrating a situation around an intersection according to scenario 1.
  • pedestrians 7 ⁇ / b> A and 7 ⁇ / b> B get off the vehicle 5 ⁇ / b> C parked at a position immediately after passing the pedestrian crossing P and cross the pedestrian crossing P.
  • the pedestrian 7A is an adult, and the pedestrian 7B is a child.
  • the light color of the signal of the pedestrian crossing P was flashing blue.
  • the light color of the signal of the route on which the vehicle 5A travels is red, but the signal of the pedestrian crossing P is blinking blue.
  • the vehicle 5A approaching the pedestrian crossing P recognizes that it will soon turn blue. For this reason, it is assumed that the vehicle 5A attempts to pass through the intersection without stopping. It is assumed that the pedestrians 7A and 7B cannot see the vehicle 5A due to the presence of the vehicle 5C. Further, a vehicle 5B further travels behind the vehicle 5A.
  • the vehicles 5A, 5B, 5C and pedestrians 7A, 7B are registered as moving bodies in the dynamic information map M1 and the moving body database 34a by the system. Further, it is assumed that the vehicles 5A and 5B are equipped with the in-vehicle device 50, and the pedestrians 7A and 7B carry the pedestrian terminal 70.
  • the edge server 3 (the computing unit 31a thereof) specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B.
  • the pedestrians 7A and 7B have a child attribute (only the pedestrian 7B) and ignore the signal.
  • a vehicle 5C that is a blind spot factor exists between the vehicle 5A and the pedestrians 7A and 7B.
  • the edge server 3 when the edge server 3 obtains an evaluation value when the vehicle 5A is an evaluation object, the pedestrian situation determination is taken into consideration in addition to the collision prediction time. In this scenario, an additional value is added to the evaluation value due to blind spot factor, pedestrian attributes, and signal ignorance.
  • the threshold value used for determining whether or not to notify the prediction result is set smaller than the evaluation value in the case where factors that inhibit safety overlap as in this scenario. Therefore, in the case of this scenario, the evaluation values of the pedestrians 7A and 7B in the vehicle 5A are larger than the threshold value. For this reason, the edge server 3 notifies the information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A to the vehicle 5A.
  • the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction time when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 notifies the pedestrians 7A and 7B of the information related to the collision prediction result of the vehicle 5A in the pedestrians 7A and 7B. .
  • the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B.
  • the evaluation value is set to a large value.
  • the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
  • the edge server 3 can appropriately provide necessary information to each mobile terminal.
  • the in-vehicle device 50 of the vehicles 5A and 5B and the pedestrian terminal 70 of the pedestrians 7A and 7B output information on the collision prediction result to the user of the own device based on the notification from the edge server 3.
  • the edge server 3 can make the user of the vehicle 5A recognize in advance that a pedestrian appears from the right side of the pedestrian crossing P ahead.
  • the pedestrians 7A and 7B are displayed without specifying them.
  • the display method may be different depending on whether the attribute of the pedestrian 7 is a child or an adult. . This is because pedestrians need more attention if they are children.
  • the output mode of the information related to the collision prediction result may be controlled differently according to the attribute of the collision prediction target.
  • information can be output to a user in the output mode according to the feature of the attribute of a collision prediction object.
  • the output screen V2 of the pedestrian terminals 70 of the pedestrians 7A and 7B includes a display D3 indicating that the vehicle A appears from the left side of the front pedestrian crossing P, an arrow D4 indicating the traveling direction of the vehicle 5A, and the like. Is displayed. Thereby, the edge server 3 can make the pedestrians 7A and 7B recognize in advance that the vehicle appears from the left side of the pedestrian crossing P ahead.
  • a display D5 or the like indicating a warning to the vehicle 5A traveling in front of the host vehicle is displayed.
  • the edge server 3 can make the user of the vehicle 5B recognize in advance that the vehicle 5A traveling ahead stops and approaches.
  • the edge server 3 can avoid collision between the moving bodies by causing the in-vehicle device 50 of the vehicles 5A and 5B and the pedestrian terminal 70 of the pedestrians 7A and 7B to output to the user. it can.
  • the output of the information regarding the collision prediction result by the pedestrian terminal 70 and the vehicle-mounted apparatus 50 is controlled by the output control part which the control part 71 and the control part 51 of the pedestrian terminal 70 and the vehicle-mounted apparatus 50 have.
  • the control part 31 of the edge server 3 has an output control part which can control the output toward the user by the pedestrian terminal 70 and the vehicle-mounted apparatus 50
  • the output control part of the edge server 3 is You may control the output to the user by the pedestrian terminal 70 and the vehicle-mounted apparatus 50.
  • FIG. 17 is a diagram illustrating a situation around an intersection according to scenario 2.
  • the settings of the vehicles 5A and 5B and the pedestrians 7A and 7B are the same as in the scenario 1.
  • scenario 2 there is no scenario 5 vehicle 5C.
  • scenario 2 the pedestrians 7A and 7B cross the pedestrian crossing P at a speed lower than a general walking speed (3.6 km / hour).
  • the signal color of the pedestrian crossing P was flashing blue at the timing when the pedestrians 7A and 7B started to cross the pedestrian crossing P. In the middle of the pedestrian crossing P, the signal color of the pedestrian crossing P turns red, and the pedestrians 7A and 7B slowly cross the pedestrian crossing P at the same walking speed.
  • the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A, and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B.
  • the edge server 3 obtains an evaluation value when the vehicle 5A is an evaluation object, the pedestrian attribute, the speed of the pedestrian, and an addition value obtained by ignoring the signal are added to the evaluation value obtained from the collision prediction time. to add.
  • the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
  • the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 sends the information regarding the prediction result of the collision prediction of the vehicle 5A in the pedestrians 7A and 7B to the pedestrians 7A and 7B. Notice.
  • the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B.
  • the evaluation value is set to a large value.
  • the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
  • the in-vehicle device 50 of the vehicles 5A and 5B and the pedestrian terminal 70 of the pedestrians 7A and 7B output information on the collision prediction result to the user of the own device based on the notification from the edge server 3.
  • the edge server 3 can make the user of the vehicle 5A recognize in advance that a pedestrian appears from the right side of the pedestrian crossing P ahead.
  • the edge server 3 can make the pedestrians 7A and 7B recognize in advance that a vehicle appears from the left side of the front crosswalk P.
  • the edge server 3 can avoid the collision of each moving body by making the vehicle-mounted apparatus 50 of vehicle 5A, 5B and the pedestrian terminal 70 of pedestrian 7A, 7B perform an output to a user. .
  • FIG. 18 is a diagram illustrating a situation around an intersection according to scenario 3.
  • pedestrians 7A and 7B walk along the sidewalk H, and there is an obstacle G1 on the sidewalk H.
  • the pedestrians 7A and 7B are walking on the roadway avoiding the obstacle G1.
  • the pedestrian 7A is an adult, and the pedestrian 7B is a child.
  • the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A, and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B.
  • the attributes of the pedestrians 7A and 7B are children (only the pedestrian 7B) and do not walk on the sidewalk.
  • the edge server 3 obtains the evaluation value of the pedestrians 7A and 7B when the vehicle 5A is the evaluation target, the attribute of the pedestrian and the pedestrian walk to the evaluation value obtained from the predicted collision time. Add the value depending on where you are (whether you are walking on a pedestrian crossing or sidewalk). Thereby, the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
  • the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 notifies the pedestrians 7A and 7B of the information related to the collision prediction result of the vehicle 5A in the pedestrians 7A and 7B. .
  • the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B. Further, a vehicle 5D that is a blind spot factor exists between the vehicle 5B and the vehicle 5A.
  • the edge server 3 When the edge server 3 obtains an evaluation value when the vehicle 5B is an evaluation object, the edge server 3 adds an addition value based on the presence or absence of a blind spot factor to the evaluation value obtained from the collision prediction time. If the evaluation value of the vehicle 5A in the vehicle 5B is larger than the threshold value, the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
  • the edge server 3 specifies the vehicle 5B as a collision prediction target of the vehicle C. As a result of the collision prediction, if the collision prediction time is short, the evaluation value is set to a large value. As a result, the edge server 3 notifies the vehicle 5C of information related to the collision prediction result of the vehicle 5B in the vehicle 5C.
  • the edge server 3 makes the in-vehicle device 50 of the vehicles 5A, 5B, and 5C and the pedestrian terminal 70 of the pedestrians 7A and 7B perform the output to the user, thereby avoiding collision between the moving bodies. Can do.
  • FIG. 19 is a diagram illustrating a situation around an intersection according to scenario 4.
  • pedestrians 7A and 7B walk along the sidewalk H, they are walking between the parked vehicle 5C and the vehicle 5D and are not crosswalks to cross the roadway.
  • the pedestrian 7A is an adult, and the pedestrian 7B is a child.
  • the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A, and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B.
  • the attributes of the pedestrians 7A and 7B are children (only the pedestrian 7B) and do not walk on the sidewalks and pedestrian crossings.
  • a vehicle 5D that is a blind spot factor exists between the vehicle 5A and the pedestrians 7A and 7B.
  • the edge server 3 calculates the evaluation value of the pedestrians 7A and 7B when the vehicle 5A is the evaluation target, in addition to the collision prediction time, the attribute of the pedestrian, the place where the pedestrian is walking (crossing)
  • the added value is added to the evaluation value depending on whether there is a sidewalk or whether or not walking on the sidewalk and whether there is a blind spot factor.
  • the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
  • the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 notifies the pedestrians 7A and 7B of the information related to the collision prediction result of the vehicle 5A in the pedestrians 7A and 7B. .
  • the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B.
  • the evaluation value is set to a large value.
  • the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
  • in-vehicle device that includes the in-vehicle camera 59 in the vehicle 5 through which the pedestrian slips, in addition to detection by the roadside sensor 8. If 50 is mounted, the vehicle-mounted camera 59 can also detect it.
  • FIG. 20 is a diagram illustrating a situation around an intersection according to scenario 5.
  • pedestrians 7A and 7B meander along the sidewalk H and walk.
  • the pedestrian 7A is an adult, and the pedestrian 7B is a child.
  • the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A, and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B.
  • the attributes of the pedestrians 7A and 7B are children (only the pedestrian 7B), and when the pedestrians protrude from the roadway, they are not walking on the sidewalk.
  • the edge server 3 obtains the evaluation value of the pedestrians 7A and 7B when the vehicle 5A is the evaluation target
  • the evaluation value obtained from the collision prediction time includes the attribute of the pedestrian, the walking state of the pedestrian ( Addition value depending on whether or not meandering and a place where a pedestrian is walking (whether or not walking on a pedestrian crossing or a sidewalk).
  • the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
  • the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 notifies the pedestrians 7A and 7B of the information related to the collision prediction result of the vehicle 5A in the pedestrians 7A and 7B. .
  • the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B.
  • the edge server 3 calculates
  • FIG. 21 is a diagram illustrating a situation around an intersection according to scenario 6.
  • pedestrians 7A and 7B cross a pedestrian crossing P that crosses a route R1.
  • the signal color of the pedestrian crossing P was flashing blue. The color changes to red, and the pedestrians 7A and 7B hurry to cross the pedestrian crossing P as they are.
  • the pedestrian 7A is an adult, and the pedestrian 7B is a child.
  • the vehicle 5A enters the intersection from the route R2, turns left, and travels in the intersection toward the route R1. Further, the vehicle 5B travels following the vehicle 5A. Since the lamp color of the signal of the pedestrian crossing P changes from flashing blue to red, the lights of the vehicles 5A and 5B and the traffic lights ahead are also switched from blue to yellow and red. Therefore, the vehicles 5A and 5B are rushing to pass through the intersection. Furthermore, there is a building G2 between the route R2 and the route R1 and at the corner of the intersection that blocks the view of the route R1 and the route R2.
  • the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A and the collision prediction targets of the pedestrians 7A and 7B. As a result, the vehicle 5A is specified. In addition, the attributes of the pedestrians 7A and 7B are children (only the pedestrian 7B), and the signals are ignored. Furthermore, there is a building G2 that is a blind spot factor between the vehicle 5A and the pedestrians 7A and 7B.
  • the edge server 3 obtains an evaluation value when the vehicle 5A is an evaluation object, the pedestrian attribute, the presence / absence of a blind spot factor, and an addition value by signal ignorance are added to the evaluation value obtained from the collision prediction time. to add.
  • the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
  • the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 sends the information regarding the prediction result of the collision prediction of the vehicle 5A in the pedestrians 7A and 7B to the pedestrians 7A and 7B. Notice.
  • the edge server 3 identifies the vehicle 5A as a collision prediction target of the vehicle 5B. As a result of the collision prediction, if the collision prediction time is short, the evaluation value is set to a large value. As a result, the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
  • the in-vehicle device 50 of the vehicles 5A and 5B and the pedestrian terminal 70 of the pedestrians 7A and 7B output information on the collision prediction result to the user of the own device based on the notification from the edge server 3.
  • the edge server 3 can make the user of the vehicle 5A recognize in advance that a pedestrian crosses the pedestrian crossing P.
  • the edge server 3 can make the pedestrians 7A and 7B recognize in advance that the vehicle 5A appears from the right side of the pedestrian crossing P.
  • the edge server 3 can avoid the collision of each moving body by making the vehicle-mounted apparatus 50 of vehicle 5A, 5B and the pedestrian terminal 70 of pedestrian 7A, 7B perform an output to a user. .
  • FIG. 22 is a diagram illustrating an aspect of information provision executed by a system according to another embodiment.
  • FIG. 22 is a flowchart illustrating an example of arithmetic processing according to another embodiment.
  • the edge server 3 of the present embodiment is configured to evaluate the comfort of movement of each evaluation object based on the dynamic information map M1 and obtain an evaluation value based on the comfort of future movement of each evaluation object. Has been. That is, the predicted traffic situation of each evaluation object predicted by the calculation unit 31a of the present embodiment is a situation indicating whether or not the future movement of the evaluation object is a comfortable movement.
  • the edge server 3 divides each route in the service area into a plurality of unit areas, determines whether there is a factor that impairs comfort in each unit area, and determines comfort. Identify non-comfortable areas that have more than a certain amount of damage.
  • the edge server 3 registers the determination result in the database and updates it as needed.
  • the factor that impairs comfort is, for example, the occurrence of traffic jams or the presence of a meandering pedestrian. If these factors exist above a certain level, the edge server 3 identifies the unit area as a non-comfort area.
  • the edge server 3 calculates
  • the evaluation value is set according to the distance between the evaluation target and the non-comfort area. This evaluation value is set to a larger value as the evaluation target and the non-comfort area are closer.
  • the evaluation value of the present embodiment is set according to the possibility that the evaluation target passes through the non-comfort area.
  • the determination unit 31b When the evaluation value is equal to or greater than a predetermined threshold, the determination unit 31b notifies the evaluation target of information related to the non-comfort area. And when approaching a non-comfort area, the in-vehicle device 50 of vehicles 5A and 5B and the pedestrian terminal 70 of pedestrians 7A and 7B send information about the non-comfort area based on the notification from the edge server 3. To the user.
  • each route R10, R11, R12, R13, R14 delimited by the intersection constitutes a unit area.
  • a traffic jam occurs in route R11, and meandering pedestrians 7A and 7B exist.
  • the edge server 3 identifies the route R11 as a non-comfort area. It is assumed that other routes are not specified as non-comfort areas.
  • the vehicle 5A traveling along the route R10 toward the intersection where the route R11 and the route R12 are connected is approaching the route R11 which is a non-comfort area.
  • the evaluation value of the vehicle 5A as the evaluation target increases as it approaches the route R11 that is a non-comfort area, and becomes equal to or higher than a predetermined threshold value.
  • the edge server 3 notifies the vehicle 5A, which is the evaluation target, of information related to the non-comfort area.
  • the vehicle 5B traveling along the route R13 toward the intersection where the route R11 and the route R14 are connected is approaching the route R11 which is a non-comfort area.
  • the evaluation value of the vehicle 5B as the evaluation target increases as it approaches the route R11 that is a non-comfort area, and becomes equal to or greater than a predetermined threshold value.
  • the edge server 3 notifies the information regarding the non-comfort area to the vehicle 5B which is the evaluation target.
  • the in-vehicle device 50 of the vehicle 5 ⁇ / b> A or 5 ⁇ / b> B Based on the notification from the edge server 3, the in-vehicle device 50 of the vehicle 5 ⁇ / b> A or 5 ⁇ / b> B outputs information on the non-comfort area that is likely to pass in the future to the user of the own device as information on the predicted traffic information.
  • a display D10 indicating that a non-comfort area exists, an arrow D11 indicating a detour avoiding the non-comfort area, and the like Is displayed.
  • a display D12 indicating that a non-comfort area exists, an arrow D13 indicating a detour avoiding the non-comfort area, and the like are displayed. Is done.
  • the edge server 3 can make the user of the vehicle 5A recognize in advance that a non-comfort area appears, and can maintain the comfort during movement for each evaluation object.

Abstract

Provided is an information provision system comprising: a mobile terminal installed in one or at least a portion of a plurality of mobile bodies located within a prescribed area; a computation unit for obtaining an evaluation value for the result of a forecast of a traffic situation for each mobile terminal, i.e., a forecast traffic situation, on the basis of dynamic map information in which dynamic information relating to the one or the plurality of mobile bodies is superposed over map information of the area; a determination unit for determining whether to report the forecast traffic situation for each mobile terminal to mobile terminals on the basis of the evaluation value and on a per mobile terminal basis; and a report unit for reporting the forecast traffic situation to mobile terminals on the basis of the results of determination by the determination unit.

Description

情報提供システム、移動端末、情報提供装置、情報提供方法、及びコンピュータプログラムInformation providing system, mobile terminal, information providing apparatus, information providing method, and computer program
 本発明は、情報提供システム、移動端末、情報提供装置、情報提供方法、及びコンピュータプログラムに関するものである。
 本出願は、2018年4月10日出願の日本出願第2018-075446号に基づく優先権を主張し、前記日本出願に記載された全ての記載内容を援用するものである。
The present invention relates to an information providing system, a mobile terminal, an information providing apparatus, an information providing method, and a computer program.
This application claims priority based on Japanese Patent Application No. 2018-074446 filed on Apr. 10, 2018, and incorporates all the content described in the above Japanese application.
 特許文献1には、他車両の情報を自車両に報知する交通システムが開示されている。 Patent Document 1 discloses a transportation system that informs the host vehicle of information on other vehicles.
特開2013-109746号公報JP 2013-109746 A
 一実施形態である情報提供システムは、所定のエリア内に位置する1又は複数の移動体のうちの少なくとも一部に搭載された移動端末と、前記エリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算部と、前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定部と、前記判定部の判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知部と、を備えている。 An information providing system according to an embodiment includes a mobile terminal mounted on at least a part of one or more moving objects located in a predetermined area, and the one or more movements in the map information of the area. A calculation unit for obtaining an evaluation value of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals based on dynamic map information on which dynamic information about the body is superimposed; and the predicted traffic situation of each of the mobile terminals Determining whether to notify the mobile terminal whether or not to notify the mobile terminal based on the evaluation value, and notification for notifying the mobile terminal of the predicted traffic situation based on the determination result of the determination unit And a section.
 また、他の実施形態である移動端末は、上記情報提供システムから前記予測交通状況を受け付け、ユーザへ前記予測交通状況を出力する移動端末である。 Further, a mobile terminal according to another embodiment is a mobile terminal that receives the predicted traffic situation from the information providing system and outputs the predicted traffic situation to a user.
 他の実施形態である情報提供方法は、移動端末へ情報提供を行う情報提供方法であって、1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算ステップと、前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定ステップと、前記判定部の判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知ステップと、を含む。 An information providing method according to another embodiment is an information providing method for providing information to a mobile terminal, and includes dynamic information related to the one or more mobile objects in map information of an area where the one or more mobile objects are located. A calculation step for obtaining an evaluation value of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals mounted on at least a part of the one or more mobile objects based on the dynamic map information on which the information is superimposed And a determination step for determining for each mobile terminal based on the evaluation value whether or not to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals, and based on the determination result of the determination unit A notification step of notifying the mobile terminal of the predicted traffic situation.
 また、他の実施形態であるコンピュータプログラムは、移動端末へ情報提供を行う情報提供処理をコンピュータに実行させるためのコンピュータプログラムであって、前記コンピュータに1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算ステップと、前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定ステップと、前記判定部の判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知ステップと、を実行させるためのコンピュータプログラムである。 A computer program according to another embodiment is a computer program for causing a computer to execute an information providing process for providing information to a mobile terminal, and is a map of an area where one or a plurality of moving objects are located on the computer. Predicting the traffic situation of each of the mobile terminals mounted on at least a part of the one or more mobile objects based on the dynamic map information in which the dynamic information about the one or more mobile objects is superimposed on the information A calculation step for obtaining an evaluation value of a predicted traffic situation as a result, and a determination for determining whether to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals based on the evaluation value for each mobile terminal And a notification step of notifying the mobile terminal of the predicted traffic situation based on a determination result of the determination unit It is an eye of the computer program.
 また、他の実施形態である情報提供装置は、1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算部と、前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定部と、を備えている。 An information providing apparatus according to another embodiment is based on dynamic map information in which dynamic information about the one or more moving objects is superimposed on map information of an area where the one or more moving objects are located. A calculation unit for obtaining an evaluation value of a predicted traffic situation that is a prediction result of a traffic situation of each mobile terminal mounted on at least a part of the one or more mobile objects, and the predicted traffic situation of each of the mobile terminals A determination unit that determines, for each mobile terminal, whether to notify the mobile terminal based on the evaluation value.
図1は、一実施形態にかかる無線通信システムの全体構成を示す概略図である。FIG. 1 is a schematic diagram illustrating an overall configuration of a wireless communication system according to an embodiment. 図2は、エッジサーバおよびコアサーバの内部構成の一例を示すブロック図である。FIG. 2 is a block diagram illustrating an example of an internal configuration of the edge server and the core server. 図3は、通信端末を搭載した車両の車載装置の内部構成の一例を示すブロック図である。FIG. 3 is a block diagram illustrating an example of an internal configuration of a vehicle-mounted device in which a communication terminal is mounted. 図4は、歩行者端末の内部構成の一例を示すブロック図である。FIG. 4 is a block diagram illustrating an example of the internal configuration of the pedestrian terminal. 図5は、通信端末である無線通信機を搭載した路側センサの内部構成の一例を示すブロック図である。FIG. 5 is a block diagram illustrating an example of an internal configuration of a roadside sensor equipped with a wireless communication device that is a communication terminal. 図6は、本実施形態にかかる情報提供システムの全体構成図である。FIG. 6 is an overall configuration diagram of the information providing system according to the present embodiment. 図7は、動的情報の更新処理および配信処理の一例を示すシーケンス図である。FIG. 7 is a sequence diagram illustrating an example of dynamic information update processing and distribution processing. 図8は、予測交通状況を提供するための機能について示したエッジサーバの機能ブロック図である。FIG. 8 is a functional block diagram of the edge server showing functions for providing the predicted traffic situation. 図9は、移動体データベースの一例を示す図である。FIG. 9 is a diagram illustrating an example of a mobile object database. 図10は、演算部による予測交通状況の評価値の演算処理の一例を示すフローチャートである。FIG. 10 is a flowchart illustrating an example of a calculation process of the evaluation value of the predicted traffic situation by the calculation unit. 図11は、図10中ステップS55の車両用演算処理の一例を示すフローチャートである。FIG. 11 is a flowchart showing an example of the vehicle calculation process in step S55 in FIG. 図12は、図11中の歩行者の状況判定処理の一例を示すフローチャートである。FIG. 12 is a flowchart illustrating an example of a pedestrian situation determination process in FIG. 11. 図13は、図10中の歩行者用演算処理の一例を示すフローチャートである。FIG. 13 is a flowchart showing an example of the pedestrian calculation process in FIG. 図14は、評価値データベースの一例を示す図である。FIG. 14 is a diagram illustrating an example of an evaluation value database. 図15は、判定部による判定処理の一例を示すフローチャートである。FIG. 15 is a flowchart illustrating an example of determination processing by the determination unit. 図16は、シナリオ1に係る交差点周辺の状況を示した図である。FIG. 16 is a diagram illustrating a situation around an intersection according to scenario 1. FIG. 図17は、シナリオ2に係る交差点周辺の状況を示した図である。FIG. 17 is a diagram illustrating a situation around an intersection according to scenario 2. 図18は、シナリオ3に係る交差点周辺の状況を示した図である。FIG. 18 is a diagram illustrating a situation around an intersection according to scenario 3. 図19は、シナリオ4に係る交差点周辺の状況を示した図である。FIG. 19 is a diagram illustrating a situation around an intersection according to scenario 4. 図20は、シナリオ5に係る交差点周辺の状況を示した図である。FIG. 20 is a diagram illustrating a situation around an intersection according to scenario 5. In FIG. 図21は、シナリオ6に係る交差点周辺の状況を示した図である。FIG. 21 is a diagram illustrating a situation around an intersection according to scenario 6. In FIG. 図22は、他の実施形態に係るシステムによって実行される情報提供の態様を示す図である。FIG. 22 is a diagram illustrating an aspect of information provision executed by a system according to another embodiment.
[本開示が解決しようとする課題]
 上記従来例では、システムの中央装置が各車両から得られた車両情報に基づいて各車両の異常事象の有無を判定し、判定結果を各車両に報知するように構成されている。
[Problems to be solved by the present disclosure]
In the above conventional example, the central device of the system is configured to determine the presence / absence of an abnormal event in each vehicle based on the vehicle information obtained from each vehicle and to notify the determination result to each vehicle.
 上記従来例では、異常事象が生じた結果を報知するように構成されているが、例えば、このようなシステムを用いて移動体同士の衝突可能性の有無等といった各移動体個々の交通状況を予測しようとする場合、各車両同士の関係は多様であり、予測した交通状況の情報を各車両に提供する際に、得られた情報取捨選択することなく提供すれば、各車両に与えられる情報量が膨大になり、システムに与える負荷の観点から好ましくない。 In the above conventional example, it is configured to notify the result of the occurrence of an abnormal event. For example, the traffic situation of each moving body such as the presence or absence of the possibility of collision between the moving bodies using such a system is described. When trying to predict, the relationship between each vehicle is diverse, and when providing the information on the predicted traffic situation to each vehicle, the information given to each vehicle is provided if it is provided without selecting the information obtained. The amount becomes enormous and is not preferable from the viewpoint of the load applied to the system.
 本開示はこのような事情に鑑みてなされたものであり、必要な情報を適切に情報提供することができる技術の提供を目的とする。 This disclosure has been made in view of such circumstances, and aims to provide a technology that can appropriately provide necessary information.
[本開示の効果]
 本開示によれば、必要な情報を適切に情報提供することができる。
[Effects of the present disclosure]
According to the present disclosure, necessary information can be appropriately provided.
 最初に実施形態の内容を列記して説明する。
[実施形態の概要]
(1)一実施形態である情報提供システムは、所定のエリア内に位置する1又は複数の移動体のうちの少なくとも一部に搭載された移動端末と、前記エリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算部と、前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定部と、前記判定部の判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知部と、を備えている。
First, the contents of the embodiment will be listed and described.
[Outline of Embodiment]
(1) An information providing system according to an embodiment includes a mobile terminal mounted on at least a part of one or a plurality of mobile objects located in a predetermined area, and the map information of the area including the 1 or Based on dynamic map information on which dynamic information on a plurality of moving objects is superimposed, a calculation unit that obtains an estimated value of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals, and each of the mobile terminals A determination unit that determines for each mobile terminal whether or not to notify the mobile terminal of the predicted traffic situation based on the evaluation value, and the mobile terminal based on the determination result of the determination unit A notification unit for notifying.
 上記構成によれば、予測交通状況を通知するか否かを、移動端末それぞれの予測交通状況の評価値に基づいて移動端末ごとに判定するので、必要な情報を適切に各移動端末へ情報提供することができる。
 また、移動端末それぞれの予測交通状況の評価値を求めるために、1又は複数の移動体に関する動的情報が重畳された動的マップ情報を用いるので、移動端末が搭載されていない移動体も含めて予測交通状況の評価値を得ることができ、各移動端末において、適切に予測された交通状況を評価値として表すことができる。
 このように、上記構成によれば、適切に予測された交通状況に関する情報を適切に各移動端末へ情報提供することができる。
According to the above configuration, whether to notify the predicted traffic situation is determined for each mobile terminal based on the estimated value of the predicted traffic situation of each mobile terminal, so that necessary information is appropriately provided to each mobile terminal can do.
In addition, since dynamic map information on which dynamic information related to one or a plurality of mobile objects is superimposed is used to obtain an evaluation value of the predicted traffic situation of each mobile terminal, including mobile objects that are not equipped with mobile terminals Thus, an estimated value of the predicted traffic situation can be obtained, and the appropriately predicted traffic situation can be expressed as an evaluation value in each mobile terminal.
Thus, according to the said structure, the information regarding the appropriately predicted traffic condition can be appropriately provided to each mobile terminal.
(2)上記情報提供システムにおいて、前記通知部は、前記移動端末のうち、前記判定部が通知すると判定した移動端末に対して、前記予測交通状況を通知することが好ましい。
 この場合、評価値に基づいて予測交通状況に関する情報が必要と判定された移動端末のみに情報提供することができる。
(2) In the information providing system, it is preferable that the notification unit notifies the predicted traffic situation to a mobile terminal determined to be notified by the determination unit among the mobile terminals.
In this case, it is possible to provide information only to mobile terminals that are determined to require information on the predicted traffic situation based on the evaluation value.
(3)また、上記情報提供システムにおいて、前記予測交通状況は、前記演算部により前記評価値が求められる移動端末を搭載した対象移動体と、前記1又は複数の移動体のうちの前記対象移動体以外の他の移動体との間の衝突予測の予測結果であり、前記演算部は、前記動的マップ情報に基づいて、前記移動端末それぞれについて前記衝突予測を行い、その予測結果に基づいて前記評価値を、前記移動端末それぞれの安全度を評価する値として求めることが好ましい。
 この場合、移動端末と移動体との衝突予測に基づいた安全度に関する評価値を得ることができる。
(3) Moreover, in the information providing system, the predicted traffic situation includes a target mobile unit equipped with a mobile terminal for which the evaluation value is calculated by the calculation unit, and the target mobile unit among the one or more mobile units. It is a prediction result of collision prediction with other mobile bodies other than the body, and the calculation unit performs the collision prediction for each of the mobile terminals based on the dynamic map information, and based on the prediction result The evaluation value is preferably obtained as a value for evaluating the safety level of each mobile terminal.
In this case, it is possible to obtain an evaluation value related to the safety degree based on the prediction of the collision between the mobile terminal and the mobile object.
(4)また、上記情報提供システムにおいて、前記演算部は、前記他の移動体のうち、前記対象移動体に対して衝突すると予測される移動体を、前記予測結果に基づいて特定し、前記衝突すると予測される移動体に関する前記予測結果に基づいて前記評価値を求めることが好ましい。
 この場合、衝突すると予測される移動体の衝突予測に基づいた安全度に関する評価値を得ることができる。
(4) Moreover, in the information providing system, the calculation unit identifies a moving body predicted to collide with the target moving body among the other moving bodies based on the prediction result, and It is preferable to obtain the evaluation value based on the prediction result related to the moving body predicted to collide.
In this case, it is possible to obtain an evaluation value related to the degree of safety based on the collision prediction of the moving body predicted to collide.
(5)上記情報提供システムにおいて、前記演算部は、前記対象移動体、及び、前記対象移動体に対して衝突すると予測される移動体のいずれか一方が歩行者である場合、前記歩行者の状況に応じた調整値を前記評価値に加味することが好ましい。
 この場合、歩行者特有の状況を、移動端末への情報提供の実行判定に反映することができる。
(5) In the information providing system, when the calculation unit is a pedestrian when one of the target moving body and the moving body predicted to collide with the target moving body is a pedestrian, It is preferable to add an adjustment value according to the situation to the evaluation value.
In this case, the situation unique to the pedestrian can be reflected in the execution determination of information provision to the mobile terminal.
(6)上記情報提供システムにおいて、前記演算部は、前記対象移動体と、前記対象移動体に対して衝突すると予測される移動体と、の間に死角を生じさせる死角要因の有無を判定し、前記死角要因の有無の判定結果を前記評価値に加味してもよい。
 この場合、死角要因の有無を、移動端末への情報提供の実行判定に反映させることができる。
(6) In the information providing system, the calculation unit determines whether or not there is a blind spot factor that causes a blind spot between the target moving body and a moving body that is predicted to collide with the target moving body. The determination result of the presence / absence of the blind spot factor may be added to the evaluation value.
In this case, the presence / absence of the blind spot factor can be reflected in the determination of execution of information provision to the mobile terminal.
(7)上記情報提供システムにおいて、前記予測交通状況を前記移動端末のユーザへ向けて出力させるように、前記移動端末を制御する制御部をさらに備え、前記制御部は、前記対象移動体に対して衝突すると予測される移動体の属性に応じて、前記予測交通状況の出力態様が異なるように制御するものであってもよい。
 この場合、衝突すると予測される移動体の属性それぞれの特徴に応じた出力態様でユーザに出力することができる。
(7) The information providing system further includes a control unit that controls the mobile terminal so that the predicted traffic situation is output to a user of the mobile terminal, and the control unit The output mode of the predicted traffic situation may be controlled to be different depending on the attribute of the moving body predicted to collide.
In this case, it can output to a user in the output mode according to the characteristic of each attribute of the moving body estimated to collide.
(8)また、上記情報提供システムにおいて、前記予測交通状況は、前記演算部により前記評価値が求められる移動端末の将来の移動が快適な移動であるか否かを示す情報であり、前記演算部は、前記動的マップ情報に基づいて、前記移動端末それぞれの将来の移動の快適性について評価し、前記移動端末それぞれの将来の移動の快適性に基づいて前記評価値を求めるものであってもよい。
 この場合、移動端末それぞれの快適性に関する評価値を得ることができる。
(8) Further, in the information providing system, the predicted traffic situation is information indicating whether or not a future movement of the mobile terminal for which the evaluation value is obtained by the calculation unit is a comfortable movement, and the calculation The unit evaluates the future mobility comfort of each of the mobile terminals based on the dynamic map information, and obtains the evaluation value based on the future mobility comfort of each of the mobile terminals. Also good.
In this case, an evaluation value regarding the comfort of each mobile terminal can be obtained.
(9)また、他の実施形態である移動端末は、上記(1)から(8)のいずれか1つの情報提供システムから前記予測交通状況を受け付け、ユーザへ前記予測交通状況を出力する移動端末である。 (9) Moreover, the mobile terminal which is other embodiment receives the said predicted traffic condition from any one information provision system of said (1) to (8), and outputs the said predicted traffic condition to a user It is.
(10)また、他の実施形態である情報提供方法は、移動端末へ情報提供を行う情報提供方法であって、1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算ステップと、前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定ステップと、前記判定部の判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知ステップと、を含む。 (10) In addition, an information providing method according to another embodiment is an information providing method for providing information to a mobile terminal. In the map information of an area where one or more mobile objects are located, the one or more information is provided. Based on dynamic map information on which dynamic information related to a moving body is superimposed, an evaluation of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals mounted on at least a part of the one or more mobile bodies A calculation step for obtaining a value, a determination step for determining whether or not to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals based on the evaluation value, and determination by the determination unit A notification step of notifying the mobile terminal of the predicted traffic situation based on the result.
(11)また、他の実施形態であるコンピュータプログラムは、移動端末へ情報提供を行う情報提供処理をコンピュータに実行させるためのコンピュータプログラムであって、前記コンピュータに1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算ステップと、前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定ステップと、前記判定部の判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知ステップと、を実行させるためのコンピュータプログラムである。 (11) A computer program according to another embodiment is a computer program for causing a computer to execute an information providing process for providing information to a mobile terminal, and one or a plurality of moving objects are located in the computer. The traffic of each of the mobile terminals mounted on at least a part of the one or more mobile objects based on the dynamic map information in which the dynamic information about the one or more mobile objects is superimposed on the map information of the area A calculation step for obtaining an evaluation value of a predicted traffic situation that is a prediction result of the situation, and whether or not to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals for each mobile terminal based on the evaluation value A determination step of determining, and a notification step of notifying the mobile terminal of the predicted traffic situation based on a determination result of the determination unit Is a computer program for causing.
(12)また、他の実施形態である情報提供装置は、1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算部と、前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定部と、を備えている。 (12) In addition, the information providing apparatus according to another embodiment includes dynamic map information in which dynamic information regarding the one or more moving objects is superimposed on map information of an area where the one or more moving objects are located. A computing unit that obtains an evaluation value of a predicted traffic situation that is a prediction result of a traffic situation of each of the mobile terminals mounted on at least a part of the one or more mobile objects, and the predicted traffic of each of the mobile terminals A determination unit that determines, for each mobile terminal, whether or not to notify the mobile terminal of a situation based on the evaluation value.
[実施形態の詳細]
 以下、好ましい実施形態について図面を参照しつつ説明する。
 なお、以下に記載する各実施形態の少なくとも一部を任意に組み合わせてもよい。
[Details of the embodiment]
Hereinafter, preferred embodiments will be described with reference to the drawings.
Note that at least a part of each embodiment described below may be arbitrarily combined.
〔無線通信システムの全体構成〕
 図1は、一実施形態にかかる無線通信システムの全体構成を示す概略図である。図1を参照して、無線通信システムは、無線通信が可能な複数の通信端末1A~1D、通信端末1A~1Dと無線通信する1または複数の基地局2、基地局2と有線又は無線で通信する1または複数のエッジサーバ3、および、エッジサーバ3と有線または無線で通信する1または複数のコアサーバ4を含む。通信端末1A~1Dを代表させて通信端末1とも称する。
[Overall configuration of wireless communication system]
FIG. 1 is a schematic diagram illustrating an overall configuration of a wireless communication system according to an embodiment. Referring to FIG. 1, a wireless communication system includes a plurality of communication terminals 1A to 1D capable of wireless communication, one or more base stations 2 that wirelessly communicate with communication terminals 1A to 1D, and wired or wirelessly to base station 2. It includes one or more edge servers 3 that communicate with each other and one or more core servers 4 that communicate with the edge servers 3 in a wired or wireless manner. Communication terminals 1A to 1D are also referred to as communication terminals 1 as representative.
 コアサーバ4は、コアネットワークのコアデータセンタ(DC)に設置される。エッジサーバ3は、メトロネットワークの分散データセンタ(DC)に設置される。メトロネットワークは、たとえば都市ごとに構築された通信ネットワークである。各地のメトロネットワークは、それぞれコアネットワークに接続される。基地局2は、メトロネットワークに含まれる分散データセンタのいずれかのエッジサーバ3に通信可能に接続される。 The core server 4 is installed in the core data center (DC) of the core network. The edge server 3 is installed in a distributed data center (DC) of a metro network. A metro network is a communication network constructed for each city, for example. Each metro network is connected to a core network. The base station 2 is communicably connected to any edge server 3 of the distributed data center included in the metro network.
 コアサーバ4は、コアネットワークに通信可能に接続される。エッジサーバ3は、メトロネットワークに通信可能に接続される。従って、コアサーバ4は、コアネットワークおよびメトロネットワークを介して、各地のメトロネットワークに属するエッジサーバ3および基地局2と通信可能である。基地局2は、マクロセル基地局、マイクロセル基地局、およびピコセル基地局のうちの少なくとも1つよりなる。 The core server 4 is communicably connected to the core network. The edge server 3 is communicably connected to the metro network. Therefore, the core server 4 can communicate with the edge server 3 and the base station 2 belonging to each metro network via the core network and the metro network. The base station 2 includes at least one of a macro cell base station, a micro cell base station, and a pico cell base station.
 本実施形態の無線通信システムにおいて、エッジサーバ3およびコアサーバ4は、SDN(Software-Defined Networking)が可能な汎用サーバである。基地局2および図示しないリピータなどの中継装置は、SDNが可能なトランスポート機器である。従って、ネットワーク仮想化技術により、低遅延通信と大容量通信などの相反するサービス要求条件を満足する複数の仮想的なネットワーク(ネットワークスライス)S1~S4を、無線通信システムの物理機器に定義できる。 In the wireless communication system of the present embodiment, the edge server 3 and the core server 4 are general-purpose servers capable of SDN (Software-Defined Networking). The base station 2 and a relay device such as a repeater (not shown) are transport devices capable of SDN. Therefore, a plurality of virtual networks (network slices) S1 to S4 satisfying conflicting service request conditions such as low-latency communication and large-capacity communication can be defined as physical devices of the wireless communication system by network virtualization technology.
 上記のネットワーク仮想化技術は、現時点で規格化が進行中の「第5世代移動通信システム」(以下、「5G」(5th Generation)と略記する。)の基本コンセプトである。従って、本実施形態にかかる無線通信システムは、たとえば5Gに準拠している。
 もっとも、本実施形態にかかる無線通信システムは、遅延時間などの所定のサービス要求条件に応じて複数のネットワークスライス(以下、「スライス」ともいう。)S1~S4を定義可能な移動通信システムであればよく、5Gに限定されるものではない。また、定義するスライスの階層は、4階層に限らず5階層以上であってもよい。
The above-mentioned network virtualization technology is a basic concept of “5th generation mobile communication system” (hereinafter abbreviated as “5G”), which is currently being standardized. Therefore, the wireless communication system according to the present embodiment is compliant with 5G, for example.
However, the radio communication system according to the present embodiment may be a mobile communication system capable of defining a plurality of network slices (hereinafter also referred to as “slices”) S1 to S4 according to predetermined service request conditions such as a delay time. What is necessary is just and it is not limited to 5G. Moreover, the hierarchy of slices to be defined is not limited to four, but may be five or more.
 図1の例では、各ネットワークスライスS1~S4は、次のように定義される。スライスS1は、通信端末1A~1Dが、直接通信するように定義されたネットワークスライスである。スライスS1で直接通信する通信端末1A~1Dを、「ノードN1」ともいう。 In the example of FIG. 1, each network slice S1 to S4 is defined as follows. The slice S1 is a network slice defined so that the communication terminals 1A to 1D communicate directly. The communication terminals 1A to 1D that directly communicate in the slice S1 are also referred to as “node N1”.
 スライスS2は、通信端末1A~1Dが、基地局2と通信するように定義されたネットワークスライスである。スライスS2における最上位の通信ノード(図例では基地局2)を、「ノードN2」ともいう。 The slice S2 is a network slice defined so that the communication terminals 1A to 1D communicate with the base station 2. The highest communication node in the slice S2 (base station 2 in the illustrated example) is also referred to as “node N2”.
 スライスS3は、通信端末1A~1Dが、基地局2を経由してエッジサーバ3と通信するように定義されたネットワークスライスである。スライスS3における最上位の通信ノード(図例ではエッジサーバ3)を、「ノードN3」ともいう。スライスS3では、ノードN2が中継ノードとなる。すなわち、ノードN1→ノードN2→ノードN3のアップリンク経路と、ノードN3→ノードN2→ノードN1のダウンリンク経路によりデータ通信が行われる。 The slice S3 is a network slice defined so that the communication terminals 1A to 1D communicate with the edge server 3 via the base station 2. The highest communication node (edge server 3 in the example) in the slice S3 is also referred to as “node N3”. In the slice S3, the node N2 becomes a relay node. That is, data communication is performed through an uplink path of node N1 → node N2 → node N3 and a downlink path of node N3 → node N2 → node N1.
 スライスS4は、通信端末1A~1Dが、基地局2およびエッジサーバ3を経由してコアサーバ4と通信するように定義されたネットワークスライスである。スライスS4における最上位の通信ノード(図例ではコアサーバ4)を、「ノードN4」ともいう。スライスS4では、ノードN2およびノードN3が中継ノードとなる。すなわち、ノードN1→ノードN2→ノードN3→ノードN4のアップリンク経路と、ノードN4→ノードN3→ノードN2→ノードN1のダウンリンク経路と、によりデータ通信が行われる。 The slice S4 is a network slice defined so that the communication terminals 1A to 1D communicate with the core server 4 via the base station 2 and the edge server 3. The highest communication node in the slice S4 (core server 4 in the figure) is also referred to as “node N4”. In the slice S4, the node N2 and the node N3 are relay nodes. That is, data communication is performed by the uplink path of node N1 → node N2 → node N3 → node N4 and the downlink path of node N4 → node N3 → node N2 → node N1.
 スライスS4において、エッジサーバ3を中継ノードとしないルーティングの場合もある。この場合、ノードN1→ノードN2→ノードN4のアップリンク経路と、ノードN4→ノードN2→ノードN1のダウンリンク経路と、によりデータ通信が行われる。 In the slice S4, there is a case where the routing does not use the edge server 3 as a relay node. In this case, data communication is performed through the uplink path of node N1 → node N2 → node N4 and the downlink path of node N4 → node N2 → node N1.
 スライスS2において、複数の基地局2(ノードN2)が含まれる場合は、基地局2,2間の通信を辿るルーティングも可能である。同様に、スライスS3において、複数のエッジサーバ3(ノードN3)が含まれる場合は、エッジサーバ3,3間の通信を辿るルーティングも可能である。スライスS4において、複数のコアサーバ4(ノードN4)が含まれる場合は、コアサーバ4,4の通信を辿るルーティングも可能である。 When a plurality of base stations 2 (node N2) are included in the slice S2, routing for tracing communication between the base stations 2 and 2 is also possible. Similarly, when a plurality of edge servers 3 (node N3) are included in the slice S3, routing for tracing communication between the edge servers 3 and 3 is also possible. When a plurality of core servers 4 (nodes N4) are included in the slice S4, routing that traces communication between the core servers 4 and 4 is also possible.
 通信端末1Aは、車両5に搭載された無線通信機である。車両5には、通常の乗用車だけでなく、路線バスや緊急車両などの公共車両も含まれる。車両5は、四輪車だけでなく、二輪車(バイク)であってもよい。車両5の駆動方式は、エンジン駆動、電気モータ駆動、およびハイブリッド方式のいずれでもよい。車両5の運転方式は、搭乗者が加減速やハンドル操舵などの操作を行う通常運転、およびその操作をソフトウェアが実行する自動運転のうちのいずれでもよい。 The communication terminal 1A is a wireless communication device mounted on the vehicle 5. The vehicles 5 include not only ordinary passenger cars but also public vehicles such as route buses and emergency vehicles. The vehicle 5 may be a two-wheeled vehicle (motorcycle) as well as a four-wheeled vehicle. The drive system of the vehicle 5 may be any of engine drive, electric motor drive, and hybrid system. The driving method of the vehicle 5 may be any of normal driving in which the passenger performs operations such as acceleration / deceleration and steering of the steering wheel, and automatic driving in which the operation is performed by software.
 車両5の通信端末1Aは、車両5に既設の無線通信機であってもよいし、搭乗者が車両5に持ち込んだ携帯端末であってもよい。搭乗者の携帯端末は、車両5の車内LAN(Local Area Network)に接続されることにより、一時的に車載の無線通信機となる。 The communication terminal 1 </ b> A of the vehicle 5 may be an existing wireless communication device in the vehicle 5, or may be a portable terminal brought into the vehicle 5 by a passenger. The passenger's mobile terminal is temporarily connected to the in-vehicle LAN (Local Area Network) of the vehicle 5 to become an in-vehicle wireless communication device.
 通信端末1Bは、歩行者7が携帯する携帯端末(歩行者端末)である。歩行者7は、道路や駐車場などの屋外、および建物内や地下街などの屋内を徒歩で移動する人間である。歩行者7には、徒歩だけでなく、動力源を有しない自転車などに搭乗する人間も含まれる。 The communication terminal 1B is a portable terminal (pedestrian terminal) carried by the pedestrian 7. The pedestrian 7 is a person who moves on foot such as outdoors on roads and parking lots and indoors such as in buildings and underground shopping streets. The pedestrian 7 includes not only a person walking but also a person who rides on a bicycle having no power source.
 通信端末1Cは、路側センサ8に搭載された無線通信機である。路側センサ8は、道路に設置された画像式車両感知器、および屋外または屋内に設置された防犯カメラなどである。通信端末1Dは、交差点の交通信号制御機9に搭載された無線通信機である。 The communication terminal 1 </ b> C is a wireless communication device mounted on the roadside sensor 8. The roadside sensor 8 is an image type vehicle detector installed on the road, a security camera installed outdoors or indoors, and the like. The communication terminal 1D is a wireless communication device mounted on the traffic signal controller 9 at the intersection.
 スライスS1~S4のサービス要求条件は、次の通りである。スライスS1~S4に許容される遅延時間D1~D4は、D1<D2<D3<D4となるように定義される。たとえば、D1=1ms、D2=10ms、D3=100ms、D4=1sである。スライスS1~S4に許容される所定期間(たとえば1日)当たりのデータ通信量C1~C4は、C1<C2<C3<C4となるように定義される。たとえば、C1=20GB、C2=100GB、C3=2TB、C4=10TBである。 The service request conditions for slices S1 to S4 are as follows. Delay times D1 to D4 allowed for the slices S1 to S4 are defined such that D1 <D2 <D3 <D4. For example, D1 = 1 ms, D2 = 10 ms, D3 = 100 ms, and D4 = 1 s. Data communication amounts C1 to C4 per predetermined period (for example, one day) allowed for the slices S1 to S4 are defined such that C1 <C2 <C3 <C4. For example, C1 = 20 GB, C2 = 100 GB, C3 = 2 TB, C4 = 10 TB.
 上記の通り、図1の無線通信システムでは、スライスS1での直接的な無線通信(たとえば、車両5の通信端末1Aが直接通信する「車車間通信」など)、および基地局2を経由するスライスS2の無線通信が可能である。もっとも、本実施形態では、図1の無線通信システムにおけるスライスS3およびスライスS4を利用した、比較的広域のサービスエリア(たとえば、市町村や都道府県を包含するエリア)に含まれるユーザに対する情報提供サービスが想定される。 As described above, in the wireless communication system of FIG. 1, direct wireless communication in the slice S1 (for example, “vehicle-to-vehicle communication” in which the communication terminal 1A of the vehicle 5 directly communicates) and the slice that passes through the base station 2 S2 wireless communication is possible. However, in this embodiment, there is an information providing service for users included in a relatively wide service area (for example, an area including a municipality or a prefecture) using the slice S3 and the slice S4 in the wireless communication system of FIG. is assumed.
〔エッジサーバおよびコアサーバの内部構成〕
 図2は、エッジサーバ3およびコアサーバ4の内部構成の一例を示すブロック図である。図2を参照して、エッジサーバ3は、CPU(Central Processing Unit)などを含む制御部31、ROM(Read Only Memory)32、RAM(Random Access Memory)33、記憶部34、および、通信部35を含む。
[Internal configuration of edge server and core server]
FIG. 2 is a block diagram illustrating an example of the internal configuration of the edge server 3 and the core server 4. Referring to FIG. 2, the edge server 3 includes a control unit 31 including a CPU (Central Processing Unit), a ROM (Read Only Memory) 32, a RAM (Random Access Memory) 33, a storage unit 34, and a communication unit 35. including.
 制御部31は、ROM32に予め記憶された1または複数のプログラムをRAM33に読み出して実行することにより、各ハードウェアの動作を制御し、コンピュータ装置をコアサーバ4や基地局2などと通信可能なエッジサーバ3として機能させる。 The control unit 31 reads one or more programs stored in advance in the ROM 32 into the RAM 33 and executes them, thereby controlling the operation of each hardware and communicating the computer device with the core server 4 or the base station 2. It functions as the edge server 3.
 RAM33は、SRAM(Static RAM)またはDRAM(Dynamic RAM)などの揮発性のメモリ素子で構成され、制御部31が実行するプログラムおよびその実行に必要なデータを一時的に記憶する。 The RAM 33 is composed of a volatile memory element such as SRAM (Static RAM) or DRAM (Dynamic RAM), and temporarily stores a program executed by the control unit 31 and data necessary for the execution.
 記憶部34は、フラッシュメモリもしくはEEPROM(Electrically Erasable Programmable Read Only Memory)などの不揮発性のメモリ素子、または、ハードディスクなどの磁気記憶装置などにより構成される。 The storage unit 34 includes a non-volatile memory element such as a flash memory or an EEPROM (Electrically Erasable Programmable Read Only Memory), or a magnetic storage device such as a hard disk.
 通信部35は、メトロネットワークを介してコアサーバ4や基地局2などと通信する機能を有している。通信部35は、制御部31から与えられた情報を、メトロネットワークを介して外部装置に送信するとともに、メトロネットワークを介して受信した情報を制御部31に与える。 The communication unit 35 has a function of communicating with the core server 4 and the base station 2 via the metro network. The communication unit 35 transmits the information given from the control unit 31 to the external device via the metro network and gives the information received via the metro network to the control unit 31.
 記憶部34は、動的なマップ情報として動的情報マップ(以下、単に「マップ」ともいう。)M1を記憶する。マップM1は、静的情報である高精細のデジタル地図に対して、時々刻々と変化する動的情報を重畳させたデータの集合体(仮想的なデータベース)である。
 マップM1を構成する情報には、下記の「動的情報」や「静的情報」が含まれる。
The storage unit 34 stores a dynamic information map (hereinafter also simply referred to as “map”) M1 as dynamic map information. The map M1 is an aggregate (virtual database) of data in which dynamic information that changes every moment is superimposed on a high-definition digital map that is static information.
The information constituting the map M1 includes the following “dynamic information” and “static information”.
 「動的情報」は、1秒以内の遅延時間が要求される動的なデータを指す。たとえば、ITS(Intelligent Transport Systems)先読み情報として活用される、移動体(車両および歩行者など)の位置情報、および信号情報などが動的情報に該当する。
 なお、動的情報に含まれる移動体の位置情報には、通信端末1A,1Bを有することで無線通信が可能な車両5や歩行者7の位置情報の他、無線通信機能を有していない車両5や歩行者7の位置情報も含まれている。
“Dynamic information” refers to dynamic data that requires a delay time of 1 second or less. For example, the position information and signal information of mobile bodies (such as vehicles and pedestrians) that are utilized as ITS (Intelligent Transport Systems) prefetch information correspond to dynamic information.
In addition, the position information of the moving body included in the dynamic information does not have a wireless communication function in addition to the position information of the vehicle 5 and the pedestrian 7 that can perform wireless communication by having the communication terminals 1A and 1B. Position information of the vehicle 5 and the pedestrian 7 is also included.
 「静的情報」は、1カ月以内の遅延時間が許容される静的なデータを指す。たとえば、路面情報、車線情報、および3次元構造物データなどが静的情報に該当する。 “Static information” refers to static data that allows a delay time of one month or less. For example, road surface information, lane information, and three-dimensional structure data correspond to static information.
 エッジサーバ3の制御部31は、記憶部34に格納されたマップM1の動的情報を、所定の更新周期ごとに更新する(更新処理)。具体的には、制御部31は、所定の更新周期ごとに、自装置のサービスエリア内で車両5や路側センサ8などによって取得された各種のセンサ情報を各通信端末1A~1Dから収集し、収集したセンサ情報に基づいてマップM1の動的情報を更新する。 The control unit 31 of the edge server 3 updates the dynamic information of the map M1 stored in the storage unit 34 every predetermined update cycle (update process). Specifically, the control unit 31 collects, from each communication terminal 1A to 1D, various sensor information acquired by the vehicle 5, the roadside sensor 8, and the like within the service area of its own device at every predetermined update period. The dynamic information of the map M1 is updated based on the collected sensor information.
 制御部31は、所定のユーザの通信端末1A,1Bから動的情報の要求メッセージを受信すると、所定の配信周期ごとに、最新の動的情報を要求メッセージの送信元の通信端末1A,1Bへ配信する(配信処理)。
 制御部31は、交通管制センターおよび民間気象業務支援センターなどからサービスエリア内の各地の交通情報および気象情報を収集し、収集した情報に基づいて、マップM1の動的情報または静的情報を更新してもよい。
When receiving the dynamic information request message from the communication terminal 1A, 1B of the predetermined user, the control unit 31 sends the latest dynamic information to the communication terminal 1A, 1B that is the transmission source of the request message for each predetermined distribution cycle. Distribute (distribution process).
The control unit 31 collects traffic information and weather information of each location in the service area from the traffic control center and the private weather service support center, and updates the dynamic information or static information of the map M1 based on the collected information. May be.
 さらに図2を参照して、コアサーバ4は、CPUなどを含む制御部41、ROM42、RAM43、記憶部44、および、通信部45を含む。 2, the core server 4 includes a control unit 41 including a CPU, a ROM 42, a RAM 43, a storage unit 44, and a communication unit 45.
 制御部41は、ROM32に予め記憶された1または複数のプログラムをRAM43に読み出して実行することにより、各ハードウェアの動作を制御し、コンピュータ装置をエッジサーバ3と通信可能なコアサーバ4として機能させる。 The control unit 41 reads one or more programs stored in advance in the ROM 32 into the RAM 43 and executes them to control the operation of each hardware and function as a core server 4 capable of communicating with the edge server 3. Let
 RAM43は、SRAMまたはDRAMなどの揮発性のメモリ素子で構成され、制御部41が実行するプログラムおよびその実行に必要なデータを一時的に記憶する。 The RAM 43 is composed of a volatile memory element such as SRAM or DRAM, and temporarily stores a program executed by the control unit 41 and data necessary for the execution.
 記憶部44は、フラッシュメモリもしくはEEPROMなどの不揮発性のメモリ素子、または、ハードディスクなどの磁気記憶装置などにより構成される。 The storage unit 44 is configured by a nonvolatile memory element such as a flash memory or an EEPROM, or a magnetic storage device such as a hard disk.
 通信部45は、コアネットワークを介してエッジサーバ3や基地局2などと通信する機能を有している。通信部45は、制御部41から与えられた情報を、コアネットワークを介して外部装置に送信するとともに、コアネットワークを介して受信した情報を制御部41に与える。 The communication unit 45 has a function of communicating with the edge server 3 and the base station 2 via the core network. The communication unit 45 transmits information given from the control unit 41 to the external device via the core network, and gives information received via the core network to the control unit 41.
 図2に示すように、コアサーバ4の記憶部44は情報マップM2を記憶する。マップM2のデータ構造(動的情報および静的情報を含むデータ構造)は、マップM1のデータ構造と同様である。マップM2は、特定のエッジサーバ3のマップM1と同じサービスエリアのマップでもよいし、複数のエッジサーバ3が保持する各マップM1を統合した、より広域のマップであってもよい。 As shown in FIG. 2, the storage unit 44 of the core server 4 stores an information map M2. The data structure of the map M2 (data structure including dynamic information and static information) is the same as the data structure of the map M1. The map M2 may be a map of the same service area as the map M1 of the specific edge server 3, or may be a wider area map in which the maps M1 held by the plurality of edge servers 3 are integrated.
 コアサーバ4の制御部41は、エッジサーバ3と同様に、記憶部44に格納されたマップM2の動的情報を更新する更新処理と、要求メッセージに応答して動的情報を配信する配信処理と、を行ってもよい。すなわち、制御部41は、エッジサーバ3から独立して、自装置のマップM2に基づく更新処理および配信処理を行うことができる。
 すなわち、制御部41は、エッジサーバ3とは別に、自装置のマップM2に基づく動的情報の更新処理及び配信処理を独自に実行可能である。
Similar to the edge server 3, the control unit 41 of the core server 4 updates the dynamic information of the map M2 stored in the storage unit 44, and the distribution process of distributing the dynamic information in response to the request message. And may be performed. That is, the control unit 41 can perform update processing and distribution processing based on the map M2 of the own device independently of the edge server 3.
That is, the control unit 41 can independently execute dynamic information update processing and distribution processing based on the map M2 of its own device separately from the edge server 3.
 もっとも、スライスS4に属するコアサーバ4は、スライスS3に属するエッジサーバ3に比べて、通信端末1A~1Dとの通信の遅延時間が大きい。
 このため、コアサーバ4がマップM2の動的情報を独自に更新しても、エッジサーバ3が管理するマップM1の動的情報に比べてリアルタイム性に劣る。
 そこで、例えば所定のエリアごとに定義した優先度に応じて、エッジサーバ3の制御部31とコアサーバ4の制御部41が動的情報の更新処理及び配信処理を分散的に処理することが好ましい。
However, the core server 4 belonging to the slice S4 has a longer communication delay time with the communication terminals 1A to 1D than the edge server 3 belonging to the slice S3.
For this reason, even if the core server 4 independently updates the dynamic information of the map M2, it is inferior in real time as compared to the dynamic information of the map M1 managed by the edge server 3.
Therefore, for example, it is preferable that the control unit 31 of the edge server 3 and the control unit 41 of the core server 4 perform dynamic information update processing and distribution processing in a distributed manner according to the priority defined for each predetermined area. .
〔車載装置の内部構成〕
 図3は、通信端末1Aを搭載した車両5の車載装置50の内部構成の一例を示すブロック図である。
 図3を参照して、車両5に搭載される車載装置50は、制御部(ECU:Electronic Control Unit)51、GPS受信機52、車速センサ53、ジャイロセンサ54、記憶部55、ディスプレイ56、スピーカ57、入力デバイス58、車載カメラ59、レーダセンサ60、および、通信部61を含む。
[Internal configuration of in-vehicle device]
FIG. 3 is a block diagram illustrating an example of an internal configuration of the in-vehicle device 50 of the vehicle 5 on which the communication terminal 1A is mounted.
Referring to FIG. 3, an in-vehicle device 50 mounted on a vehicle 5 includes a control unit (ECU: Electronic Control Unit) 51, a GPS receiver 52, a vehicle speed sensor 53, a gyro sensor 54, a storage unit 55, a display 56, a speaker. 57, an input device 58, an in-vehicle camera 59, a radar sensor 60, and a communication unit 61.
 通信部61は、前述の通信端末1A(5Gに準拠した通信が可能な無線通信機)である。従って、車両5の車載装置50は、スライスS3に属する移動端末の一種として、エッジサーバ3と通信することができる。また、車両5の車載装置50は、スライスS4に属する移動端末の一種として、コアサーバ4と通信することもできる。 The communication unit 61 is the communication terminal 1A described above (a wireless communication device capable of communication conforming to 5G). Therefore, the in-vehicle device 50 of the vehicle 5 can communicate with the edge server 3 as a kind of mobile terminal belonging to the slice S3. The in-vehicle device 50 of the vehicle 5 can also communicate with the core server 4 as a kind of mobile terminal belonging to the slice S4.
 制御部51は、車両5の経路探索および他の電子機器52~61の制御などを行うコンピュータ装置である。制御部51は、GPS受信機52が定期的に取得するGPS信号により自車両の車両位置を求める。また、制御部51は、車速センサ53およびジャイロセンサ54の入力信号に基づいて、車両位置および方位を補完し、車両5の正確な現在位置および方位を把握する。 The control unit 51 is a computer device that performs route search of the vehicle 5, control of the other electronic devices 52 to 61, and the like. The control unit 51 obtains the vehicle position of the host vehicle from GPS signals that the GPS receiver 52 periodically acquires. Further, the control unit 51 complements the vehicle position and direction based on the input signals of the vehicle speed sensor 53 and the gyro sensor 54, and grasps the accurate current position and direction of the vehicle 5.
 GPS受信機52、車速センサ53およびジャイロセンサ54は、車両5の現在位置、速度および向きを計測するセンサ類である。
 記憶部55は、地図データベースを含む。地図データベースは、制御部51に道路地図データを提供する。道路地図データは、リンクデータやノードデータを含み、DVD、CD-ROM、メモリカード、またはHDDなどの記録媒体に格納されている。記憶部55は、記録媒体から必要な道路地図データを読み出して制御部51に提供する。
The GPS receiver 52, the vehicle speed sensor 53, and the gyro sensor 54 are sensors that measure the current position, speed, and direction of the vehicle 5.
The storage unit 55 includes a map database. The map database provides road map data to the control unit 51. The road map data includes link data and node data, and is stored in a recording medium such as a DVD, a CD-ROM, a memory card, or an HDD. The storage unit 55 reads out necessary road map data from the recording medium and provides it to the control unit 51.
 ディスプレイ56およびスピーカ57は、制御部51が生成した各種情報を車両5の搭乗者であるユーザに通知するための出力装置である。具体的には、ディスプレイ56は、経路探索の際の入力画面、自車周辺の地図画像および目的地までの経路情報などを表示する。スピーカ57は、車両5を目的地に誘導するためのアナウンスなどを音声出力する。これらの出力装置は、通信部61が受信した提供情報を搭乗者に通知することもできる。 The display 56 and the speaker 57 are output devices for notifying a user who is a passenger of the vehicle 5 of various information generated by the control unit 51. Specifically, the display 56 displays an input screen for route search, a map image around the host vehicle, route information to the destination, and the like. The speaker 57 outputs an announcement or the like for guiding the vehicle 5 to the destination. These output devices can also notify the passenger of the provision information received by the communication unit 61.
 入力デバイス58は、車両5の搭乗者が各種の入力操作を行うためデバイスである。入力デバイス58は、ハンドルに設けた操作スイッチ、ジョイスティックディスプレイ56に設けたタッチパネル、およびこれらの組合せなどである。入力デバイス58は、搭乗者の音声認識によって入力を受け付ける音声認識装置であってもよい。入力デバイス58が生成した入力信号は、制御部51に送信される。 The input device 58 is a device for a passenger of the vehicle 5 to perform various input operations. The input device 58 includes an operation switch provided on the handle, a touch panel provided on the joystick display 56, and a combination thereof. The input device 58 may be a voice recognition device that accepts input by voice recognition of a passenger. The input signal generated by the input device 58 is transmitted to the control unit 51.
 車載カメラ59は、車両5の前方の映像を取り込む画像センサである。車載カメラ59は、単眼または複眼のいずれでもよい。レーダセンサ60は、ミリ波レーダやLiDAR方式などにより車両5の前方や周囲に存在する物体を検出するセンサである。
 制御部51は、車載カメラ59およびレーダセンサ60による計測データに基づいて、運転中の搭乗者に対する注意喚起をディスプレイ56に出力させたり、強制的なブレーキ介入を行ったりする運転支援制御を実行することができる。
The in-vehicle camera 59 is an image sensor that captures an image in front of the vehicle 5. The in-vehicle camera 59 may be either monocular or compound eye. The radar sensor 60 is a sensor that detects an object existing in front of or around the vehicle 5 by a millimeter wave radar, a LiDAR method, or the like.
Based on the measurement data from the in-vehicle camera 59 and the radar sensor 60, the control unit 51 executes driving support control that outputs a warning to the occupant during driving to the display 56 or performs forced braking intervention. be able to.
 制御部51は、記憶部55に格納された各種の制御プログラムを実行する、マイクロコンピュータなどの演算処理装置により構成される。
 制御部51は、上記制御プログラムを実行することにより実現される機能として、ディスプレイ56に地図画像を表示させる機能、出発地から目的地までの経路(中継地がある場合はその位置を含む。)を算出する機能、および、算出した経路に従って車両5を目的地まで誘導する機能など、各種のナビゲーション機能を有する。
The control unit 51 is configured by an arithmetic processing device such as a microcomputer that executes various control programs stored in the storage unit 55.
As a function realized by executing the control program, the control unit 51 displays a map image on the display 56, a route from the departure point to the destination (including the position if there is a relay point). And various navigation functions such as a function of guiding the vehicle 5 to the destination according to the calculated route.
 制御部51は、車載カメラ59およびレーダセンサ60のうちの少なくとも1つの計測データに基づいて、自車両の前方または周囲の物体を認識する物体認識処理と、認識した物体までの距離を算出する測距処理とを実行する機能を有する。
 制御部51は、測距処理により算出した距離と、自車両のセンサ位置とから、物体認識処理によって認識した物体の位置情報を算出できる。
Based on the measurement data of at least one of the in-vehicle camera 59 and the radar sensor 60, the control unit 51 performs object recognition processing for recognizing an object in front of or around the host vehicle, and measurement for calculating a distance to the recognized object. And a function of executing distance processing.
The control unit 51 can calculate the position information of the object recognized by the object recognition process from the distance calculated by the distance measurement process and the sensor position of the host vehicle.
 制御部51は、エッジサーバ3(コアサーバ4であってもよい。)との通信において、以下の各処理を実行可能である。
  1)要求メッセージの送信処理
  2)動的情報の受信処理
  3)変化点情報の生成処理
  4)変化点情報の送信処理
The control unit 51 can execute the following processes in communication with the edge server 3 (which may be the core server 4).
1) Request message transmission processing 2) Dynamic information reception processing 3) Change point information generation processing 4) Change point information transmission processing
 要求メッセージの送信処理は、エッジサーバ3が逐次更新するマップM1の動的情報の配信を要求する制御パケットを、エッジサーバ3に送信する処理である。当該制御パケットは、自車両の車両IDを含む。
 エッジサーバ3は、所定の車両IDを含む要求メッセージを受信すると、送信元の車両IDを有する車両5の通信端末1A宛てに、動的情報を所定の配信周期で配信する。
The request message transmission process is a process of transmitting, to the edge server 3, a control packet for requesting distribution of dynamic information of the map M1 that is sequentially updated by the edge server 3. The control packet includes the vehicle ID of the host vehicle.
When the edge server 3 receives the request message including the predetermined vehicle ID, the edge server 3 distributes the dynamic information to the communication terminal 1A of the vehicle 5 having the transmission source vehicle ID at a predetermined distribution cycle.
 動的情報の受信処理は、自装置に宛ててエッジサーバ3が配信した動的情報を受信する処理である。
 制御部51による変化点情報の生成処理は、受信した動的情報と、受信時点における自車両のセンサ情報との比較結果から、それらの情報間の変化を算出し、両情報間の差分に関する情報である変化点情報を生成する処理である。
 制御部51が生成する変化点情報は、たとえば、次の情報例a1~a2である。
The dynamic information receiving process is a process of receiving the dynamic information distributed by the edge server 3 to the own apparatus.
The change point information generation process by the control unit 51 calculates the change between the information from the comparison result between the received dynamic information and the sensor information of the host vehicle at the time of reception, and information on the difference between the two pieces of information. This is a process for generating change point information.
The change point information generated by the control unit 51 is, for example, the following information examples a1 to a2.
 情報例a1:認識物体に関する変化点情報
 制御部51は、受信した動的情報には含まれない物体X(車両、歩行者等の移動体および障害物など)を、自身の物体認識処理により検出した場合は、検出した物体Xの画像データと位置情報とを変化点情報とする。制御部51は、受信した動的情報に含まれる物体Xの位置情報と、自身の物体認識処理により求めた物体Xの位置情報とが、所定の閾値以上ずれている場合は、検出した物体Xの画像データと、両者の位置情報の差分値とを変化点情報とする。
Information example a1: Change point information regarding a recognized object The control unit 51 detects an object X (a moving object such as a vehicle or a pedestrian and an obstacle) that is not included in the received dynamic information by its own object recognition processing. In such a case, the detected image data of the object X and the position information are used as change point information. When the position information of the object X included in the received dynamic information and the position information of the object X obtained by its own object recognition process are shifted by a predetermined threshold or more, the control unit 51 detects the detected object X And the difference value between the position information of the two are used as change point information.
 情報例a2:自車両に関する変化点情報
 制御部51は、受信した動的情報に含まれる自車両の位置情報と、GPS信号により自身が算出した自車両の車両位置とが、所定の閾値以上ずれている場合は、両者の差分値を変化点情報とする。制御部51は、受信した動的情報に含まれる自車両の方位と、ジャイロセンサ54の計測データから自身が算出した自車両の方位とが、所定の閾値以上ずれている場合は、両者の差分値を変化点情報とする。
Information example a2: Change point information regarding own vehicle The control unit 51 deviates the position information of the own vehicle included in the received dynamic information from the vehicle position of the own vehicle calculated by the GPS signal by a predetermined threshold or more. If they are different, the difference value between them is used as change point information. When the direction of the own vehicle included in the received dynamic information and the direction of the own vehicle calculated from the measurement data of the gyro sensor 54 are different from each other by a predetermined threshold or more, the control unit 51 determines the difference between the two. The value is used as change point information.
 制御部51は、上記のようにして変化点情報を生成すると、生成した変化点情報と、自車両の車両IDとを含むエッジサーバ3宛の通信パケットを生成する。
 変化点情報の送信処理は、変化点情報を含む上記の通信パケットを、エッジサーバ3宛てに送信する処理である。変化点情報の送信処理は、エッジサーバ3による動的情報の配信周期内に行われる。
When the change point information is generated as described above, the control unit 51 generates a communication packet addressed to the edge server 3 including the generated change point information and the vehicle ID of the host vehicle.
The change point information transmission process is a process of transmitting the communication packet including the change point information to the edge server 3. The change point information transmission process is performed within the dynamic information distribution cycle by the edge server 3.
 制御部51は、エッジサーバ3などから受信した動的情報に基づいて、運転中の搭乗者に対する注意喚起をディスプレイ56に出力させたり、強制的なブレーキ介入を行ったりする運転支援制御を実行することもできる。 Based on the dynamic information received from the edge server 3 or the like, the control unit 51 executes driving support control that causes the display 56 to output a warning for a driver who is driving or to perform forced braking intervention. You can also.
〔歩行者端末の内部構成〕
 図4は、歩行者端末70(通信端末1B)の内部構成の一例を示すブロック図である。
 図4の歩行者端末70は、たとえば5Gに準拠した通信処理が可能な無線通信機である。従って、歩行者端末70は、スライスS3に属する移動端末の一種として、エッジサーバ3と通信することができる。また、歩行者端末70は、スライスS4に属する移動端末の一種として、コアサーバ4と通信することもできる。
[Internal configuration of pedestrian terminal]
FIG. 4 is a block diagram illustrating an example of an internal configuration of the pedestrian terminal 70 (communication terminal 1B).
The pedestrian terminal 70 in FIG. 4 is a wireless communication device capable of communication processing based on 5G, for example. Therefore, the pedestrian terminal 70 can communicate with the edge server 3 as a kind of mobile terminal belonging to the slice S3. The pedestrian terminal 70 can also communicate with the core server 4 as a kind of mobile terminal belonging to the slice S4.
 図4を参照して、歩行者端末70は、制御部71、記憶部72、表示部73、操作部74、および、通信部75を含む。 Referring to FIG. 4, pedestrian terminal 70 includes a control unit 71, a storage unit 72, a display unit 73, an operation unit 74, and a communication unit 75.
 通信部75は、5Gサービスを提供するキャリアの基地局2と無線通信する通信インターフェースである。通信部75は、基地局2からのRF信号をデジタル信号に変換して制御部71に出力する。また、通信部75は、制御部71から入力されたデジタル信号をRF信号に変換して、基地局2に送信する。 The communication unit 75 is a communication interface that wirelessly communicates with the base station 2 of the carrier that provides the 5G service. The communication unit 75 converts the RF signal from the base station 2 into a digital signal and outputs it to the control unit 71. Further, the communication unit 75 converts the digital signal input from the control unit 71 into an RF signal and transmits the RF signal to the base station 2.
 制御部71は、CPU、ROMおよびRAMを含む。制御部71は、記憶部72に記憶されたプログラムを読み出して実行し、歩行者端末70の全体の動作を制御する。 The control unit 71 includes a CPU, a ROM, and a RAM. The control unit 71 reads out and executes the program stored in the storage unit 72 and controls the overall operation of the pedestrian terminal 70.
 記憶部72は、ハードディスクや不揮発性のメモリなどより構成され、各種のコンピュータプログラムやデータを記憶する。また、記憶部72は、歩行者端末70の識別情報である携帯IDを記憶する。携帯IDは、たとえば、キャリア契約者の固有のユーザIDやMACアドレスなどである。 The storage unit 72 is configured by a hard disk, a non-volatile memory, or the like, and stores various computer programs and data. In addition, the storage unit 72 stores a mobile ID that is identification information of the pedestrian terminal 70. The mobile ID is, for example, a unique user ID or MAC address of the carrier contractor.
 さらに、記憶部72は、ユーザが任意にインストールした各種のアプリケーションソフトを記憶している。記憶部72が記憶するアプリケーションソフトは、例えば、エッジサーバ3(コアサーバ4でもよい。)との通信により、マップM1の動的情報などを受信する情報提供サービスを享受するためのアプリケーションソフトを含む。 Furthermore, the storage unit 72 stores various application software arbitrarily installed by the user. The application software stored in the storage unit 72 includes, for example, application software for receiving an information providing service for receiving dynamic information of the map M1 through communication with the edge server 3 (or the core server 4). .
 操作部74は、各種の操作ボタンや表示部73のタッチパネル機能により構成される。操作部74は、ユーザの操作に応じた操作信号を制御部71に出力する。 The operation unit 74 includes various operation buttons and a touch panel function of the display unit 73. The operation unit 74 outputs an operation signal corresponding to a user operation to the control unit 71.
 表示部73は、たとえば液晶ディスプレイである。表示部73は、各種の情報をユーザに提示する。たとえば、表示部73は、サーバ3,4から送信された情報マップM1,M2の画像データなどを画面表示する。 The display unit 73 is, for example, a liquid crystal display. The display unit 73 presents various information to the user. For example, the display unit 73 displays the image data of the information maps M1 and M2 transmitted from the servers 3 and 4 on the screen.
 制御部71は、GPS信号から現在時刻を取得する時刻同期機能と、GPS信号から自車両の現在位置(緯度、経度及び高度)を計測する位置検出機能と、方位センサによって歩行者7の向きを計測する方位検出機能と、をさらに有する。 The control unit 71 uses the time synchronization function to acquire the current time from the GPS signal, the position detection function to measure the current position (latitude, longitude, and altitude) of the host vehicle from the GPS signal, and the direction sensor to determine the direction of the pedestrian 7. And a direction detection function for measuring.
 制御部71は、エッジサーバ3(コアサーバ4であってもよい。)との通信において、以下の各処理を実行可能である。
  1)要求メッセージの送信処理
  2)動的情報の受信処理
  3)変化点情報の生成処理
  4)変化点情報の送信処理
The control unit 71 can execute the following processes in communication with the edge server 3 (which may be the core server 4).
1) Request message transmission processing 2) Dynamic information reception processing 3) Change point information generation processing 4) Change point information transmission processing
 要求メッセージの送信処理は、エッジサーバ3が逐次更新するマップM1の動的情報の配信を要求する制御パケットを、エッジサーバ3に送信する処理である。当該制御パケットは、歩行者端末70の携帯IDを含む。
 エッジサーバ3は、所定の携帯IDを含む要求メッセージを受信すると、送信元の携帯IDを有する歩行者7の通信端末1B宛てに、動的情報を所定の配信周期で配信する。
The request message transmission process is a process of transmitting, to the edge server 3, a control packet for requesting distribution of dynamic information of the map M1 that is sequentially updated by the edge server 3. The control packet includes the mobile ID of the pedestrian terminal 70.
When the edge server 3 receives the request message including the predetermined portable ID, the edge server 3 distributes the dynamic information to the communication terminal 1B of the pedestrian 7 having the transmission source portable ID at a predetermined distribution cycle.
 動的情報の受信処理は、自装置に宛ててエッジサーバ3が配信した動的情報を受信する処理である。
 制御部71による変化点情報の生成処理は、受信した動的情報と、受信時点における自車両のセンサ情報との比較結果から、それらの情報間の変化を算出し、両情報間の差分に関する情報である変化点情報を生成する処理である。
 制御部71が生成する変化点情報は、たとえば、次の情報例である。
The dynamic information receiving process is a process of receiving the dynamic information distributed by the edge server 3 to the own apparatus.
The change point information generation process by the control unit 71 calculates the change between the received dynamic information and the sensor information of the host vehicle at the time of reception, and information on the difference between the two pieces of information. This is a process for generating change point information.
The change point information generated by the control unit 71 is, for example, the following information example.
 情報例:自車両に関する変化点情報
 制御部71は、受信した動的情報に含まれる自歩行者7の位置情報と、GPS信号により自身が算出した自歩行者7の位置とが、所定の閾値以上ずれている場合は、両者の差分値を変化点情報とする。制御部71は、受信した動的情報に含まれる自歩行者7の方位と、方位センサによって算出した自歩行者7の方位とが、所定の閾値以上ずれている場合は、両者の差分値を変化点情報とする。
Information example: Change point information regarding own vehicle The control unit 71 has a predetermined threshold value based on the position information of the own pedestrian 7 included in the received dynamic information and the position of the own pedestrian 7 calculated by the GPS signal. When there is a deviation, the difference value between the two is used as change point information. When the azimuth of the pedestrian 7 included in the received dynamic information and the azimuth of the pedestrian 7 calculated by the azimuth sensor are deviated by a predetermined threshold or more, the control unit 71 sets a difference value between the two. Change point information.
 制御部71は、上記のようにして変化点情報を生成すると、生成した変化点情報と、自端末70の携帯IDとを含むエッジサーバ3宛の通信パケットを生成する。
 変化点情報の送信処理は、変化点情報を含む上記の通信パケットを、エッジサーバ3宛てに送信する処理である。変化点情報の送信処理は、エッジサーバ3による動的情報の配信周期内に行われる。
When generating the change point information as described above, the control unit 71 generates a communication packet addressed to the edge server 3 including the generated change point information and the portable ID of the terminal 70 itself.
The change point information transmission process is a process of transmitting the communication packet including the change point information to the edge server 3. The change point information transmission process is performed within the dynamic information distribution cycle by the edge server 3.
 以上のように、制御部71は、変化点情報の生成処理及び変化点情報の送信処理を行うことで、自端末70の位置及び方位情報などを含む状態情報を、エッジサーバ3へ送信する。 As described above, the control unit 71 transmits the state information including the position and orientation information of the terminal 70 to the edge server 3 by performing the change point information generation process and the change point information transmission process.
〔路側センサの内部構成〕
 図5は、通信端末1Cである無線通信機を搭載した路側センサ8の内部構成の一例を示すブロック図である。図5を参照して、路側センサ8は、制御部81、記憶部82、路側カメラ83、レーダセンサ84、および、通信部85を含む。
[Internal configuration of roadside sensor]
FIG. 5 is a block diagram showing an example of the internal configuration of the roadside sensor 8 equipped with a wireless communication device that is the communication terminal 1C. Referring to FIG. 5, roadside sensor 8 includes a control unit 81, a storage unit 82, a roadside camera 83, a radar sensor 84, and a communication unit 85.
 通信部85は、前述の通信端末1C、すなわち、たとえば5Gに準拠した通信処理が可能な無線通信機である。従って、路側センサ8は、スライスS3に属する固定端末の一種として、エッジサーバ3と通信することができる。また、路側センサ8は、スライスS4に属する固定端末の一種として、コアサーバ4と通信することもできる。 The communication unit 85 is the above-described communication terminal 1C, that is, a wireless communication device capable of communication processing based on, for example, 5G. Therefore, the roadside sensor 8 can communicate with the edge server 3 as a kind of fixed terminal belonging to the slice S3. The roadside sensor 8 can also communicate with the core server 4 as a kind of fixed terminal belonging to the slice S4.
 制御部81は、CPU、ROMおよびRAMを含む。制御部81は、記憶部82に記憶されたプログラムを読み出して実行し、路側センサ8の全体の動作を制御する。 The control unit 81 includes a CPU, a ROM, and a RAM. The control unit 81 reads and executes the program stored in the storage unit 82 and controls the overall operation of the roadside sensor 8.
 記憶部82は、ハードディスクや不揮発性のメモリなどより構成され、各種のコンピュータプログラムやデータを記憶する。また、記憶部82は、路側センサ8の識別情報であるセンサIDを記憶する。センサIDは、たとえば、路側センサ8の所有者固有のユーザIDやMACアドレスなどである。 The storage unit 82 is configured by a hard disk, a non-volatile memory, or the like, and stores various computer programs and data. The storage unit 82 stores a sensor ID that is identification information of the roadside sensor 8. The sensor ID is, for example, a user ID unique to the owner of the roadside sensor 8 or a MAC address.
 路側カメラ83は、所定の撮影エリアの映像を取り込む画像センサである。路側カメラ83は、単眼または複眼のいずれでもよい。レーダセンサ60は、ミリ波レーダやLiDAR方式などにより車両5の前方や周囲に存在する物体を検出するセンサである。 The roadside camera 83 is an image sensor that captures an image of a predetermined shooting area. The roadside camera 83 may be either monocular or compound eye. The radar sensor 60 is a sensor that detects an object existing in front of or around the vehicle 5 by a millimeter wave radar, a LiDAR method, or the like.
 路側センサ8が防犯カメラである場合、制御部81は、取り込んだ映像データなどを防犯管理者のコンピュータ装置に送信する。路側センサ8が画像式車両感知器である場合、制御部81は、取り込んだ映像データなどを交通管制センターに送信する。 When the roadside sensor 8 is a security camera, the control unit 81 transmits the captured video data and the like to the security administrator's computer device. When the roadside sensor 8 is an image type vehicle detector, the control unit 81 transmits the captured video data and the like to the traffic control center.
 制御部81は、路側カメラ83およびレーダセンサ84のうちの少なくとも1つの計測データに基づいて、撮影エリア内の物体を認識する物体認識処理と、認識した物体までの距離を算出する測距処理と、を実行する機能を有する。制御部51は、測距処理により算出した距離と、自車両のセンサ位置とから、物体認識処理によって認識した物体の位置情報を算出できる。 The control unit 81 performs object recognition processing for recognizing an object in the shooting area based on at least one measurement data of the roadside camera 83 and the radar sensor 84, and distance measurement processing for calculating a distance to the recognized object. , Has a function of executing. The control unit 51 can calculate the position information of the object recognized by the object recognition process from the distance calculated by the distance measurement process and the sensor position of the host vehicle.
 制御部81は、エッジサーバ3(コアサーバ4であってもよい。)との通信において、以下の各処理を実行可能である。
  1)変化点情報の生成処理
  2)変化点情報の送信処理
The control unit 81 can execute the following processes in communication with the edge server 3 (which may be the core server 4).
1) Change point information generation process 2) Change point information transmission process
 路側センサ8における変化点情報の生成処理は、所定の計測周期(たとえば、エッジサーバ3による動的情報の配信周期)ごとの、前回のセンサ情報と今回のセンサ情報との比較結果から、それらのセンサ情報間の変化を算出し、両情報間の差分に関する情報である変化点情報を生成する処理である。
 路側センサ8が生成する変化点情報は、たとえば、次の情報例b1である。
The change point information generation processing in the roadside sensor 8 is based on the comparison result between the previous sensor information and the current sensor information for each predetermined measurement cycle (for example, the dynamic information distribution cycle by the edge server 3). This is a process of calculating changes between sensor information and generating change point information that is information relating to differences between the two pieces of information.
The change point information generated by the roadside sensor 8 is, for example, the following information example b1.
 情報例b1:認識物体に関する変化点情報
 制御部81は、前回の物体認識処理では検出されなかった物体Y(車両、歩行者等の移動体及び障害物など)を、今回の物体認識処理により検出した場合は、検出した物体Yの画像データと位置情報を変化点情報とする。
 制御部81は、前回の物体認識処理により求めた物体Yの位置情報と、今回の物体認識処理により求めた物体Yの位置情報とが、所定の閾値以上ずれている場合は、検出した物体Yの位置情報と、両者の差分値とを変化点情報とする。
Information example b1: Change point information regarding a recognized object The control unit 81 detects an object Y (a moving object such as a vehicle or a pedestrian and an obstacle) that has not been detected in the previous object recognition process by the current object recognition process. In such a case, the detected image data of the object Y and the position information are used as change point information.
When the position information of the object Y obtained by the previous object recognition process and the position information of the object Y obtained by the current object recognition process are shifted by a predetermined threshold value or more, the control unit 81 detects the detected object Y. And the difference value between them are used as change point information.
 制御部81は、上記のようにして変化点情報を生成すると、生成した変化点情報と、自装置のセンサIDとを含むエッジサーバ3宛の通信パケットを生成する。
 変化点情報の送信処理は、変化点情報をデータに含む上記の通信パケットを、エッジサーバ3宛てに送信する処理である。変化点情報の送信処理は、エッジサーバ3による動的情報の配信周期内に行われる。
When generating the change point information as described above, the control unit 81 generates a communication packet addressed to the edge server 3 including the generated change point information and the sensor ID of the own device.
The change point information transmission process is a process of transmitting the communication packet including the change point information in the data to the edge server 3. The change point information transmission process is performed within the dynamic information distribution cycle by the edge server 3.
〔情報提供システムの全体構成〕
 図6は、本実施形態にかかる情報提供システムの全体構成図である。
 図6を参照して、本実施形態にかかる情報提供システムは、比較的広範囲であるエッジサーバ3のサービスエリア(リアルワールド)に散在する多数の車両5、歩行者端末70、および路側センサ8と、これらの通信ノードと基地局2を介して行われる5Gに準拠した通信などにより低遅延での無線通信が可能であって、情報提供装置として機能するエッジサーバ3と、を含む。つまり、情報提供システムは、上述の無線通信システムの一部又は全部を含んで構成される。
 なお、エッジサーバ3のサービスエリアに存在する移動体には、通信端末1Aや車載装置50が搭載されることで無線通信が可能な車両5や、歩行者端末70を携帯する歩行者7の他、無線通信機能を有していない車両5、歩行者端末70を携帯しない歩行者7も含まれている。
[Overall configuration of information provision system]
FIG. 6 is an overall configuration diagram of the information providing system according to the present embodiment.
Referring to FIG. 6, the information providing system according to the present embodiment includes a large number of vehicles 5, pedestrian terminals 70, and roadside sensors 8 scattered in a service area (real world) of edge server 3 that is relatively wide. In addition, these communication nodes include an edge server 3 that can perform wireless communication with low delay by communication based on 5G performed via the base station 2 and functions as an information providing apparatus. That is, the information providing system includes a part or all of the above-described wireless communication system.
In addition, the mobile body existing in the service area of the edge server 3 includes the vehicle 5 capable of wireless communication by mounting the communication terminal 1A and the in-vehicle device 50, and the pedestrian 7 carrying the pedestrian terminal 70. Also included are a vehicle 5 that does not have a wireless communication function and a pedestrian 7 that does not carry the pedestrian terminal 70.
 エッジサーバ3は、サービスエリア内の車両5の車載装置50や、歩行者端末70、路側センサ8などから、前述の変化点情報を所定周期で収集する(ステップS31)。
 エッジサーバ3は、収集した変化点情報をマップマッチングによって統合し(統合処理)、管理中の情報マップM1の動的情報を更新する(ステップS32)。
The edge server 3 collects the above-described change point information at a predetermined cycle from the in-vehicle device 50 of the vehicle 5 in the service area, the pedestrian terminal 70, the roadside sensor 8, and the like (step S31).
The edge server 3 integrates the collected change point information by map matching (integration processing), and updates the dynamic information of the information map M1 being managed (step S32).
 エッジサーバ3は、車両5の車載装置50または歩行者端末70から要求があれば、最新の動的情報を要求元の通信ノードに送信する(ステップS33)。これにより、たとえば動的情報を受信した車両5は、搭乗者の運転支援などに動的情報を活用することができる。
 なお、エッジサーバ3は、ステップS32で更新したマップM1を動的情報として要求元の通信ノードに送信してもよい。
If there is a request from the in-vehicle device 50 or the pedestrian terminal 70 of the vehicle 5, the edge server 3 transmits the latest dynamic information to the requesting communication node (step S33). Thereby, for example, the vehicle 5 that has received the dynamic information can use the dynamic information for driving assistance of the passenger.
The edge server 3 may transmit the map M1 updated in step S32 as dynamic information to the requesting communication node.
 動的情報を受信した車両5は、動的情報に基づいて自車両のセンサ情報との変化点情報を検出すると、検出した変化点情報をエッジサーバ3に送信する(ステップS34)。 When the vehicle 5 that has received the dynamic information detects the change point information with the sensor information of the vehicle based on the dynamic information, the vehicle 5 transmits the detected change point information to the edge server 3 (step S34).
 このように、本実施形態の情報提供システムでは、変化点情報の収集(ステップS31)→動的情報の更新(ステップS32)→動的情報の配信(ステップS33)→車両による変化点情報の検出(ステップS34)→変化点情報の収集(ステップS31)の順で、各通信ノードにおける情報処理が循環する。 Thus, in the information provision system of this embodiment, change point information collection (step S31) → dynamic information update (step S32) → dynamic information distribution (step S33) → change point information detection by a vehicle (Step S34) → Information processing in each communication node circulates in the order of change point information collection (Step S31).
 図6は1つのエッジサーバ3のみを含む情報提供システムを例示しているが、情報提供システムは複数のエッジサーバ3を含んでもよいし、エッジサーバ3の替わりに、あるいはエッジサーバ3に加えて、1または複数のコアサーバ4を含んでもよい。
 また、エッジサーバ3が管理する情報マップM1は、デジタル地図などの地図情報に少なくとも物体の動的情報が重畳されたマップであればよい。この点は、コアサーバの情報マップM2の場合も同様である。
Although FIG. 6 illustrates an information providing system including only one edge server 3, the information providing system may include a plurality of edge servers 3, instead of the edge server 3, or in addition to the edge server 3. One or a plurality of core servers 4 may be included.
The information map M1 managed by the edge server 3 may be a map in which at least dynamic information of an object is superimposed on map information such as a digital map. This also applies to the core server information map M2.
〔動的情報の更新処理および配信処理〕
 図7は、歩行者端末70、車両5の車載装置50、路側センサ8、およびエッジサーバ3の協働により実行される、動的情報の更新処理および配信処理の一例を示すシーケンス図である。
 以下の説明では、実行主体が歩行者端末70、車両5の車載装置50、路側センサ8およびエッジサーバ3となっているが、実際の実行主体は、それらの制御部71,51,81,31である。
 なお、図7中のU1,U2・・・は、動的情報の配信周期である。
[Dynamic information update processing and distribution processing]
FIG. 7 is a sequence diagram illustrating an example of dynamic information update processing and distribution processing executed by the cooperation of the pedestrian terminal 70, the in-vehicle device 50 of the vehicle 5, the roadside sensor 8, and the edge server 3.
In the following description, the execution subject is the pedestrian terminal 70, the in-vehicle device 50 of the vehicle 5, the roadside sensor 8, and the edge server 3, but the actual execution subject is the control units 71, 51, 81, 31. It is.
7, U1, U2,... Are dynamic information distribution cycles.
 図7を参照して、エッジサーバ3は、歩行者端末70および車両5の車載装置50から動的情報の要求メッセージを受信すると(ステップS1)、受信時点において最新の動的情報を、送信元の歩行者端末70および車両5の車載装置50に配信する(ステップS2)。 Referring to FIG. 7, when the edge server 3 receives the dynamic information request message from the pedestrian terminal 70 and the in-vehicle device 50 of the vehicle 5 (step S <b> 1), the latest dynamic information at the time of reception is transmitted to the transmission source. To the pedestrian terminal 70 and the in-vehicle device 50 of the vehicle 5 (step S2).
 好ましくは、ステップS1でエッジサーバ3は、受信した要求メッセージを解析し、当該メッセージに含まれる要求元を示す情報が予め登録されている通信端末1を示す情報である場合に、当該要求メッセージの送信元に対して動的情報を送信する。 Preferably, in step S1, the edge server 3 analyzes the received request message, and when the information indicating the request source included in the message is information indicating the communication terminal 1 registered in advance, Send dynamic information to the source.
 ステップS1において、歩行者端末70および車載装置50のうちのいずれか一方から要求メッセージがあった場合には、ステップS2において、要求メッセージの送信元である一方の通信端末のみに動的情報が配信される。 If there is a request message from either one of the pedestrian terminal 70 and the in-vehicle device 50 in step S1, dynamic information is distributed only to one communication terminal that is the transmission source of the request message in step S2. Is done.
 ステップS2で配信された動的情報を受信した歩行者端末70は、配信周期U1内に、変化点情報を生成すると(ステップS3)、生成した変化点情報をエッジサーバ3に送信する(ステップS6)。
 ステップS2で配信された動的情報を受信した車載装置50は、配信周期U1内に、動的情報と自身のセンサ情報との比較結果から変化点情報を生成すると(ステップS4)、生成した変化点情報をエッジサーバ3に送信する(ステップS6)。
 また、路側センサ8は、配信周期U1内に、自身のセンサ情報の変化点情報を生成すると、生成した変化点情報をエッジサーバ3に送信する(ステップS6)。
The pedestrian terminal 70 that has received the dynamic information distributed in step S2 generates change point information within the distribution cycle U1 (step S3), and transmits the generated change point information to the edge server 3 (step S6). ).
The vehicle-mounted device 50 that has received the dynamic information distributed in step S2 generates change point information from the comparison result between the dynamic information and its own sensor information within the distribution cycle U1 (step S4), and the generated change. The point information is transmitted to the edge server 3 (step S6).
Moreover, if the roadside sensor 8 produces | generates the change point information of own sensor information within the delivery period U1, it will transmit the produced | generated change point information to the edge server 3 (step S6).
 エッジサーバ3は、更新周期U1内に、歩行者端末70、車載装置50および路側センサ8から変化点情報を受信すると、それらの変化点情報を反映した動的情報に更新し(ステップS7)、更新後の動的情報を歩行者端末70および車載装置50に配信する(ステップS8)。 When the edge server 3 receives the change point information from the pedestrian terminal 70, the in-vehicle device 50, and the roadside sensor 8 within the update cycle U1, the edge server 3 updates the dynamic information reflecting the change point information (step S7). The updated dynamic information is distributed to the pedestrian terminal 70 and the in-vehicle device 50 (step S8).
 例えば、配信周期U1内に、車載装置50のみが変化点情報を生成した場合は、ステップS4で車載装置50が生成した変化点情報のみがエッジサーバ3に送信され(ステップS6)、その変化点情報のみを反映した動的情報の更新が行われる(ステップS7)。
 また、配信周期U1内に、歩行者端末70、車載装置50、および路側センサ8が変化点情報をしなかった場合は、ステップS3~S7の処理が実行されず、前回送信分の動的情報(ステップS2)と同じ動的情報が歩行者端末70および車載装置50に配信される(ステップS8)。
 このように、エッジサーバ3は、配信周期U1内に送信された変化点情報に基づき、ステップS7における動的情報の更新を行う。
For example, when only the in-vehicle device 50 generates change point information within the distribution cycle U1, only the change point information generated by the in-vehicle device 50 in step S4 is transmitted to the edge server 3 (step S6), and the change point The dynamic information that reflects only the information is updated (step S7).
If the pedestrian terminal 70, the in-vehicle device 50, and the roadside sensor 8 do not perform change point information within the distribution cycle U1, the processes of steps S3 to S7 are not executed, and the dynamic information for the previous transmission is transmitted. The same dynamic information as (Step S2) is distributed to the pedestrian terminal 70 and the in-vehicle device 50 (Step S8).
Thus, the edge server 3 updates the dynamic information in step S7 based on the change point information transmitted within the distribution cycle U1.
 ステップS8で配信された動的情報を受信した歩行者端末70は、配信周期U2内に、変化点情報を生成すると(ステップS9)、生成した変化点情報をエッジサーバ3に送信する(ステップS12)。
 ステップS8で配信された動的情報を受信した車載装置50は、配信周期U2内に、動的情報と自身のセンサ情報との比較結果から変化点情報を生成すると(ステップS10)、生成した変化点情報をエッジサーバ3に送信する(ステップS12)。
 また、路側センサ8は、配信周期U2内に、自身のセンサ情報の変化点情報を生成すると、生成した変化点情報をエッジサーバ3に送信する(ステップS12)。
The pedestrian terminal 70 that has received the dynamic information distributed in step S8 generates change point information within the distribution cycle U2 (step S9), and transmits the generated change point information to the edge server 3 (step S12). ).
The in-vehicle device 50 that has received the dynamic information distributed in step S8 generates change point information from the comparison result between the dynamic information and its own sensor information within the distribution cycle U2 (step S10), and the generated change. The point information is transmitted to the edge server 3 (step S12).
Moreover, if the roadside sensor 8 produces | generates the change point information of own sensor information within the delivery period U2, it will transmit the produced | generated change point information to the edge server 3 (step S12).
 エッジサーバ3は、配信周期U2内に車載装置50および路側センサ8から変化点情報を受信すると、それらの変化点情報を反映した動的情報に更新し(ステップS13)、更新後の動的情報を歩行者端末70および車載装置50に配信する(ステップS14)。
 このように、エッジサーバ3は、配信周期U2内に送信された変化点情報に基づき、ステップS13における動的情報の更新を行う。
When receiving the change point information from the in-vehicle device 50 and the roadside sensor 8 within the distribution cycle U2, the edge server 3 updates the dynamic information reflecting the change point information (step S13), and the updated dynamic information. Is distributed to the pedestrian terminal 70 and the vehicle-mounted device 50 (step S14).
Thus, the edge server 3 updates the dynamic information in step S13 based on the change point information transmitted within the distribution cycle U2.
 ステップS14以降の処理は、歩行者端末70および車両5の双方から、動的情報の配信停止の要求メッセージを受信するか、または、歩行者端末70および車両5の通信が遮断されるまで、上記と同様のシーケンスによって繰り返される。 The processing after step S14 is performed until either the dynamic information distribution stop request message is received from both the pedestrian terminal 70 and the vehicle 5 or the communication between the pedestrian terminal 70 and the vehicle 5 is interrupted. And the same sequence is repeated.
〔移動端末に対する情報提供〕
 本実施形態の情報提供システムは、サービスエリア内に位置する1又は複数の移動体に搭載された歩行者端末70や、車両5の車載装置50に対して予測交通状況に関する情報を提供する機能を有している。なお、予測交通状況とは、将来の交通状況を予測した結果を示す。
[Providing information to mobile terminals]
The information providing system of the present embodiment has a function of providing information related to the predicted traffic situation to the pedestrian terminal 70 mounted on one or a plurality of moving bodies located in the service area and the in-vehicle device 50 of the vehicle 5. Have. The predicted traffic situation indicates a result of predicting a future traffic situation.
 図8は、予測交通状況を提供するための機能について示したエッジサーバ3の機能ブロック図である。
 エッジサーバ3の制御部31は、演算部31a、判定部31b、通知部31c、検出部31dを機能的に有している。これら各機能は、記憶部34に記憶されたプログラムを制御部31が実行することで実現される。
FIG. 8 is a functional block diagram of the edge server 3 showing functions for providing the predicted traffic situation.
The control unit 31 of the edge server 3 functionally includes a calculation unit 31a, a determination unit 31b, a notification unit 31c, and a detection unit 31d. Each of these functions is realized by the control unit 31 executing a program stored in the storage unit 34.
 演算部31aは、動的情報マップM1に基づいて、動的情報マップM1が表すサービスエリア内に位置する移動体(歩行者7、車両5)に搭載された移動端末(歩行者端末70及び車載装置50)それぞれの交通状況の予測を行い、予測交通状況の評価値を求める機能を有している。演算部31aは、動的情報マップM1から得られる情報が登録された移動体データベース34a(後に説明する)を参照し、予測交通状況の評価値を求める。 Based on the dynamic information map M1, the calculation unit 31a is a mobile terminal (pedestrian terminal 70 and on-vehicle device) mounted on a mobile body (pedestrian 7, vehicle 5) located in the service area represented by the dynamic information map M1. Device 50) It has a function of predicting each traffic situation and obtaining an evaluation value of the predicted traffic situation. The computing unit 31a refers to a mobile database 34a (described later) in which information obtained from the dynamic information map M1 is registered, and obtains an estimated value of the predicted traffic situation.
 判定部31bは、移動端末(歩行者端末70及び車載装置50)へ、各移動端末それぞれの予測交通状況に関する情報を通知するか否かを、前記評価値に基づいて判定する機能を有している。
 通知部31cは、判定部31bの判定結果に基づいて移動端末へ予測交通状況に関する情報を通知する機能を有している。
 また、検出部31dは、動的情報マップM1の動的情報に位置情報が含まれている複数の移動体(歩行者7、車両5)を検出し、各移動体の状況を示す移動体情報を生成する機能を有している。
The determination unit 31b has a function of determining, based on the evaluation value, whether to notify the mobile terminal (the pedestrian terminal 70 and the in-vehicle device 50) information regarding the predicted traffic situation of each mobile terminal. Yes.
The notification unit 31c has a function of notifying the mobile terminal of information related to the predicted traffic situation based on the determination result of the determination unit 31b.
In addition, the detection unit 31d detects a plurality of moving bodies (pedestrian 7 and vehicle 5) whose position information is included in the dynamic information of the dynamic information map M1, and the moving body information indicating the status of each moving body. It has the function to generate.
 また、記憶部34には、上述の動的情報マップM1の他、移動体データベース34a及び評価値データベース34bが記憶されている。
 図9は、移動体データベース34aの一例を示す図である。
 図9に示すように、移動体データベース34aには、検出部31dが生成する移動体情報が登録されている。
 移動体データベース34aは、検出部31dによって管理、更新される。
 検出部31dは、動的情報マップM1を参照し、動的情報に新たな移動体(歩行者7、車両5)の位置情報が登録されると、その移動体に移動体IDを付与し、移動体IDに対応する移動体情報を生成して移動体データベース34aに登録する。このように、検出部31dは、動的情報マップM1に位置情報が登録されている移動体を検出するとともに、移動体それぞれに移動体IDを付与し、移動体情報を生成する。
In addition to the dynamic information map M1, the mobile unit database 34a and the evaluation value database 34b are stored in the storage unit 34.
FIG. 9 is a diagram illustrating an example of the mobile object database 34a.
As shown in FIG. 9, the moving body information generated by the detection unit 31d is registered in the moving body database 34a.
The mobile database 34a is managed and updated by the detection unit 31d.
The detection unit 31d refers to the dynamic information map M1, and when the position information of a new moving body (pedestrian 7, vehicle 5) is registered in the dynamic information, the moving body ID is given to the moving body, The mobile body information corresponding to the mobile body ID is generated and registered in the mobile body database 34a. As described above, the detection unit 31d detects a moving body whose position information is registered in the dynamic information map M1, and assigns a moving body ID to each moving body to generate moving body information.
 移動体情報には、通信機能の有無に関する情報、車両ID(携帯ID)、移動体の属性情報、位置情報、移動方向を示す方位情報、及び移動速度を示す速度情報といった情報が含まれる。なお、属性情報とは、移動体の種別を示す情報であり、例えば、移動体が車両であるか又は歩行者であるかを示す情報である。また属性情報は、移動体が歩行者の場合、大人か子供かを示す情報、及び体の向きを示す情報を含む。さらに、属性情報は、その歩行者が松葉杖や車椅子の利用者か否かを示す情報、服の色や種類等の外観を示す情報、歩きスマホであるか否かを示す情報等を含んでいてもよい。 The moving body information includes information such as information on presence / absence of a communication function, vehicle ID (mobile ID), moving body attribute information, position information, direction information indicating a moving direction, and speed information indicating a moving speed. The attribute information is information indicating the type of the moving object, for example, information indicating whether the moving object is a vehicle or a pedestrian. Moreover, attribute information contains the information which shows whether it is an adult or a child, and the information which shows the direction of a body, when a moving body is a pedestrian. Further, the attribute information includes information indicating whether or not the pedestrian is a crutch or wheelchair user, information indicating the appearance of the color or type of clothes, information indicating whether or not the user is a walking smartphone, and the like. Also good.
 移動体データベース34aには、移動体ID、通信機能の有無に関する情報、車両ID(携帯ID)、移動体の属性情報、位置情報、方位情報、及び速度情報それぞれを登録するための欄が設けられている。 The mobile body database 34a is provided with columns for registering mobile body IDs, information on presence / absence of communication functions, vehicle ID (mobile ID), mobile body attribute information, position information, direction information, and speed information. ing.
 検出部31dは、動的情報マップM1を参照し、移動体それぞれの移動体情報を生成する。
 検出部31dは、移動体情報のうち、動的情報マップM1に含まれている通信機能の有無に関する情報、車両ID(携帯ID)、及び位置情報については、移動体データベース34aに含まれる情報をそのまま取得する。
 属性情報について、検出部31dは、動的情報マップM1に含まれる、カメラ等によって撮像された移動体の画像データを参照し、移動体それぞれの属性を判定しその判定に基づいて属性情報を生成する。
 方位情報及び速度情報について、検出部31dは、動的情報マップM1に含まれる移動体それぞれの位置情報の経時変化に基づいて算出する。
The detecting unit 31d refers to the dynamic information map M1 and generates moving body information for each moving body.
The detection unit 31d includes information on the presence or absence of a communication function included in the dynamic information map M1, the vehicle ID (mobile ID), and the position information among the mobile body information. Get as it is.
For the attribute information, the detection unit 31d refers to the image data of the moving object captured by the camera or the like included in the dynamic information map M1, determines the attribute of each moving object, and generates attribute information based on the determination To do.
For the azimuth information and the speed information, the detection unit 31d calculates based on the temporal change of the position information of each moving object included in the dynamic information map M1.
 検出部31dは、移動体それぞれの移動体情報の生成と、移動体情報の移動体データベース34aへの登録を繰り返し実行し、移動体データベース34aを随時更新する。これにより、移動体データベース34aに登録されている移動体情報は、最新の情報に維持される。 The detection unit 31d repeatedly generates the mobile body information of each mobile body and registers the mobile body information in the mobile body database 34a, and updates the mobile body database 34a as needed. Thereby, the moving body information registered in the moving body database 34a is maintained in the latest information.
 また、図8中の評価値データベース34bは、演算部31aが求める予測交通状況の評価値を登録するためのデータベースである。評価値データベース34bについては後に説明する。 In addition, the evaluation value database 34b in FIG. 8 is a database for registering the evaluation value of the predicted traffic situation obtained by the calculation unit 31a. The evaluation value database 34b will be described later.
〔評価値の演算処理〕
 図10は、演算部31aによる予測交通状況の評価値の演算処理の一例を示すフローチャートである。
 図10に示すように、まず、演算部31aは、移動体データベース34aを読み込み(ステップS51)、通信機能を有する移動体を評価対象として特定する(ステップS52)。予測交通状況に関する情報は、歩行者端末70や車載装置50を有している移動体に提供可能である。よって、演算部31aは、歩行者端末70や車載装置50を有している移動体を、評価値を求める評価対象として特定する。
 つまり、評価対象とは、演算部31aにより評価値が求められる移動端末を指す。
 なお、以下の説明において、評価対象とは、移動体に携帯又は搭載されている歩行者端末70又は車載装置50の他、評価対象である歩行者端末70や車載装置50を有している移動体(対象移動体)を指すことがある。
[Evaluation value calculation]
FIG. 10 is a flowchart illustrating an example of a calculation process of the evaluation value of the predicted traffic situation by the calculation unit 31a.
As shown in FIG. 10, first, the computing unit 31a reads the mobile object database 34a (step S51), and specifies a mobile object having a communication function as an evaluation target (step S52). Information relating to the predicted traffic situation can be provided to a mobile body having the pedestrian terminal 70 and the in-vehicle device 50. Therefore, the calculating part 31a specifies the mobile body which has the pedestrian terminal 70 and the vehicle-mounted apparatus 50 as an evaluation object which calculates | requires an evaluation value.
That is, the evaluation target refers to a mobile terminal whose evaluation value is obtained by the calculation unit 31a.
In the following description, the evaluation object is a movement having the pedestrian terminal 70 or the in-vehicle device 50 that is the evaluation object in addition to the pedestrian terminal 70 or the in-vehicle device 50 that is carried or mounted on the moving body. It may refer to the body (target moving body).
 次いで、演算部31aは、評価値演算処理を行う(ステップS53)。
 演算部31aは、評価値演算処理において、特定した評価対象それぞれに対して順次処理を実行し、評価対象の全てに対して処理するまで処理を繰り返す。
 演算部31aは、評価値演算処理において、まず評価対象の属性が車両か否かを判定する(ステップS54)。
Next, the calculation unit 31a performs evaluation value calculation processing (step S53).
In the evaluation value calculation process, the calculation unit 31a sequentially executes the process for each of the specified evaluation targets, and repeats the process until it is processed for all the evaluation targets.
In the evaluation value calculation process, the calculation unit 31a first determines whether or not the attribute to be evaluated is a vehicle (step S54).
 評価対象の属性が車両であると判定する場合(ステップS54)、演算部31aは、ステップS55へ進み、車両用演算処理を行う。演算部31aは、車両用演算処理において評価対象の評価値を求める(ステップS55)。 When it is determined that the attribute to be evaluated is a vehicle (step S54), the calculation unit 31a proceeds to step S55 and performs a calculation process for the vehicle. The calculation unit 31a obtains an evaluation value to be evaluated in the vehicle calculation process (step S55).
 図11は、図10中ステップS55の車両用演算処理の一例を示すフローチャートである。
 図11に示すように、演算部31aは、評価対象以外の移動体(他の移動体)を特定し(ステップS61)、評価対象(対象移動体)と、評価対象以外の移動体との衝突予測時間を、評価対象以外の移動体それぞれについて算出する(ステップS62)。
FIG. 11 is a flowchart showing an example of the vehicle calculation process in step S55 in FIG.
As illustrated in FIG. 11, the calculation unit 31a identifies a moving body (another moving body) other than the evaluation target (step S61), and a collision between the evaluation target (target moving body) and a moving body other than the evaluation target. The predicted time is calculated for each mobile object other than the evaluation target (step S62).
 演算部31aは、移動体データベース34aを参照し、評価対象、及び評価対象以外の移動体それぞれの位置情報、方位情報、及び速度情報から、評価対象と、評価対象以外の移動体とが衝突するとした場合の衝突予測時間を求める。
 演算部31aは、位置情報、及び方位情報から衝突の可能性がない場合、衝突予測時間を極端に大きい所定値(例えば、5分)に設定する。また、演算部31aは、求めた衝突予測時間が前記所定値以上となる場合も、衝突予測時間を前記所定値に設定する。
When the calculation unit 31a refers to the moving object database 34a and the evaluation object and the moving object other than the evaluation object collide with each other from the position information, the azimuth information, and the speed information of the evaluation object and the moving object other than the evaluation object, The estimated collision time is obtained.
When there is no possibility of a collision from the position information and the direction information, the calculation unit 31a sets the collision prediction time to an extremely large predetermined value (for example, 5 minutes). In addition, the calculation unit 31a sets the collision prediction time to the predetermined value even when the calculated collision prediction time is equal to or longer than the predetermined value.
 このように、演算部31aは、動的情報マップM1に基づいて、評価対象と評価対象以外の移動体との衝突を予測し、衝突予測の予測結果(予測交通状況)として衝突予測時間を求める。 As described above, the calculation unit 31a predicts a collision between the evaluation object and a mobile body other than the evaluation object based on the dynamic information map M1, and obtains a collision prediction time as a prediction result (predicted traffic situation) of the collision prediction. .
 演算部31aは、評価対象以外の移動体それぞれについて算出した衝突予測時間のうち、最も短い衝突予測時間となる移動体を衝突予測対象として特定する(ステップS63)。
 ここで、衝突予測時間が最も短い移動体が評価対象に対して最も衝突する可能性が高いと判定することができる。このため、演算部31aは、最も短い衝突予測時間の移動体を衝突予測対象として特定する。
The computing unit 31a identifies the mobile body having the shortest predicted collision time among the predicted collision times calculated for each of the mobile bodies other than the evaluation target as a collision prediction target (step S63).
Here, it can be determined that the moving object with the shortest collision prediction time is most likely to collide with the evaluation target. For this reason, the calculating part 31a specifies the mobile body of the shortest collision prediction time as a collision prediction object.
 次いで、演算部31aは、評価対象と衝突予測対象との間の衝突予測時間に基づいて、予測結果(衝突予測結果)の評価値を求める(ステップS64)。
 演算部31aは、衝突予測時間に対して、下記に示すルールに従って予測結果の評価値を求める。例えば、以下のような設定になるが、これに限定されるものではない。
   衝突予測時間が10秒以上: 評価値=0
   衝突予測時間が10秒未満: 評価値=20
   衝突予測時間が 5秒未満: 評価値=100
   衝突予測時間が 3秒未満: 評価値=200
   衝突予測時間が 1秒未満: 評価値=500
 この評価値は、値が大きいほど、評価対象の安全性を阻害する要因が高くなるように設定される。つまり、評価値は、評価対象それぞれの安全度を評価するための値である。
 なお、演算部31aは、衝突予測対象以外の移動体に対する評価値として「0」を設定する。
Next, the computing unit 31a obtains an evaluation value of the prediction result (collision prediction result) based on the collision prediction time between the evaluation object and the collision prediction object (step S64).
The calculation unit 31a obtains an evaluation value of the prediction result according to the following rule with respect to the collision prediction time. For example, the setting is as follows, but the present invention is not limited to this.
Collision prediction time is 10 seconds or more: Evaluation value = 0
Collision prediction time is less than 10 seconds: Evaluation value = 20
Collision prediction time is less than 5 seconds: Evaluation value = 100
Collision prediction time is less than 3 seconds: Evaluation value = 200
Collision prediction time is less than 1 second: Evaluation value = 500
The evaluation value is set such that the larger the value, the higher the factor that hinders the safety of the evaluation target. That is, the evaluation value is a value for evaluating the degree of safety of each evaluation object.
The calculation unit 31a sets “0” as the evaluation value for the moving body other than the collision prediction target.
 以上のように、演算部31aは、評価対象と、評価対象以外の移動体との間の衝突予測の予測結果である衝突予測時間に基づいて移動体ごとの評価値を求める。
 これにより、評価対象と、評価対象以外の移動体との間の衝突予測の評価値を得ることができる。
As described above, the calculation unit 31a obtains an evaluation value for each moving object based on the collision prediction time that is a prediction result of the collision prediction between the evaluation object and the moving object other than the evaluation object.
Thereby, the evaluation value of the collision prediction between the evaluation object and the moving object other than the evaluation object can be obtained.
 より詳細には、演算部31aは、評価対象以外の移動体のうち、評価対象に対して衝突すると予測される移動体(衝突予測対象)を、衝突予測の予測結果である衝突予測時間に基づいて特定し、衝突予測対象に関する衝突予測時間に基づいて評価値を求める。
 これにより、衝突すると予測される評価対象の衝突予測に関する評価値を得ることができる。
More specifically, the calculation unit 31a selects a mobile body (collision prediction target) that is predicted to collide with the evaluation target among the mobile bodies other than the evaluation target based on the collision prediction time that is a prediction result of the collision prediction. And an evaluation value is obtained based on the collision prediction time for the collision prediction target.
Thereby, it is possible to obtain an evaluation value related to a collision prediction of an evaluation target predicted to collide.
 次いで、演算部31aは、ステップS65に進み、評価対象と衝突予測対象との間に死角を生じさせる死角要因が有るか否かを判定する(ステップS65)。
 評価対象と衝突予測対象との間の死角要因の有無は、演算部31aが動的情報マップM1を参照することで判定される。演算部31aは、動的情報マップM1を参照し、評価対象と衝突予測対象との間に両者の見通しを遮る建物や、他の移動体等の有無を判定する。評価対象と衝突予測対象との間にこのような建物や他の移動体等が存在する場合、演算部31aは、評価対象と衝突予測対象との間に死角要因が有ると判定する。一方、評価対象と衝突予測対象との間に見通しを遮るものが無ければ、演算部31aは、死角要因がないと判定する。
Next, the calculation unit 31a proceeds to step S65, and determines whether or not there is a blind spot factor that causes a blind spot between the evaluation target and the collision prediction target (step S65).
The presence or absence of a blind spot factor between the evaluation target and the collision prediction target is determined by the calculation unit 31a referring to the dynamic information map M1. The computing unit 31a refers to the dynamic information map M1 and determines the presence or absence of a building or other moving body that blocks the prospects of both between the evaluation target and the collision prediction target. When such a building or other moving body exists between the evaluation target and the collision prediction target, the calculation unit 31a determines that there is a blind spot factor between the evaluation target and the collision prediction target. On the other hand, if there is nothing that blocks the line of sight between the evaluation target and the collision prediction target, the calculation unit 31a determines that there is no blind spot factor.
 ステップS65において、評価対象と衝突予測対象との間に死角要因が有ると判定する場合、演算部31aは、ステップS64において求めた評価値に加算を行い(ステップS66)、ステップS67へ進む。
 一方、評価対象と衝突予測対象との間に死角要因が無いと判定する場合(ステップS65)、演算部31aは、評価値に対する加算を行わずにステップS67へ進む。
If it is determined in step S65 that there is a blind spot factor between the evaluation target and the collision prediction target, the computing unit 31a adds to the evaluation value obtained in step S64 (step S66), and proceeds to step S67.
On the other hand, when it is determined that there is no blind spot factor between the evaluation target and the collision prediction target (step S65), the calculation unit 31a proceeds to step S67 without performing addition to the evaluation value.
 評価値は、上述のように、値が大きいほど、評価対象の安全性を阻害する要因が高くなるように設定される。
 評価対象と衝突予測対象との間に死角要因が有る場合、評価対象においては、安全性がより阻害される。よって、死角要因が有ると判定する場合には、演算部31aは評価値に加算を行う。
 なおステップS66において評価値に加算される加算値は、例えば「100」である。この加算値は、一例であってこれに限定されるものではない。以下に示す加算値も同様である。
As described above, the evaluation value is set such that the larger the value, the higher the factor that hinders the safety of the evaluation target.
When there is a blind spot factor between the evaluation target and the collision prediction target, the safety is further inhibited in the evaluation target. Therefore, when it determines with there being a blind spot factor, the calculating part 31a adds to an evaluation value.
The added value added to the evaluation value in step S66 is “100”, for example. This added value is an example and is not limited to this. The same applies to the added values shown below.
 このように、演算部31aは、評価対象と、衝突予測対象との間に死角を生じさせる死角要因の有無を判定し、死角要因の有無の判定結果を評価値に加味する。
 この場合、死角要因の有無を、評価値に反映でき、後述する評価対象への情報提供の実行判定に反映させることができる。
As described above, the calculation unit 31a determines the presence / absence of a blind spot factor that causes a blind spot between the evaluation target and the collision prediction target, and adds the determination result of the presence / absence of the blind spot factor to the evaluation value.
In this case, the presence / absence of the blind spot factor can be reflected in the evaluation value, and can be reflected in the execution determination of providing information to the evaluation target described later.
 次に、演算部31aは、ステップS67において、衝突予測対象が歩行者か否かを判定する(ステップS67)。
 衝突予測対象(の移動体)が歩行者7である場合、演算部31aは、ステップS68へ進み、衝突予測対象である歩行者7の状況判定を行い、処理を終える。
Next, in step S67, the calculation unit 31a determines whether or not the collision prediction target is a pedestrian (step S67).
When the collision prediction target (the moving body) is the pedestrian 7, the calculation unit 31a proceeds to step S68, determines the situation of the pedestrian 7 that is the collision prediction target, and finishes the process.
 一方、衝突予測対象(の移動体)が歩行者7でない場合、衝突予測対象は車両5であるので、演算部31aは、歩行者7の状況判定を行うことなく車両用演算処理を終える。 On the other hand, when the collision prediction target (the moving body) is not the pedestrian 7, the collision prediction target is the vehicle 5, and thus the calculation unit 31 a finishes the vehicle calculation process without determining the situation of the pedestrian 7.
 図12は、図11中の歩行者7の状況判定処理の一例を示すフローチャートである。
 図12に示すように、演算部31aは、衝突予測対象の歩行者7が横断歩道又は歩道を歩行していないか否かを判定する(ステップS71)。
 衝突予測対象の歩行者7が横断歩道又は歩道を歩行していないか否かの判定は、演算部31aが動的情報マップM1を参照することで判定される。演算部31aは、動的情報マップM1の静的情報に含まれる横断歩道や歩道の位置情報と、歩行者7の位置情報とを比較することで、歩行者7が横断歩道又は歩道を歩行していないか否かを判定することができる。
FIG. 12 is a flowchart showing an example of the situation determination process for the pedestrian 7 in FIG.
As illustrated in FIG. 12, the calculation unit 31 a determines whether or not the pedestrian 7 subject to collision prediction is walking on a pedestrian crossing or a sidewalk (step S <b> 71).
Whether or not the pedestrian 7 subject to collision prediction is walking on a pedestrian crossing or a sidewalk is determined by referring to the dynamic information map M1 by the calculation unit 31a. The computing unit 31a compares the position information of the pedestrian crossing and the sidewalk included in the static information of the dynamic information map M1 with the position information of the pedestrian 7, so that the pedestrian 7 walks the pedestrian crossing or the sidewalk. It can be determined whether or not.
 ステップS71において、衝突予測対象の歩行者7が横断歩道又は歩道を歩行していないと判定する場合、演算部31aは、評価値に加算を行い(ステップS72)、ステップS73へ進む。
 一方、衝突予測対象の歩行者7が横断歩道又は歩道を歩行していると判定する場合(ステップS71)、演算部31aは、評価値に対する加算を行わずにステップS73へ進む。
In step S71, when it determines with the pedestrian 7 of collision prediction object not walking the pedestrian crossing or a sidewalk, the calculating part 31a adds to an evaluation value (step S72), and progresses to step S73.
On the other hand, when it determines with the pedestrian 7 of collision prediction object walking the pedestrian crossing or a sidewalk (step S71), the calculating part 31a progresses to step S73, without performing addition with respect to an evaluation value.
 衝突予測対象の歩行者7が横断歩道又は歩道を歩行していない場合、評価対象においては、安全性がより阻害される。よって、衝突予測対象の歩行者7が横断歩道又は歩道を歩行していないと判定する場合には、演算部31aは評価値に加算を行う。
 なおステップS72において評価値に加算される加算値は、例えば「100」である。
When the pedestrian 7 subject to collision prediction is not walking on a pedestrian crossing or a sidewalk, safety is further inhibited in the evaluation target. Therefore, when it determines with the pedestrian 7 of collision prediction object not walking the pedestrian crossing or a sidewalk, the calculating part 31a adds to an evaluation value.
Note that the added value added to the evaluation value in step S72 is, for example, “100”.
 次に、演算部31aは、衝突予測対象の歩行者7の歩行速度が所定値よりも遅いか否かを判定する(ステップS73)。
 衝突予測対象の歩行者7の歩行速度が所定値よりも遅いか否かの判定は、移動体データベース34aを参照することで判定することができる。
 なお、歩行速度と比較される所定値は、例えば、一般的な歩行者の速度として3.6km毎時に設定される。
Next, the computing unit 31a determines whether or not the walking speed of the pedestrian 7 to be predicted for collision is slower than a predetermined value (step S73).
Whether or not the walking speed of the pedestrian 7 subject to collision prediction is slower than a predetermined value can be determined by referring to the mobile database 34a.
The predetermined value to be compared with the walking speed is set, for example, every 3.6 km as a general pedestrian speed.
 ステップS73において、衝突予測対象の歩行者7の歩行速度が所定値よりも遅いと判定する場合、演算部31aは、評価値に加算を行い(ステップS74)、ステップS75へ進む。
 一方、衝突予測対象の歩行者7の歩行速度が所定値よりも遅くないと判定する場合(ステップS73)、演算部31aは、評価値に対する加算を行わずにステップS75へ進む。
In step S73, when it determines with the walking speed of the pedestrian 7 of collision prediction object being slower than predetermined value, the calculating part 31a adds to an evaluation value (step S74), and progresses to step S75.
On the other hand, when it determines with the walking speed of the pedestrian 7 of collision prediction object not being slower than predetermined value (step S73), the calculating part 31a progresses to step S75, without adding with respect to an evaluation value.
 例えば、衝突予測対象の歩行者7が横断歩道を渡っている場合において、その歩行者7の歩行速度が所定値よりも遅い場合、青信号の間に歩行者7が横断歩道を渡り切れない可能性があることを考慮すれば、評価対象においては、安全性の阻害要因となる。よって、歩行者7の歩行速度が所定値よりも遅いと判定する場合には、演算部31aは評価値に加算を行う。
 なお、ステップS74において評価値に加算される加算値は、例えば「100」である。
For example, when the pedestrian 7 subject to collision prediction is crossing a pedestrian crossing and the walking speed of the pedestrian 7 is slower than a predetermined value, the pedestrian 7 may not cross the pedestrian crossing during the green light. Considering the fact that there is, there is a safety hindrance factor in the evaluation target. Therefore, when it determines with the walking speed of the pedestrian 7 being slower than a predetermined value, the calculating part 31a adds to an evaluation value.
Note that the added value added to the evaluation value in step S74 is, for example, “100”.
 次に、演算部31aは、衝突予測対象の歩行者7の属性が子供か否かを判定する(ステップS75)。
 衝突予測対象の歩行者7の属性が子供か否かの判定は、移動体データベース34aを参照することで判定することができる。
Next, the computing unit 31a determines whether or not the attribute of the pedestrian 7 to be predicted for collision is a child (step S75).
Whether or not the attribute of the pedestrian 7 to be predicted for collision is a child can be determined by referring to the mobile database 34a.
 ステップS75において、衝突予測対象の歩行者7の属性が子供であると判定する場合、演算部31aは、評価値に加算を行い(ステップS76)、ステップS77へ進む。
 一方、衝突予測対象の歩行者7の属性が子供でないと判定する場合(ステップS75)、演算部31aは、評価値に対する加算を行わずにステップS77へ進む。
In step S75, when it determines with the attribute of the pedestrian 7 of collision prediction object being a child, the calculating part 31a adds to an evaluation value (step S76), and progresses to step S77.
On the other hand, when it determines with the attribute of the pedestrian 7 of collision prediction object not being a child (step S75), the calculating part 31a progresses to step S77, without performing addition with respect to an evaluation value.
 衝突予測対象の歩行者7が子供である場合、評価対象においては、安全性の阻害要因となる。よって、衝突予測対象の歩行者7の属性が子供と判定する場合には、演算部31aは評価値に加算を行う。
 なおステップS76において評価値に加算される加算値は、例えば「100」である。
When the pedestrian 7 subject to collision prediction is a child, it becomes an obstacle to safety in the evaluation target. Therefore, when the attribute of the pedestrian 7 subject to collision prediction is determined to be a child, the calculation unit 31a adds to the evaluation value.
The added value added to the evaluation value in step S76 is “100”, for example.
 次に、演算部31aは、衝突予測対象の歩行者7が蛇行しているか否かを判定する(ステップS77)。
 衝突予測対象の歩行者7が蛇行しているか否かの判定は、移動体データベース34a、又は動的情報マップM1に含まれる移動体の位置情報の経時変化に基づいて判定することができる。
Next, the calculation unit 31a determines whether or not the pedestrian 7 subject to collision prediction is meandering (step S77).
Whether or not the pedestrian 7 subject to collision prediction is meandering can be determined based on a time-dependent change in the position information of the moving body included in the moving body database 34a or the dynamic information map M1.
 ステップS77において、衝突予測対象の歩行者7が蛇行していると判定する場合、演算部31aは、評価値に加算を行い(ステップS78)、ステップS79へ進む。
 一方、衝突予測対象の歩行者7が蛇行していないと判定する場合(ステップS77)、演算部31aは、評価値に対する加算を行わずにステップS79へ進む。
In step S77, when it is determined that the pedestrian 7 subject to collision prediction is meandering, the calculation unit 31a adds the evaluation value (step S78), and proceeds to step S79.
On the other hand, when it determines with the pedestrian 7 of collision prediction object not meandering (step S77), the calculating part 31a progresses to step S79, without performing addition with respect to an evaluation value.
 衝突予測対象の歩行者7が蛇行している場合、評価対象においては、安全性の阻害要因となる。よって、衝突予測対象の歩行者7が蛇行していると判定する場合には、演算部31aは評価値に加算を行う。
 なおステップS78において評価値に加算される加算値は、例えば「100」である。
When the pedestrian 7 subject to collision prediction is meandering, it becomes an obstacle to safety in the evaluation target. Therefore, when it determines with the pedestrian 7 of a collision prediction object meandering, the calculating part 31a adds to an evaluation value.
The added value added to the evaluation value in step S78 is, for example, “100”.
 次に、演算部31aは、衝突予測対象の歩行者7が信号無視をしているか否かを判定する(ステップS79)。
 衝突予測対象の歩行者7が信号無視をしているか否かの判定は、動的情報マップM1の動的情報に含まれる信号情報及び移動体の位置情報に基づいて判定することができる。
Next, the calculation unit 31a determines whether or not the pedestrian 7 to be predicted for collision is ignoring the signal (step S79).
Whether or not the pedestrian 7 subject to collision prediction ignores the signal can be determined based on the signal information included in the dynamic information of the dynamic information map M1 and the position information of the moving body.
 ステップS79において、衝突予測対象の歩行者7が信号無視をしていると判定する場合、演算部31aは、評価値に加算を行い(ステップS80)、車両用演算処理(図11)を終える。
 一方、衝突予測対象の歩行者7が信号無視をしていないと判定する場合(ステップS79)、演算部31aは、評価値に対する加算を行わずに、車両用演算処理(図11)を終える。
In step S79, when it is determined that the pedestrian 7 subject to collision prediction ignores the signal, the calculation unit 31a adds to the evaluation value (step S80), and ends the vehicle calculation process (FIG. 11).
On the other hand, when it determines with the pedestrian 7 of collision prediction object not ignoring a signal (step S79), the calculating part 31a complete | finishes the calculation process for vehicles (FIG. 11), without adding with respect to an evaluation value.
 衝突予測対象の歩行者7が信号無視をしている場合、評価対象においては、安全性の阻害要因となる。よって、衝突予測対象の歩行者7が信号無視をしていると判定する場合には、演算部31aは評価値に加算を行う。
 なおステップS79において評価値に加算される加算値は、例えば「100」である。
When the pedestrian 7 subject to collision prediction ignores the signal, it becomes an obstacle to safety in the evaluation target. Therefore, when it determines with the pedestrian 7 of collision prediction object ignoring a signal, the calculating part 31a adds to an evaluation value.
Note that the addition value added to the evaluation value in step S79 is, for example, “100”.
 このように、演算部31aは、状況判定処理において、歩行者7に関する状況を取得し、取得した歩行者7の状況に応じた調整値としての加算値を評価値に加味する。 Thus, in the situation determination process, the calculation unit 31a acquires the situation regarding the pedestrian 7, and adds the added value as the adjustment value according to the acquired situation of the pedestrian 7 to the evaluation value.
 以上のように、演算部31aは、車両用演算処理(図10中、ステップS55)を行うことで、評価対象の評価値を求める。 As described above, the calculation unit 31a performs the vehicle calculation process (step S55 in FIG. 10) to obtain the evaluation value to be evaluated.
 一方、図10中のステップS54において、評価対象の属性が車両でないと判定する場合(ステップS54)、演算部31aは、ステップS56へ進み、歩行者用演算処理を行う。演算部31aは、歩行者用演算処理において評価対象の評価値を求める(ステップS56)。 On the other hand, when it is determined in step S54 in FIG. 10 that the attribute to be evaluated is not a vehicle (step S54), the calculation unit 31a proceeds to step S56 and performs a pedestrian calculation process. The computing unit 31a obtains an evaluation value to be evaluated in the pedestrian computation process (step S56).
 図13は、図10中の歩行者用演算処理の一例を示すフローチャートである。
 図13中、ステップ61からステップS66までは、評価対象が車両であるか歩行者であるかの相違だけで、図11と同様の処理である。よって、ステップ61からステップS66については説明を省略する。
FIG. 13 is a flowchart showing an example of the pedestrian calculation process in FIG.
In FIG. 13, Step 61 to Step S <b> 66 are the same processes as those in FIG. 11 except for whether the evaluation target is a vehicle or a pedestrian. Therefore, description of step 61 to step S66 is omitted.
 図13中、ステップS65又はステップS66の処理を終えると、演算部31aは、ステップS82に進む。
 演算部31aは、ステップ82において、衝突予測対象が車両か否かを判定する(ステップS82)。
 衝突予測対象(の移動体)が車両であると判定する場合、演算部31aは、ステップS83へ進み、評価対象である歩行者7の状況判定を行い、歩行者用演算処理を終える。
 ここで、評価対象である歩行者7の状況判定処理は、図12と同様である。
In FIG. 13, when the process of step S65 or step S66 is completed, the arithmetic unit 31a proceeds to step S82.
In step 82, the calculation unit 31a determines whether or not the collision prediction target is a vehicle (step S82).
When it determines with a collision prediction object (its mobile body) being a vehicle, the calculating part 31a progresses to step S83, performs the situation determination of the pedestrian 7 which is an evaluation object, and complete | finishes the calculation process for pedestrians.
Here, the situation determination process of the pedestrian 7 to be evaluated is the same as in FIG.
 一方、衝突予測対象(の移動体)が車両でないと判定する場合、演算部31aは、評価対象の歩行者7の状況判定を行うことなく歩行者用演算処理を終える。
 なお、歩行者用演算処理においては、衝突予測時間に応じた評価値に関するルールや、各判定によって評価値に加算される加算値は、歩行者であることを考慮して、車両用演算処理と異なる値に設定される。
On the other hand, when it is determined that the collision prediction target (the moving body) is not a vehicle, the calculation unit 31a finishes the pedestrian calculation process without determining the situation of the evaluation target pedestrian 7.
In the calculation process for pedestrians, the rule regarding the evaluation value according to the collision prediction time and the addition value added to the evaluation value by each determination are the calculation process for the vehicle in consideration of being a pedestrian. Set to a different value.
 なお、演算部31aは、車両用演算処理を示す図11中のステップS67において、衝突予測対象が歩行者か否かを判定し、衝突予測対象(の移動体)が歩行者7である場合のみ、衝突予測対象である歩行者7の状況判定を行う。
 また、同様に演算部31aは、歩行者用演算処理を示す図13中のステップS82において、衝突予測対象が車両か否かを判定し、衝突予測対象(の移動体)が車両であると判定する場合のみ、評価対象である歩行者7の状況判定を行う。
Note that the calculation unit 31a determines whether or not the collision prediction target is a pedestrian in step S67 in FIG. 11 showing the vehicle calculation process, and only when the collision prediction target (the moving body) is the pedestrian 7. Then, the situation of the pedestrian 7 that is a collision prediction target is determined.
Similarly, in step S82 in FIG. 13 showing the pedestrian calculation process, the calculation unit 31a determines whether or not the collision prediction target is a vehicle, and determines that the collision prediction target (the moving body) is a vehicle. Only when it does, the situation determination of the pedestrian 7 which is an evaluation object is performed.
 このように、演算部31aは、評価対象、及び、評価対象に対して衝突すると予測される移動体のいずれか一方が歩行者である場合、その歩行者に関する状況を取得し、取得した歩行者7の状況に応じた加算値を評価値に加味する。
 この場合、歩行者特有の状況を、評価値に反映でき、後述する評価対象への情報提供の実行判定に反映させることができる。
As described above, when either one of the evaluation object and the moving body predicted to collide with the evaluation object is a pedestrian, the calculation unit 31a acquires the situation related to the pedestrian and acquires the acquired pedestrian. 7 is added to the evaluation value.
In this case, the situation unique to the pedestrian can be reflected in the evaluation value, and can be reflected in the execution determination for providing information to the evaluation target described later.
 図10に戻って、ステップS55の車両用演算処理、又はステップS56の歩行者用演算処理によって評価対象の評価値を求めると、演算部31aは、ステップS57へ進み、求めた評価値を評価値データベース34bへ登録する(ステップS57)。 Returning to FIG. 10, when the evaluation value of the evaluation target is obtained by the vehicle calculation process of step S55 or the pedestrian calculation process of step S56, the calculation unit 31a proceeds to step S57 and uses the calculated evaluation value as the evaluation value. Registration in the database 34b (step S57).
 演算部31aは、図10中のステップS54からステップS57までの処理を、特定した評価対象に対して順次処理し、評価対象の全てを処理するまで処理を繰り返す。
 演算部31aは、特定した評価対象の全てについて評価値を求めデータベース34bへ登録すると、再度、ステップS51に戻り、同様の処理を繰り返す。
The calculation unit 31a sequentially performs the processing from step S54 to step S57 in FIG. 10 on the specified evaluation target, and repeats the processing until all the evaluation targets are processed.
When the calculation unit 31a obtains evaluation values for all the specified evaluation targets and registers them in the database 34b, the calculation unit 31a returns to step S51 again and repeats the same processing.
 よって、演算部31aは、演算処理を繰り返すことで、特定した評価対象それぞれの評価値の算出及び登録を繰り返し実行し、評価値データベース34bの登録内容を随時更新する。 Therefore, the calculation unit 31a repeatedly calculates and registers the evaluation value of each specified evaluation target by repeating the calculation process, and updates the registration content of the evaluation value database 34b as needed.
 図14は、評価値データベース34bの一例を示す図である。
 図14に示すように、評価値データベース34bには、評価対象の移動体IDと、評価対象以外の移動体の評価値とが対応付けられて登録されている。
FIG. 14 is a diagram illustrating an example of the evaluation value database 34b.
As shown in FIG. 14, in the evaluation value database 34b, the mobile object ID to be evaluated and the evaluation values of mobile objects other than the evaluation object are registered in association with each other.
 評価値データベース34bには、評価対象の移動体IDの欄、車両ID(携帯ID)の欄、及び評価対象以外の移動体の評価値の欄が設けられている。
 評価対象の移動体IDの欄には、評価対象として特定された移動体の移動体IDが登録されている。
 また、車両ID(携帯ID)の欄には、評価対象の移動体が有する移動端末歩行者端末70又は車載装置50の車両ID(携帯ID)が登録されている。
The evaluation value database 34b is provided with a mobile object ID field to be evaluated, a vehicle ID (mobile ID) field, and a mobile object evaluation value field other than the evaluation object.
The mobile object ID of the mobile object specified as the evaluation object is registered in the column of the evaluation object mobile object ID.
In the column of vehicle ID (mobile ID), the vehicle ID (mobile ID) of the mobile terminal pedestrian terminal 70 or the in-vehicle device 50 included in the mobile object to be evaluated is registered.
 評価対象以外の移動体の評価値の欄には、評価対象以外の移動体それぞれの移動体IDの欄が含まれている。これにより、評価対象以外の移動体の評価値の欄には、複数の移動体それぞれの評価値が登録される。
 上述したように、衝突予測対象以外の移動体に対する評価値は「0」に設定される。
 よって、評価対象以外の移動体の評価値に「0」以外の値が登録されている評価対象以外の移動体は、その評価対象の衝突予測対象であることを示している。
The column of the evaluation value of the mobile body other than the evaluation target includes a mobile body ID column of each mobile body other than the evaluation target. Thereby, the evaluation value of each of the plurality of mobile objects is registered in the column of the evaluation value of the mobile object other than the evaluation object.
As described above, the evaluation value for the moving object other than the collision prediction target is set to “0”.
Therefore, a mobile body other than the evaluation target in which a value other than “0” is registered as the evaluation value of the mobile body other than the evaluation target indicates that the evaluation target is a collision prediction target.
 例えば、図14中、移動体IDが「1006」である評価対象の評価値において、評価対象以外の移動体の評価値の欄のうち、移動体IDが「1004」に対応する欄には評価値として「500」が登録され、それ以外には「0」が登録されている。このことより、移動体IDが「1006」である評価対象の衝突予測対象として、移動体IDが「1004」の移動体が特定されていることが判る。
 このように、評価値データベース34bを参照することで、各評価対象の衝突予測対象を特定することができる。
For example, in FIG. 14, in the evaluation value of the evaluation target with the mobile object ID “1006”, the column corresponding to “1004” in the mobile object ID among the evaluation value fields of the mobile objects other than the evaluation object is evaluated. “500” is registered as a value, and “0” is registered in other cases. From this, it can be seen that the moving object with the moving object ID “1004” is specified as the evaluation target collision prediction target with the moving object ID “1006”.
Thus, the collision prediction object of each evaluation object can be specified by referring to the evaluation value database 34b.
〔評価値の判定処理〕
 図15は、判定部31bによる判定処理の一例を示すフローチャートである。
 図15に示すように、判定部31bは、評価値データベース34bを参照し、評価値が予め設定された閾値以上である評価対象があるか否かを判定する(ステップS85)。
 ステップS85において、評価値が閾値以上である評価対象がないと判定すると、判定部31bは、さらにステップS85を繰り返す。よって、判定部31bは、評価値が閾値以上である評価対象があると判定するまで、ステップS85を繰り返す。
[Evaluation value judgment process]
FIG. 15 is a flowchart illustrating an example of a determination process performed by the determination unit 31b.
As illustrated in FIG. 15, the determination unit 31b refers to the evaluation value database 34b and determines whether there is an evaluation target whose evaluation value is equal to or greater than a preset threshold value (step S85).
If it determines with there being no evaluation object whose evaluation value is more than a threshold value in step S85, the determination part 31b will repeat step S85 further. Therefore, the determination unit 31b repeats Step S85 until it is determined that there is an evaluation target whose evaluation value is equal to or greater than the threshold value.
 ステップS85において、評価値が閾値以上である評価対象があると判定すると、判定部31bは、ステップS86へ進み、その評価対象へ、衝突予測対象の衝突予測結果に関する情報を通知することを決定し、ステップS85へ戻る。 If it is determined in step S85 that there is an evaluation object whose evaluation value is equal to or greater than the threshold value, the determination unit 31b proceeds to step S86 and determines to notify the evaluation object of information related to the collision prediction result of the collision prediction object. Return to step S85.
 判定部31bは、各評価対象の評価値を参照し、評価値が閾値以上の評価対象が複数あれば、その複数すべての評価対象へ、衝突予測対象の衝突予測結果に関する情報の通知を決定する。
 このように、判定部31bは、評価対象へ、評価対象それぞれの予測結果に関する情報を通知するか否かを、評価値に基づいて評価対象ごとに判定する。
The determination unit 31b refers to the evaluation value of each evaluation object, and if there are a plurality of evaluation objects whose evaluation values are equal to or greater than the threshold value, determines the notification of information related to the collision prediction result of the collision prediction object to all the evaluation objects. .
As described above, the determination unit 31b determines, for each evaluation target, whether or not to notify the evaluation target of information related to the prediction result of each evaluation target based on the evaluation value.
 すなわち、本実施形態では、衝突予測結果に関する情報(予測交通状況に関する情報)を通知するか否かを、評価対象(歩行者端末70や車載装置50又はこれらを有している移動体)それぞれの予測結果の評価値に基づいて評価対象ごとに判定するので、必要な情報を適切に各評価対象へ情報提供することができる。
 また、評価対象それぞれの衝突予測の予測結果の評価値を求めるために、複数の移動体に関する動的情報が重畳された動的情報マップM1を用いるので、移動端末が搭載されていない移動体も含めて予測交通状況の評価値を得ることができ、各評価対象において、適切に予測された交通状況を評価値として表すことができる。
 このように、上記構成によれば、適切に衝突予測された予測結果に関する情報を適切に各評価対象へ情報提供することができる。
That is, in this embodiment, whether or not to notify information related to the collision prediction result (information related to the predicted traffic situation) is determined for each of the evaluation targets (the pedestrian terminal 70, the in-vehicle device 50, or the mobile body having these). Since it determines for every evaluation object based on the evaluation value of a prediction result, required information can be appropriately provided to each evaluation object.
In addition, since the dynamic information map M1 on which dynamic information on a plurality of moving objects is superimposed is used in order to obtain the evaluation value of the prediction result of the collision prediction of each evaluation target, there is also a moving object on which no mobile terminal is mounted. In addition, the evaluation value of the predicted traffic situation can be obtained, and the traffic situation appropriately predicted for each evaluation target can be expressed as the evaluation value.
Thus, according to the said structure, the information regarding the prediction result appropriately collided can be appropriately provided to each evaluation object.
〔通知処理〕
 判定部31bが、評価対象へ衝突予測結果に関する情報の通知を決定すると、通知部31cは、判定部31bが通知を決定した評価対象へ、当該評価対象と衝突予測対象との間の衝突予測結果に関する情報を通知する。
 これにより、評価値に基づいて衝突予測の予測結果に関する情報が必要と判定された移動端末のみに情報提供することができる。
 なお、通知部31cが評価対象へ通知する衝突予測結果に関する情報としては、衝突予測対象の属性や、衝突予測対象が接近してくる方向、衝突予測時間等が含まれる。
[Notification processing]
When the determination unit 31b determines to notify the evaluation target of information related to the collision prediction result, the notification unit 31c determines the collision prediction result between the evaluation target and the collision prediction target to the evaluation target for which the determination unit 31b has determined the notification. Notify information about.
Thereby, it is possible to provide information only to the mobile terminal that is determined to need information on the prediction result of the collision prediction based on the evaluation value.
The information related to the collision prediction result notified to the evaluation target by the notification unit 31c includes the attribute of the collision prediction target, the direction in which the collision prediction target approaches, the collision prediction time, and the like.
 通知部31cによる通知を受け付けた評価対象の移動端末(歩行者端末70及び車載装置50)は、当該移動端末のユーザへ向けて、通知された予測結果に関する情報を出力する。 The mobile terminal (the pedestrian terminal 70 and the in-vehicle device 50) to be evaluated that has received the notification by the notification unit 31c outputs information on the notified prediction result to the user of the mobile terminal.
〔シナリオ1について〕
 次に、本実施形態の情報提供システムの動作について、道路上で想定されるシナリオに従って説明する。
 図16は、シナリオ1に係る交差点周辺の状況を示した図である。
 図16において、歩行者7A,7Bは、横断歩道Pを通過した直後の位置に駐車されている車両5Cから降車して横断歩道Pを横断している。また、歩行者7Aは大人であり、歩行者7Bは子供である。
 歩行者7A,7Bが横断歩道Pを横断し始めたタイミングにおいて横断歩道Pの信号の灯色は、青色の点滅であった。
[About scenario 1]
Next, the operation of the information providing system of the present embodiment will be described according to a scenario assumed on the road.
FIG. 16 is a diagram illustrating a situation around an intersection according to scenario 1. FIG.
In FIG. 16, pedestrians 7 </ b> A and 7 </ b> B get off the vehicle 5 </ b> C parked at a position immediately after passing the pedestrian crossing P and cross the pedestrian crossing P. The pedestrian 7A is an adult, and the pedestrian 7B is a child.
At the timing when the pedestrians 7A and 7B started to cross the pedestrian crossing P, the light color of the signal of the pedestrian crossing P was flashing blue.
 一方、歩行者7A,7Bが横断歩道Pを渡り始めたタイミングにおいては、車両5Aが走行する方路の信号の灯色は赤色であるが、横断歩道Pの信号が青色の点滅であるため、横断歩道Pに接近する車両5Aは、もうすぐ青色に変わることを認識している。このため車両5Aは、交差点を停止せずに通過しようと試みているとする。
 なお、車両5Aは、車両5Cの存在によって歩行者7A,7Bが目視できないものとする。
 さらに、車両5Aの後方には、さらに車両5Bが走行している。
On the other hand, at the timing when the pedestrians 7A and 7B start crossing the pedestrian crossing P, the light color of the signal of the route on which the vehicle 5A travels is red, but the signal of the pedestrian crossing P is blinking blue. The vehicle 5A approaching the pedestrian crossing P recognizes that it will soon turn blue. For this reason, it is assumed that the vehicle 5A attempts to pass through the intersection without stopping.
It is assumed that the pedestrians 7A and 7B cannot see the vehicle 5A due to the presence of the vehicle 5C.
Further, a vehicle 5B further travels behind the vehicle 5A.
 なお、車両5A,5B,5C、歩行者7A,7Bは、システムによって移動体として動的情報マップM1及び移動体データベース34aに登録されているものとする。
 また、車両5A,5Bは、車載装置50を搭載しており、歩行者7A,7Bは歩行者端末70を携帯しているものとする。
The vehicles 5A, 5B, 5C and pedestrians 7A, 7B are registered as moving bodies in the dynamic information map M1 and the moving body database 34a by the system.
Further, it is assumed that the vehicles 5A and 5B are equipped with the in-vehicle device 50, and the pedestrians 7A and 7B carry the pedestrian terminal 70.
 ここで、横断歩道Pの途中で、横断歩道Pの信号の灯色が赤色に変わり、歩行者7A,7Bが、そのまま急いで横断歩道Pを渡っているとする。 Here, it is assumed that in the middle of the pedestrian crossing P, the signal color of the pedestrian crossing P changes to red, and the pedestrians 7A and 7B hurry to cross the pedestrian crossing P as they are.
 このとき、車両5Aと、歩行者7A,7Bとは、横断歩道Pで衝突の可能性がある。よって、エッジサーバ3(の演算部31a)は、車両5Aの衝突予測対象として、歩行者7A,7Bを特定するとともに、歩行者7A,7Bの衝突予測対象として、車両5Aを特定する。また、歩行者7A,7Bは、属性が子供(歩行者7Bのみ)であり、信号無視をしている。さらに、車両5Aと歩行者7A,7Bとの間に死角要因である車両5Cが存在する。 At this time, the vehicle 5A and the pedestrians 7A and 7B may collide at the pedestrian crossing P. Therefore, the edge server 3 (the computing unit 31a thereof) specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B. The pedestrians 7A and 7B have a child attribute (only the pedestrian 7B) and ignore the signal. Furthermore, a vehicle 5C that is a blind spot factor exists between the vehicle 5A and the pedestrians 7A and 7B.
 このような場合、エッジサーバ3は、車両5Aを評価対象としたときの評価値を求める場合、衝突予測時間の他、歩行者の状況判定も加味する。本シナリオでは、死角要因、歩行者の属性、及び信号無視によって評価値に加算値が加算される。
 予測結果を通知するか否かの判定に用いられる前記閾値は、本シナリオのように、安全性を阻害する要因が重なるような場合における評価値よりも小さく設定される。よって、本シナリオのような場合では、車両5Aにおける歩行者7A,7Bの評価値は前記閾値よりも大きい値となる。このため、エッジサーバ3は、車両5Aにおける歩行者7A,7Bの衝突予測結果に関する情報を車両5Aへ通知する。
In such a case, when the edge server 3 obtains an evaluation value when the vehicle 5A is an evaluation object, the pedestrian situation determination is taken into consideration in addition to the collision prediction time. In this scenario, an additional value is added to the evaluation value due to blind spot factor, pedestrian attributes, and signal ignorance.
The threshold value used for determining whether or not to notify the prediction result is set smaller than the evaluation value in the case where factors that inhibit safety overlap as in this scenario. Therefore, in the case of this scenario, the evaluation values of the pedestrians 7A and 7B in the vehicle 5A are larger than the threshold value. For this reason, the edge server 3 notifies the information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A to the vehicle 5A.
 また、エッジサーバ3は、歩行者7A,7Bを評価対象としたときの評価値を求める場合においても、衝突予測時間の他、歩行者の状況判定も加味する。よって、歩行者7A,7Bにおける車両5Aの評価値が前記閾値よりも大きい値となり、エッジサーバ3は、歩行者7A,7Bにおける車両5Aの衝突予測結果に関する情報を歩行者7A,7Bへ通知する。 Moreover, the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction time when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 notifies the pedestrians 7A and 7B of the information related to the collision prediction result of the vehicle 5A in the pedestrians 7A and 7B. .
 さらに、車両5Bにおいても、車両5Aが横断歩道Pに近づくに従って速度を落とし、両車両が接近すると、エッジサーバ3は、車両5Bの衝突予測対象として車両5Aを特定する。衝突予測の結果、衝突予測時間が短ければ、評価値が大きな値に設定される。この結果、エッジサーバ3は、車両5Bにおける車両5Aの衝突予測結果に関する情報を車両5Bへ通知する。 Furthermore, also in the vehicle 5B, the speed decreases as the vehicle 5A approaches the pedestrian crossing P, and when both vehicles approach, the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B. As a result of the collision prediction, if the collision prediction time is short, the evaluation value is set to a large value. As a result, the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
 このように、エッジサーバ3は、必要な情報を適切に各移動端末へ情報提供することができる。
 車両5A,5Bの車載装置50、歩行者7A,7Bの歩行者端末70は、エッジサーバ3からの通知に基づいて、衝突予測結果に関する情報を自装置のユーザへ出力する。
As described above, the edge server 3 can appropriately provide necessary information to each mobile terminal.
The in-vehicle device 50 of the vehicles 5A and 5B and the pedestrian terminal 70 of the pedestrians 7A and 7B output information on the collision prediction result to the user of the own device based on the notification from the edge server 3.
 図16中、車両5Aの車載装置50の出力画面V1には、自車両前方の横断歩道Pの右側から歩行者が現れることを示す表示D1や、その歩行者の進行方向を示す矢印D2等が表示される。
 これにより、エッジサーバ3は、前方の横断歩道Pの右側から歩行者が現れることを事前に車両5Aのユーザに認識させることができる。
 なお、ここでは、歩行者7A,7Bを特定することなく表示しているが、例えば、歩行者7の属性が子供である場合と、大人である場合とで表示方法を異なるようにしてもよい。歩行者が子供の場合の方が、より注意が必要だからである。
In FIG. 16, on the output screen V1 of the in-vehicle device 50 of the vehicle 5A, a display D1 indicating that a pedestrian appears from the right side of the pedestrian crossing P in front of the host vehicle, an arrow D2 indicating the traveling direction of the pedestrian, and the like. Is displayed.
Thereby, the edge server 3 can make the user of the vehicle 5A recognize in advance that a pedestrian appears from the right side of the pedestrian crossing P ahead.
Here, the pedestrians 7A and 7B are displayed without specifying them. However, for example, the display method may be different depending on whether the attribute of the pedestrian 7 is a child or an adult. . This is because pedestrians need more attention if they are children.
 つまり、本システムでは、衝突予測対象の属性に応じて、衝突予測結果に関する情報の出力態様は、異なるように制御されてもよい。これにより、衝突予測対象の属性の特徴に応じた出力態様でユーザへ向けて情報を出力することができる。 That is, in this system, the output mode of the information related to the collision prediction result may be controlled differently according to the attribute of the collision prediction target. Thereby, information can be output to a user in the output mode according to the feature of the attribute of a collision prediction object.
 また、歩行者7A,7Bの歩行者端末70の出力画面V2には、前方の横断歩道Pの左側から車両Aが現れることを示す表示D3や、その車両5Aの進行方向を示す矢印D4等が表示される。
 これにより、エッジサーバ3は、前方の横断歩道Pの左側から車両が現れることを事前に歩行者7A,7Bに認識させることができる。
The output screen V2 of the pedestrian terminals 70 of the pedestrians 7A and 7B includes a display D3 indicating that the vehicle A appears from the left side of the front pedestrian crossing P, an arrow D4 indicating the traveling direction of the vehicle 5A, and the like. Is displayed.
Thereby, the edge server 3 can make the pedestrians 7A and 7B recognize in advance that the vehicle appears from the left side of the pedestrian crossing P ahead.
 また、車両5Bの車載装置50の出力画面V3には、自車両前方を走行する車両5Aに対する注意を促すことを表す表示D5等が表示される。
 これにより、エッジサーバ3は、前方を走行する車両5Aが停止して接近することを事前に車両5Bのユーザに認識させることができる。
In addition, on the output screen V3 of the in-vehicle device 50 of the vehicle 5B, a display D5 or the like indicating a warning to the vehicle 5A traveling in front of the host vehicle is displayed.
Thereby, the edge server 3 can make the user of the vehicle 5B recognize in advance that the vehicle 5A traveling ahead stops and approaches.
 このように、エッジサーバ3は、車両5A,5Bの車載装置50、歩行者7A,7Bの歩行者端末70にユーザへの出力を行わせることで、各移動体同士の衝突を回避させることができる。 In this way, the edge server 3 can avoid collision between the moving bodies by causing the in-vehicle device 50 of the vehicles 5A and 5B and the pedestrian terminal 70 of the pedestrians 7A and 7B to output to the user. it can.
 なお、歩行者端末70及び車載装置50による衝突予測結果に関する情報の出力は、歩行者端末70及び車載装置50の制御部71及び制御部51が有する出力制御部によって制御される。
 また、エッジサーバ3の制御部31が、歩行者端末70及び車載装置50によるユーザへ向けた出力を制御可能な出力制御部を有している場合には、エッジサーバ3の出力制御部が、歩行者端末70及び車載装置50によるユーザへの出力を制御してもよい。
In addition, the output of the information regarding the collision prediction result by the pedestrian terminal 70 and the vehicle-mounted apparatus 50 is controlled by the output control part which the control part 71 and the control part 51 of the pedestrian terminal 70 and the vehicle-mounted apparatus 50 have.
Moreover, when the control part 31 of the edge server 3 has an output control part which can control the output toward the user by the pedestrian terminal 70 and the vehicle-mounted apparatus 50, the output control part of the edge server 3 is You may control the output to the user by the pedestrian terminal 70 and the vehicle-mounted apparatus 50. FIG.
〔シナリオ2について〕
 図17は、シナリオ2に係る交差点周辺の状況を示した図である。
 図17中、車両5A,5B、歩行者7A,7Bの設定は、シナリオ1と同様である。また、シナリオ2には、シナリオ1の車両5Cがいない。
 シナリオ2では、歩行者7A,7Bが横断歩道Pを一般的な歩行速度(3.6km毎時)よりも低い速度で渡っている。
[About scenario 2]
FIG. 17 is a diagram illustrating a situation around an intersection according to scenario 2.
In FIG. 17, the settings of the vehicles 5A and 5B and the pedestrians 7A and 7B are the same as in the scenario 1. In scenario 2, there is no scenario 5 vehicle 5C.
In scenario 2, the pedestrians 7A and 7B cross the pedestrian crossing P at a speed lower than a general walking speed (3.6 km / hour).
 歩行者7A,7Bがゆっくりと横断歩道Pを渡っているため、歩行者7A,7Bが横断歩道Pを横断し始めたタイミングにおいて横断歩道Pの信号の灯色は、青色の点滅であったが、横断歩道Pの途中で、横断歩道Pの信号の灯色が赤色に変わり、歩行者7A,7Bは、そのままの歩行速度でゆっくりと横断歩道Pを渡っているとする。 Since the pedestrians 7A and 7B slowly cross the pedestrian crossing P, the signal color of the pedestrian crossing P was flashing blue at the timing when the pedestrians 7A and 7B started to cross the pedestrian crossing P. In the middle of the pedestrian crossing P, the signal color of the pedestrian crossing P turns red, and the pedestrians 7A and 7B slowly cross the pedestrian crossing P at the same walking speed.
 この場合、シナリオ1のように、車両5Aと歩行者7A,7Bとの間に死角要因はない。
 また、歩行者7A,7Bはゆっくりと横断歩道Pを渡っているため、青色の点滅であった横断歩道Pの信号の灯色が、横断歩道Pの途中で赤色に変わり、歩行者7A,7Bがそのままの歩行速度でゆっくりと横断歩道Pを渡っているとする。
 ここで、車両5Aと、歩行者7A,7Bとは、横断歩道上で衝突の可能性がある。よって、エッジサーバ3は、車両5Aの衝突予測対象として、歩行者7A,7Bを特定するとともに、歩行者7A,7Bの衝突予測対象として、車両5Aを特定する。
In this case, as in scenario 1, there is no blind spot factor between the vehicle 5A and the pedestrians 7A and 7B.
Moreover, since the pedestrians 7A and 7B slowly cross the pedestrian crossing P, the light color of the signal of the pedestrian crossing P, which was flashing in blue, turns red in the middle of the pedestrian crossing P, and the pedestrians 7A and 7B Is slowly crossing the pedestrian crossing P at the same walking speed.
Here, the vehicle 5A and the pedestrians 7A and 7B may collide on the pedestrian crossing. Therefore, the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A, and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B.
 このとき、エッジサーバ3は、車両5Aを評価対象としたときの評価値を求める場合、衝突予測時間から求められる評価値に、歩行者の属性、歩行者の速度、及び信号無視による加算値を加算する。
 これにより、車両5Aにおける歩行者7A,7Bの評価値は前記閾値よりも大きい値となり、エッジサーバ3は、車両5Aにおける歩行者7A,7Bの衝突予測結果に関する情報を車両5Aへ通知する。
At this time, when the edge server 3 obtains an evaluation value when the vehicle 5A is an evaluation object, the pedestrian attribute, the speed of the pedestrian, and an addition value obtained by ignoring the signal are added to the evaluation value obtained from the collision prediction time. to add.
Thereby, the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
 また、エッジサーバ3は、歩行者7A,7Bを評価対象としたときの評価値を求める場合においても、衝突予測の他、歩行者の状況判定も加味する。よって、歩行者7A,7Bにおける車両5Aの評価値が前記閾値よりも大きい値となり、エッジサーバ3は、歩行者7A,7Bにおける車両5Aの衝突予測の予測結果に関する情報を歩行者7A,7Bへ通知する。 In addition, the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 sends the information regarding the prediction result of the collision prediction of the vehicle 5A in the pedestrians 7A and 7B to the pedestrians 7A and 7B. Notice.
 さらに、車両5Bにおいても、車両5Aが横断歩道Pに近づくに従って速度を落とし、両車両が接近すると、エッジサーバ3は、車両5Bの衝突予測対象として車両5Aを特定する。衝突予測の結果、衝突予測時間が短ければ、評価値が大きな値に設定される。この結果、エッジサーバ3は、車両5Bにおける車両5Aの衝突予測結果に関する情報を車両5Bへ通知する。 Furthermore, also in the vehicle 5B, the speed decreases as the vehicle 5A approaches the pedestrian crossing P, and when both vehicles approach, the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B. As a result of the collision prediction, if the collision prediction time is short, the evaluation value is set to a large value. As a result, the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
 以上によって、車両5A,5Bの車載装置50、歩行者7A,7Bの歩行者端末70は、エッジサーバ3からの通知に基づいて、衝突予測結果に関する情報を自装置のユーザへ出力する。
 これによって、エッジサーバ3は、前方の横断歩道Pの右側から歩行者が現れることを事前に車両5Aのユーザに認識させることができる。
 また、エッジサーバ3は、前方の横断歩道Pの左側から車両が現れることを事前に歩行者7A,7Bに認識させることができる。
As described above, the in-vehicle device 50 of the vehicles 5A and 5B and the pedestrian terminal 70 of the pedestrians 7A and 7B output information on the collision prediction result to the user of the own device based on the notification from the edge server 3.
Thereby, the edge server 3 can make the user of the vehicle 5A recognize in advance that a pedestrian appears from the right side of the pedestrian crossing P ahead.
Further, the edge server 3 can make the pedestrians 7A and 7B recognize in advance that a vehicle appears from the left side of the front crosswalk P.
 これにより、エッジサーバ3は、車両5A,5Bの車載装置50、歩行者7A,7Bの歩行者端末70にユーザへの出力を行わせることで、各移動体同士の衝突を回避させることができる。 Thereby, the edge server 3 can avoid the collision of each moving body by making the vehicle-mounted apparatus 50 of vehicle 5A, 5B and the pedestrian terminal 70 of pedestrian 7A, 7B perform an output to a user. .
〔シナリオ3について〕
 図18は、シナリオ3に係る交差点周辺の状況を示した図である。
 図18において、歩行者7A,7Bは、歩道Hを歩いていたところ、歩道H上に障害物G1があり、障害物G1を避けて車道にはみ出して歩行している。また、歩行者7Aは大人であり、歩行者7Bは子供である。
[About scenario 3]
FIG. 18 is a diagram illustrating a situation around an intersection according to scenario 3.
In FIG. 18, pedestrians 7A and 7B walk along the sidewalk H, and there is an obstacle G1 on the sidewalk H. The pedestrians 7A and 7B are walking on the roadway avoiding the obstacle G1. The pedestrian 7A is an adult, and the pedestrian 7B is a child.
 ここで、車両5Aと、歩行者7A,7Bとは、車道上で衝突の可能性がある。よって、エッジサーバ3は、車両5Aの衝突予測対象として、歩行者7A,7Bを特定するとともに、歩行者7A,7Bの衝突予測対象として、車両5Aを特定する。また、歩行者7A,7Bは、属性が子供(歩行者7Bのみ)であり、歩道を歩行していない。 Here, there is a possibility of collision between the vehicle 5A and the pedestrians 7A and 7B on the roadway. Therefore, the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A, and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B. In addition, the attributes of the pedestrians 7A and 7B are children (only the pedestrian 7B) and do not walk on the sidewalk.
 このとき、エッジサーバ3は、車両5Aを評価対象としたときの歩行者7A,7Bの評価値を求める場合、衝突予測時間から求められる評価値に、歩行者の属性、及び歩行者が歩行している場所(横断歩道又は歩道を歩行していないか否か)による加算値を加算する。
 これにより、車両5Aにおける歩行者7A,7Bの評価値は前記閾値よりも大きい値となり、エッジサーバ3は、車両5Aにおける歩行者7A,7Bの衝突予測結果に関する情報を車両5Aへ通知する。
At this time, when the edge server 3 obtains the evaluation value of the pedestrians 7A and 7B when the vehicle 5A is the evaluation target, the attribute of the pedestrian and the pedestrian walk to the evaluation value obtained from the predicted collision time. Add the value depending on where you are (whether you are walking on a pedestrian crossing or sidewalk).
Thereby, the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
 また、エッジサーバ3は、歩行者7A,7Bを評価対象としたときの評価値を求める場合においても、衝突予測の他、歩行者の状況判定も加味する。よって、歩行者7A,7Bにおける車両5Aの評価値が前記閾値よりも大きい値となり、エッジサーバ3は、歩行者7A,7Bにおける車両5Aの衝突予測結果に関する情報を歩行者7A,7Bへ通知する。 In addition, the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 notifies the pedestrians 7A and 7B of the information related to the collision prediction result of the vehicle 5A in the pedestrians 7A and 7B. .
 また、車両5Aが、歩行者7A,7Bを避けて反対車線側にはみ出そうとすると、反対車線を走行している車両5Bは、車両5Aとの間で衝突の可能性がある。よって、この場合、エッジサーバ3は、車両5Bの衝突予測対象として、車両5Aを特定する。また、車両5Bと車両5Aとの間に死角要因である車両5Dが存在する。 Also, if the vehicle 5A tries to protrude to the opposite lane side while avoiding the pedestrians 7A and 7B, the vehicle 5B traveling in the opposite lane may collide with the vehicle 5A. Therefore, in this case, the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B. Further, a vehicle 5D that is a blind spot factor exists between the vehicle 5B and the vehicle 5A.
 エッジサーバ3は、車両5Bを評価対象としたときの評価値を求める場合、衝突予測時間から求められる評価値に、死角要因の有無による加算値を加算する。
 車両5Bにおける車両5Aの評価値が前記閾値よりも大きい値となれば、エッジサーバ3は、車両5Bにおける車両5Aの衝突予測結果に関する情報を車両5Bへ通知する。
When the edge server 3 obtains an evaluation value when the vehicle 5B is an evaluation object, the edge server 3 adds an addition value based on the presence or absence of a blind spot factor to the evaluation value obtained from the collision prediction time.
If the evaluation value of the vehicle 5A in the vehicle 5B is larger than the threshold value, the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
 また、車両5Cにおいても、車両5Bが車両5Aのはみ出しによって速度を落とし、両車両が接近すると、エッジサーバ3は、車両Cの衝突予測対象として車両5Bを特定する。衝突予測の結果、衝突予測時間が短ければ、評価値が大きな値に設定される。この結果、エッジサーバ3は、車両5Cにおける車両5Bの衝突予測結果に関する情報を車両5Cへ通知する。 Also, in the vehicle 5C, when the vehicle 5B reduces the speed due to the protrusion of the vehicle 5A and both vehicles approach, the edge server 3 specifies the vehicle 5B as a collision prediction target of the vehicle C. As a result of the collision prediction, if the collision prediction time is short, the evaluation value is set to a large value. As a result, the edge server 3 notifies the vehicle 5C of information related to the collision prediction result of the vehicle 5B in the vehicle 5C.
 これにより、エッジサーバ3は、車両5A,5B,5Cの車載装置50、歩行者7A,7Bの歩行者端末70にユーザへの出力を行わせることで、各移動体同士の衝突を回避させることができる。 Thereby, the edge server 3 makes the in-vehicle device 50 of the vehicles 5A, 5B, and 5C and the pedestrian terminal 70 of the pedestrians 7A and 7B perform the output to the user, thereby avoiding collision between the moving bodies. Can do.
〔シナリオ4について〕
 図19は、シナリオ4に係る交差点周辺の状況を示した図である。
 図19において、歩行者7A,7Bは、歩道Hを歩いていたところ、停車している車両5Cと、車両5Dとの間をすり抜けて横断歩道ではないところを歩行し車道を横断しようとしている。また、歩行者7Aは大人であり、歩行者7Bは子供である。
[About scenario 4]
FIG. 19 is a diagram illustrating a situation around an intersection according to scenario 4.
In FIG. 19, as pedestrians 7A and 7B walk along the sidewalk H, they are walking between the parked vehicle 5C and the vehicle 5D and are not crosswalks to cross the roadway. The pedestrian 7A is an adult, and the pedestrian 7B is a child.
 ここで、反対車線を走行する車両5Aと、歩行者7A,7Bとは、車道上で衝突の可能性がある。よって、エッジサーバ3は、車両5Aの衝突予測対象として、歩行者7A,7Bを特定するとともに、歩行者7A,7Bの衝突予測対象として、車両5Aを特定する。また、歩行者7A,7Bは、属性が子供(歩行者7Bのみ)であり、歩道及び横断歩道を歩行していない。さらに、車両5Aと歩行者7A,7Bとの間に死角要因である車両5Dが存在する。 Here, there is a possibility of collision between the vehicle 5A traveling in the opposite lane and the pedestrians 7A and 7B on the roadway. Therefore, the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A, and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B. The attributes of the pedestrians 7A and 7B are children (only the pedestrian 7B) and do not walk on the sidewalks and pedestrian crossings. Further, a vehicle 5D that is a blind spot factor exists between the vehicle 5A and the pedestrians 7A and 7B.
 このとき、エッジサーバ3は、車両5Aを評価対象としたときの歩行者7A,7Bの評価値を求める場合、衝突予測時間の他、歩行者の属性、歩行者が歩行している場所(横断歩道又は歩道を歩行していないか否か)、及び死角要因の有無によって評価値に加算値が加算される。
 これにより、車両5Aにおける歩行者7A,7Bの評価値は前記閾値よりも大きい値となり、エッジサーバ3は、車両5Aにおける歩行者7A,7Bの衝突予測結果に関する情報を車両5Aへ通知する。
At this time, when the edge server 3 calculates the evaluation value of the pedestrians 7A and 7B when the vehicle 5A is the evaluation target, in addition to the collision prediction time, the attribute of the pedestrian, the place where the pedestrian is walking (crossing) The added value is added to the evaluation value depending on whether there is a sidewalk or whether or not walking on the sidewalk and whether there is a blind spot factor.
Thereby, the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
 また、エッジサーバ3は、歩行者7A,7Bを評価対象としたときの評価値を求める場合においても、衝突予測の他、歩行者の状況判定も加味する。よって、歩行者7A,7Bにおける車両5Aの評価値が前記閾値よりも大きい値となり、エッジサーバ3は、歩行者7A,7Bにおける車両5Aの衝突予測結果に関する情報を歩行者7A,7Bへ通知する。 In addition, the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 notifies the pedestrians 7A and 7B of the information related to the collision prediction result of the vehicle 5A in the pedestrians 7A and 7B. .
 また、車両5Bにおいても、車両5Aが歩行者7A,7Bの車道横断によって速度を落とし、両車両が接近すると、エッジサーバ3は、車両5Bの衝突予測対象として車両5Aを特定する。衝突予測の結果、衝突予測時間が短ければ、評価値が大きな値に設定される。この結果、エッジサーバ3は、車両5Bにおける車両5Aの衝突予測結果に関する情報を車両5Bへ通知する。 Also in the vehicle 5B, when the vehicle 5A drops its speed due to the crossing of the roadway of the pedestrians 7A and 7B and both vehicles approach, the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B. As a result of the collision prediction, if the collision prediction time is short, the evaluation value is set to a large value. As a result, the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
 なお、本シナリオのように、車両5同士の間をすり抜ける移動体(歩行者)を検知する方法としては、路側センサ8による検知の他、歩行者がすり抜ける車両5に車載カメラ59を有する車載装置50が搭載されていれば、車載カメラ59によって検知することもできる。 In addition, as a method of detecting a moving body (pedestrian) that slips between the vehicles 5 as in this scenario, in-vehicle device that includes the in-vehicle camera 59 in the vehicle 5 through which the pedestrian slips, in addition to detection by the roadside sensor 8. If 50 is mounted, the vehicle-mounted camera 59 can also detect it.
〔シナリオ5について〕
 図20は、シナリオ5に係る交差点周辺の状況を示した図である。
 図20において、歩行者7A,7Bは、歩道Hを蛇行して歩いている。また、歩行者7Aは大人であり、歩行者7Bは子供である。
[About scenario 5]
FIG. 20 is a diagram illustrating a situation around an intersection according to scenario 5. In FIG.
In FIG. 20, pedestrians 7A and 7B meander along the sidewalk H and walk. The pedestrian 7A is an adult, and the pedestrian 7B is a child.
 歩行者7A,7Bが歩道Hを蛇行することで、車道にはみ出せば、車両5Aと、歩行者7A,7Bとは、車道上で衝突の可能性がある。よって、エッジサーバ3は、車両5Aの衝突予測対象として、歩行者7A,7Bを特定するとともに、歩行者7A,7Bの衝突予測対象として、車両5Aを特定する。また、歩行者7A,7Bは、属性が子供(歩行者7Bのみ)であり、車道をはみ出した場合、歩道を歩行していないことになる。 If the pedestrians 7A and 7B meander along the sidewalk H and protrude from the roadway, the vehicle 5A and the pedestrians 7A and 7B may collide on the roadway. Therefore, the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A, and specifies the vehicle 5A as the collision prediction targets of the pedestrians 7A and 7B. In addition, the attributes of the pedestrians 7A and 7B are children (only the pedestrian 7B), and when the pedestrians protrude from the roadway, they are not walking on the sidewalk.
 このとき、エッジサーバ3は、車両5Aを評価対象としたときの歩行者7A,7Bの評価値を求める場合、衝突予測時間から求められる評価値に、歩行者の属性、歩行者の歩行状態(蛇行しているか否か)、及び歩行者が歩行している場所(横断歩道又は歩道を歩行していないか否か)による加算値を加算する。
 これにより、車両5Aにおける歩行者7A,7Bの評価値は前記閾値よりも大きい値となり、エッジサーバ3は、車両5Aにおける歩行者7A,7Bの衝突予測結果に関する情報を車両5Aへ通知する。
At this time, when the edge server 3 obtains the evaluation value of the pedestrians 7A and 7B when the vehicle 5A is the evaluation target, the evaluation value obtained from the collision prediction time includes the attribute of the pedestrian, the walking state of the pedestrian ( Addition value depending on whether or not meandering and a place where a pedestrian is walking (whether or not walking on a pedestrian crossing or a sidewalk).
Thereby, the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
 また、エッジサーバ3は、歩行者7A,7Bを評価対象としたときの評価値を求める場合においても、衝突予測の他、歩行者の状況判定も加味する。よって、歩行者7A,7Bにおける車両5Aの評価値が前記閾値よりも大きい値となり、エッジサーバ3は、歩行者7A,7Bにおける車両5Aの衝突予測結果に関する情報を歩行者7A,7Bへ通知する。 In addition, the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 notifies the pedestrians 7A and 7B of the information related to the collision prediction result of the vehicle 5A in the pedestrians 7A and 7B. .
 また、車両5Aが、歩行者7A,7Bを避けて反対車線側にはみ出そうとすると、反対車線を走行している車両5Bは、車両5Aとの間で衝突の可能性がある。よって、この場合、エッジサーバ3は、車両5Bの衝突予測対象として、車両5Aを特定する。 Also, if the vehicle 5A tries to protrude to the opposite lane side while avoiding the pedestrians 7A and 7B, the vehicle 5B traveling in the opposite lane may collide with the vehicle 5A. Therefore, in this case, the edge server 3 specifies the vehicle 5A as a collision prediction target of the vehicle 5B.
 エッジサーバ3は、車両5Bを評価対象としたときの評価値を、歩行者7A,7Bとの間の衝突予測時間に基づいて求める。
 車両5Bにおける車両5Aの評価値が前記閾値よりも大きい値となれば、エッジサーバ3は、車両5Bにおける車両5Aの衝突予測結果に関する情報を車両5Bへ通知する。
The edge server 3 calculates | requires the evaluation value when the vehicle 5B is made into evaluation object based on the collision prediction time between pedestrians 7A and 7B.
If the evaluation value of the vehicle 5A in the vehicle 5B is larger than the threshold value, the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
〔シナリオ6について〕
 図21は、シナリオ6に係る交差点周辺の状況を示した図である。
 図21において、歩行者7A,7Bは、方路R1を横断する横断歩道Pを横断している。歩行者7A,7Bが横断歩道Pを横断し始めたタイミングにおいて横断歩道Pの信号の灯色は、青色の点滅であったが、横断歩道Pの途中で、横断歩道Pの信号の灯色が赤色に変わり、歩行者7A,7Bは、そのまま急いで横断歩道Pを渡っているとする。また、歩行者7Aは大人であり、歩行者7Bは子供である。
[About scenario 6]
FIG. 21 is a diagram illustrating a situation around an intersection according to scenario 6. In FIG.
In FIG. 21, pedestrians 7A and 7B cross a pedestrian crossing P that crosses a route R1. At the timing when the pedestrians 7A and 7B start to cross the pedestrian crossing P, the signal color of the pedestrian crossing P was flashing blue. The color changes to red, and the pedestrians 7A and 7B hurry to cross the pedestrian crossing P as they are. The pedestrian 7A is an adult, and the pedestrian 7B is a child.
 車両5Aは、方路R2から交差点に進入し、左折して方路R1に向かって交差点内を走行している。また、車両5Bは、車両5Aに後続して走行している。横断歩道Pの信号の灯色が青色の点滅から赤色に変わるタイミングであるので、車両5A,5Bも前方の信号機の灯色も青から黄色、赤色と、切り替わるタイミングである。よって、車両5A,5Bも交差点の通過を急いでいる。
 さらに、方路R2と方路R1との間にであって交差点の角部には、方路R1と方路R2との見通しを遮る建物G2が存在する。
The vehicle 5A enters the intersection from the route R2, turns left, and travels in the intersection toward the route R1. Further, the vehicle 5B travels following the vehicle 5A. Since the lamp color of the signal of the pedestrian crossing P changes from flashing blue to red, the lights of the vehicles 5A and 5B and the traffic lights ahead are also switched from blue to yellow and red. Therefore, the vehicles 5A and 5B are rushing to pass through the intersection.
Furthermore, there is a building G2 between the route R2 and the route R1 and at the corner of the intersection that blocks the view of the route R1 and the route R2.
 ここで、交差点を方路R1に向かって左折する車両5Aと、歩行者7A,7Bとは、車道上で衝突の可能性がある。特に、方路R1と方路R2との間には見通しを遮る建物G2が存在しているため、車両5Aと、歩行者7A,7Bの双方で接近するまで互いの存在に気づきにくい状況である。 Here, there is a possibility of collision between the vehicle 5A turning left at the intersection toward the route R1 and the pedestrians 7A and 7B on the roadway. In particular, since there is a building G2 that blocks the line of sight between the route R1 and the route R2, it is difficult to notice each other until the vehicle 5A and the pedestrians 7A and 7B approach each other. .
 車両5Aが左折し、歩行者7A,7Bに向かって走行すれば、エッジサーバ3は、車両5Aの衝突予測対象として、歩行者7A,7Bを特定するとともに、歩行者7A,7Bの衝突予測対象として、車両5Aを特定する。また、歩行者7A,7Bは、属性が子供(歩行者7Bのみ)であり、信号を無視している。さらに、車両5Aと歩行者7A,7Bとの間に死角要因である建物G2が存在する。 If the vehicle 5A turns left and travels toward the pedestrians 7A and 7B, the edge server 3 specifies the pedestrians 7A and 7B as the collision prediction targets of the vehicle 5A and the collision prediction targets of the pedestrians 7A and 7B. As a result, the vehicle 5A is specified. In addition, the attributes of the pedestrians 7A and 7B are children (only the pedestrian 7B), and the signals are ignored. Furthermore, there is a building G2 that is a blind spot factor between the vehicle 5A and the pedestrians 7A and 7B.
 このとき、エッジサーバ3は、車両5Aを評価対象としたときの評価値を求める場合、衝突予測時間から求められる評価値に、歩行者の属性、死角要因の有無、及び信号無視による加算値を加算する。
 これにより、車両5Aにおける歩行者7A,7Bの評価値は前記閾値よりも大きい値となり、エッジサーバ3は、車両5Aにおける歩行者7A,7Bの衝突予測結果に関する情報を車両5Aへ通知する。
At this time, when the edge server 3 obtains an evaluation value when the vehicle 5A is an evaluation object, the pedestrian attribute, the presence / absence of a blind spot factor, and an addition value by signal ignorance are added to the evaluation value obtained from the collision prediction time. to add.
Thereby, the evaluation value of the pedestrians 7A and 7B in the vehicle 5A becomes a value larger than the threshold value, and the edge server 3 notifies the vehicle 5A of information regarding the collision prediction result of the pedestrians 7A and 7B in the vehicle 5A.
 また、エッジサーバ3は、歩行者7A,7Bを評価対象としたときの評価値を求める場合においても、衝突予測の他、歩行者の状況判定も加味する。よって、歩行者7A,7Bにおける車両5Aの評価値が前記閾値よりも大きい値となり、エッジサーバ3は、歩行者7A,7Bにおける車両5Aの衝突予測の予測結果に関する情報を歩行者7A,7Bへ通知する。 In addition, the edge server 3 also considers the pedestrian's situation determination in addition to the collision prediction when obtaining the evaluation value when the pedestrians 7A and 7B are evaluated. Therefore, the evaluation value of the vehicle 5A in the pedestrians 7A and 7B becomes a value larger than the threshold value, and the edge server 3 sends the information regarding the prediction result of the collision prediction of the vehicle 5A in the pedestrians 7A and 7B to the pedestrians 7A and 7B. Notice.
 さらに、車両5Bにおいても、車両5Aが横断歩道Pの歩行者7A,7Bに気づいて速度を落とし、両車両が接近すると、エッジサーバ3は、車両5Bの衝突予測対象として車両5Aを特定する。衝突予測の結果、衝突予測時間が短ければ、評価値が大きな値に設定される。この結果、エッジサーバ3は、車両5Bにおける車両5Aの衝突予測結果に関する情報を車両5Bへ通知する。 Further, also in the vehicle 5B, when the vehicle 5A notices the pedestrians 7A and 7B on the pedestrian crossing P and decreases the speed, and both vehicles approach, the edge server 3 identifies the vehicle 5A as a collision prediction target of the vehicle 5B. As a result of the collision prediction, if the collision prediction time is short, the evaluation value is set to a large value. As a result, the edge server 3 notifies the vehicle 5B of information related to the collision prediction result of the vehicle 5A in the vehicle 5B.
 以上によって、車両5A,5Bの車載装置50、歩行者7A,7Bの歩行者端末70は、エッジサーバ3からの通知に基づいて、衝突予測結果に関する情報を自装置のユーザへ出力する。
 これによって、エッジサーバ3は、横断歩道Pを歩行者が渡っていることを事前に車両5Aのユーザに認識させることができる。
 また、エッジサーバ3は、横断歩道Pの右側から車両5Aが現れることを事前に歩行者7A,7Bに認識させることができる。
As described above, the in-vehicle device 50 of the vehicles 5A and 5B and the pedestrian terminal 70 of the pedestrians 7A and 7B output information on the collision prediction result to the user of the own device based on the notification from the edge server 3.
Thereby, the edge server 3 can make the user of the vehicle 5A recognize in advance that a pedestrian crosses the pedestrian crossing P.
Further, the edge server 3 can make the pedestrians 7A and 7B recognize in advance that the vehicle 5A appears from the right side of the pedestrian crossing P.
 これにより、エッジサーバ3は、車両5A,5Bの車載装置50、歩行者7A,7Bの歩行者端末70にユーザへの出力を行わせることで、各移動体同士の衝突を回避させることができる。 Thereby, the edge server 3 can avoid the collision of each moving body by making the vehicle-mounted apparatus 50 of vehicle 5A, 5B and the pedestrian terminal 70 of pedestrian 7A, 7B perform an output to a user. .
〔他の実施形態について〕
 図22は、他の実施形態に係るシステムによって実行される情報提供の態様を示す図である。
 図22は、他の実施形態に係る演算処理の一例を示すフローチャートである。
 本実施形態のエッジサーバ3は、動的情報マップM1に基づいて、評価対象それぞれの移動の快適性について評価し、評価対象それぞれの将来の移動の快適性に基づいて評価値を求めるように構成されている。つまり、本実施形態の演算部31aが予測する評価対象それぞれの予測交通状況は、評価対象の将来の移動が快適な移動であるか否かを示す状況である。
[Other Embodiments]
FIG. 22 is a diagram illustrating an aspect of information provision executed by a system according to another embodiment.
FIG. 22 is a flowchart illustrating an example of arithmetic processing according to another embodiment.
The edge server 3 of the present embodiment is configured to evaluate the comfort of movement of each evaluation object based on the dynamic information map M1 and obtain an evaluation value based on the comfort of future movement of each evaluation object. Has been. That is, the predicted traffic situation of each evaluation object predicted by the calculation unit 31a of the present embodiment is a situation indicating whether or not the future movement of the evaluation object is a comfortable movement.
 より具体的に、エッジサーバ3は、サービスエリア内における各方路を複数の単位エリアに分割し、各単位エリアに快適性を損なう要因が一定以上存在するか否かを判定し、快適性を損なう要因が一定以上存在する非快適エリアを特定する。エッジサーバ3は、その判定結果をデータベースに登録し随時更新する。
 本実施形態において快適性を損なう要因とは、例えば、渋滞の発生、又は蛇行する歩行者の存在である。これら要因が一定以上存在する場合、エッジサーバ3は、その単位エリアを非快適エリアと特定する。
More specifically, the edge server 3 divides each route in the service area into a plurality of unit areas, determines whether there is a factor that impairs comfort in each unit area, and determines comfort. Identify non-comfortable areas that have more than a certain amount of damage. The edge server 3 registers the determination result in the database and updates it as needed.
In the present embodiment, the factor that impairs comfort is, for example, the occurrence of traffic jams or the presence of a meandering pedestrian. If these factors exist above a certain level, the edge server 3 identifies the unit area as a non-comfort area.
 さらに、エッジサーバ3は、評価対象と、非快適エリアとの位置関係に基づいて評価値を求める。例えば、評価対象と、非快適エリアとの間の距離に応じて評価値を設定する。
 この評価値は、評価対象と、非快適エリアとが近づけば近づくほど大きな値に設定される。評価対象と、非快適エリアとが近づくと、当該評価対象が非快適エリアを通過する可能性が高くなり、将来の移動の快適性が損なわれるおそれがある。つまり、本実施形態の評価値は、評価対象が非快適エリアを通過する可能性に応じて設定される。
Furthermore, the edge server 3 calculates | requires an evaluation value based on the positional relationship of an evaluation object and a non-comfort area. For example, the evaluation value is set according to the distance between the evaluation target and the non-comfort area.
This evaluation value is set to a larger value as the evaluation target and the non-comfort area are closer. When the evaluation target and the non-comfort area are close to each other, there is a high possibility that the evaluation target passes through the non-comfort area, and the comfort of future movement may be impaired. That is, the evaluation value of the present embodiment is set according to the possibility that the evaluation target passes through the non-comfort area.
 その評価値が所定の閾値以上になると、判定部31bが、評価対象へ、非快適エリアに関する情報を通知する。
 そして、非快適エリアに接近したときに、車両5A,5Bの車載装置50、歩行者7A,7Bの歩行者端末70は、エッジサーバ3からの通知に基づいて、非快適エリアに関する情報を自装置のユーザへ出力する。
When the evaluation value is equal to or greater than a predetermined threshold, the determination unit 31b notifies the evaluation target of information related to the non-comfort area.
And when approaching a non-comfort area, the in-vehicle device 50 of vehicles 5A and 5B and the pedestrian terminal 70 of pedestrians 7A and 7B send information about the non-comfort area based on the notification from the edge server 3. To the user.
 図22では、交差点で区切られている各方路R10、R11、R12、R13、R14がそれぞれ単位エリアを構成している。
 各方路のうち、方路R11には、渋滞が発生し、また、蛇行する歩行者7A,7Bが存在している。これら事象により、エッジサーバ3は、方路R11を非快適エリアと特定する。なお、他の方路は、非快適エリアと特定されていないものとする。
In FIG. 22, each route R10, R11, R12, R13, R14 delimited by the intersection constitutes a unit area.
Of each route, a traffic jam occurs in route R11, and meandering pedestrians 7A and 7B exist. With these events, the edge server 3 identifies the route R11 as a non-comfort area. It is assumed that other routes are not specified as non-comfort areas.
 ここで、方路R10を、方路R11及び方路R12が繋がる交差点に向かって走行する車両5Aは、非快適エリアである方路R11に接近している。そして、評価対象としての車両5Aの評価値が非快適エリアである方路R11に接近することで高くなり、所定の閾値以上になったとする。
 この場合、エッジサーバ3は、評価対象である車両5Aへ、非快適エリアに関する情報を通知する。
Here, the vehicle 5A traveling along the route R10 toward the intersection where the route R11 and the route R12 are connected is approaching the route R11 which is a non-comfort area. Then, it is assumed that the evaluation value of the vehicle 5A as the evaluation target increases as it approaches the route R11 that is a non-comfort area, and becomes equal to or higher than a predetermined threshold value.
In this case, the edge server 3 notifies the vehicle 5A, which is the evaluation target, of information related to the non-comfort area.
 また、方路R13を、方路R11及び方路R14が繋がる交差点に向かって走行する車両5Bは、非快適エリアである方路R11に接近している。そして、評価対象としての車両5Bの評価値が非快適エリアである方路R11に接近することで高くなり、所定の閾値以上になったとする。
 この場合も、エッジサーバ3は、評価対象である車両5Bへ、非快適エリアに関する情報を通知する。
Further, the vehicle 5B traveling along the route R13 toward the intersection where the route R11 and the route R14 are connected is approaching the route R11 which is a non-comfort area. Then, it is assumed that the evaluation value of the vehicle 5B as the evaluation target increases as it approaches the route R11 that is a non-comfort area, and becomes equal to or greater than a predetermined threshold value.
Also in this case, the edge server 3 notifies the information regarding the non-comfort area to the vehicle 5B which is the evaluation target.
 車両5A,5Bの車載装置50は、エッジサーバ3からの通知に基づいて、予測交通情報に関する情報として、将来通過する可能性が高い非快適エリアに関する情報を自装置のユーザへ出力する。 Based on the notification from the edge server 3, the in-vehicle device 50 of the vehicle 5 </ b> A or 5 </ b> B outputs information on the non-comfort area that is likely to pass in the future to the user of the own device as information on the predicted traffic information.
 図22中、車両5Aの車載装置50の出力画面V10には、方路R11へ進入すると、非快適エリアが存在することを示す表示D10や、非快適エリアを避けた迂回路を示す矢印D11等が表示される。
 また、車両5Bの車載装置50の出力画面V11には、方路R13へ進入すると、非快適エリアが存在することを示す表示D12や、非快適エリアを避けた迂回路を示す矢印D13等が表示される。
In FIG. 22, on the output screen V10 of the in-vehicle device 50 of the vehicle 5A, when entering the route R11, a display D10 indicating that a non-comfort area exists, an arrow D11 indicating a detour avoiding the non-comfort area, and the like Is displayed.
Further, on the output screen V11 of the in-vehicle device 50 of the vehicle 5B, when entering the route R13, a display D12 indicating that a non-comfort area exists, an arrow D13 indicating a detour avoiding the non-comfort area, and the like are displayed. Is done.
 これらにより、エッジサーバ3は、非快適エリアが現れることを事前に車両5Aのユーザに認識させることができ、各評価対象それぞれに移動中の快適性を維持させることができる。 Thus, the edge server 3 can make the user of the vehicle 5A recognize in advance that a non-comfort area appears, and can maintain the comfort during movement for each evaluation object.
〔その他〕
 なお、今回開示された実施の形態はすべての点で例示であって制限的なものではないと考えられるべきである。
 例えば、上記各実施形態では、エッジサーバ3によって予測される予測交通状況が、衝突予測の予測結果である場合と、評価対象の将来の移動の快適性である場合について例示したが、その他の予測可能な交通状況であってもよい。
[Others]
The embodiment disclosed this time should be considered as illustrative in all points and not restrictive.
For example, in each of the above-described embodiments, the case where the predicted traffic situation predicted by the edge server 3 is the prediction result of the collision prediction and the case where it is the comfort of the future movement to be evaluated has been exemplified. Possible traffic conditions.
 本発明の範囲は、上記した意味ではなく、請求の範囲によって示され、請求の範囲と均等の意味、及び範囲内でのすべての変更が含まれることが意図される。 The scope of the present invention is indicated not by the above-described meaning but by the scope of claims, and is intended to include meanings equivalent to the scope of claims and all modifications within the scope.
 1A~1D 通信端末
 2 基地局
 3 エッジサーバ
 4 コアサーバ
 5,5A,5B,5C,5D 車両
 7,7A,7B 歩行者
 8 路側センサ
 9 交通信号制御機
 31 制御部
 31a 演算部
 31b 判定部
 31c 通知部
 31d 検出部
 34 記憶部
 34a 移動体データベース
 34b 評価値データベース
 35 通信部
 41 制御部
 44 記憶部
 45 通信部
 50 車載装置
 51 制御部
 52 受信機
 53 車速センサ
 54 ジャイロセンサ
 55 記憶部
 56 ディスプレイ
 57 スピーカ
 58 入力デバイス
 59 車載カメラ
 60 レーダセンサ
 61 通信部
 70 歩行者端末
 71 制御部
 72 記憶部
 73 表示部
 74 操作部
 75 通信部
 81 制御部
 82 記憶部
 83 路側カメラ
 84 レーダセンサ
 85 通信部
 D1 表示
 D2 矢印
 D3 表示
 D4 矢印
 D5 表示
 D10 表示
 D11 矢印
 D13 表示
 D13 矢印
 G1 障害物
 G2 建物
 M1 動的情報マップ
 M2 動的情報マップ
 N1~N4 ノード
 S1~S4 ネットワークスライス
 R1,R2,R10,R11,R12,R13,R14 方路
 V1,V2,V3,V10,V11 出力画面
1A to 1D communication terminal 2 base station 3 edge server 4 core server 5, 5A, 5B, 5C, 5D vehicle 7, 7A, 7B pedestrian 8 roadside sensor 9 traffic signal controller 31 control unit 31a calculation unit 31b determination unit 31c notification Unit 31d detection unit 34 storage unit 34a mobile object database 34b evaluation value database 35 communication unit 41 control unit 44 storage unit 45 communication unit 50 in-vehicle device 51 control unit 52 receiver 53 vehicle speed sensor 54 gyro sensor 55 storage unit 56 display 57 speaker 58 Input device 59 Car-mounted camera 60 Radar sensor 61 Communication unit 70 Pedestrian terminal 71 Control unit 72 Storage unit 73 Display unit 74 Operation unit 75 Communication unit 81 Control unit 82 Storage unit 83 Roadside camera 84 Radar sensor 85 Communication unit D1 Display D2 Arrow D3 Display D4 Arrow D5 Display D10 Display D11 Arrow D13 Display D13 Arrow G1 Obstacle G2 Building M1 Dynamic Information Map M2 Dynamic Information Map N1 to N4 Nodes S1 to S4 Network Slice R1, R2, R10, R11, R12, R13, R14 Route V1, V2, V3, V10, V11 output screen

Claims (12)

  1.  所定のエリア内に位置する1又は複数の移動体のうちの少なくとも一部に搭載された移動端末と、
     前記エリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算部と、
     前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定部と、
     前記判定部の判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知部と、を備えている
    情報提供システム。
    A mobile terminal mounted on at least a part of one or a plurality of mobile bodies located in a predetermined area;
    Based on the dynamic map information in which the dynamic information on the one or more moving objects is superimposed on the map information of the area, an evaluation value of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals is obtained. An arithmetic unit;
    A determination unit that determines whether or not to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals, for each mobile terminal based on the evaluation value;
    An information providing system comprising: a notification unit that notifies the mobile terminal of the predicted traffic situation based on a determination result of the determination unit.
  2.  前記通知部は、前記移動端末のうち、前記判定部が通知すると判定した移動端末に対して、前記予測交通状況を通知する
    請求項1に記載の情報提供システム。
    The information providing system according to claim 1, wherein the notification unit notifies the predicted traffic situation to a mobile terminal determined to be notified by the determination unit among the mobile terminals.
  3.  前記予測交通状況は、前記演算部により前記評価値が求められる移動端末を搭載した対象移動体と、前記1又は複数の移動体のうちの前記対象移動体以外の他の移動体との間の衝突予測の予測結果であり、
     前記演算部は、前記動的マップ情報に基づいて、前記移動端末それぞれについて前記衝突予測を行い、その予測結果に基づいて前記評価値を、前記移動端末それぞれの安全度を評価する値として求める
    請求項1又は請求項2に記載の情報提供システム。
    The predicted traffic situation is between a target mobile body equipped with a mobile terminal for which the evaluation value is determined by the calculation unit and a mobile body other than the target mobile body among the one or a plurality of mobile bodies. It is a prediction result of collision prediction,
    The calculation unit performs the collision prediction for each of the mobile terminals based on the dynamic map information, and determines the evaluation value as a value for evaluating the safety degree of each of the mobile terminals based on the prediction result. The information providing system according to claim 1 or 2.
  4.  前記演算部は、前記他の移動体のうち、前記対象移動体に対して衝突すると予測される移動体を、前記予測結果に基づいて特定し、前記衝突すると予測される移動体に関する前記予測結果に基づいて前記評価値を求める
    請求項3に記載の情報提供システム。
    The calculation unit specifies a mobile body predicted to collide with the target mobile body among the other mobile bodies based on the prediction result, and the prediction result regarding the mobile body predicted to collide The information providing system according to claim 3, wherein the evaluation value is obtained based on the information.
  5.  前記演算部は、前記対象移動体、及び、前記対象移動体に対して衝突すると予測される移動体のいずれか一方が歩行者である場合、前記歩行者の状況に応じた調整値を前記評価値に加味する
    請求項4に記載の情報提供システム。
    When either one of the target mobile body and the mobile body predicted to collide with the target mobile body is a pedestrian, the calculation unit evaluates an adjustment value according to the situation of the pedestrian. The information providing system according to claim 4, wherein the information is added to the value.
  6.  前記演算部は、前記対象移動体と、前記対象移動体に対して衝突すると予測される移動体と、の間に死角を生じさせる死角要因の有無を判定し、前記死角要因の有無の判定結果を前記評価値に加味する
    請求項4又は請求項5に記載の情報提供システム。
    The calculation unit determines the presence / absence of a blind spot factor that causes a blind spot between the target moving body and the mobile body predicted to collide with the target mobile body, and the determination result of the presence / absence of the blind spot factor The information providing system according to claim 4 or 5, wherein the value is added to the evaluation value.
  7.  前記予測交通状況を前記移動端末のユーザへ向けて出力させるように、前記移動端末を制御する制御部をさらに備え、
     前記制御部は、前記対象移動体に対して衝突すると予測される移動体の属性に応じて、前記予測交通状況の出力態様が異なるように制御する
    請求項3から請求項6のいずれか一項に記載の情報提供システム。
    A control unit for controlling the mobile terminal so as to output the predicted traffic situation to a user of the mobile terminal;
    7. The control unit according to claim 3, wherein the control unit controls the output mode of the predicted traffic situation to be different according to an attribute of the moving body predicted to collide with the target moving body. Information providing system described in 1.
  8.  前記予測交通状況は、前記演算部により前記評価値が求められる移動端末の将来の移動が快適な移動であるか否かを示す情報であり、
     前記演算部は、前記動的マップ情報に基づいて、前記移動端末それぞれの将来の移動の快適性について評価し、前記移動端末それぞれの将来の移動の快適性に基づいて前記評価値を求める
    請求項1又は請求項2に記載の情報提供システム。
    The predicted traffic situation is information indicating whether or not the future movement of the mobile terminal for which the evaluation value is calculated by the calculation unit is a comfortable movement,
    The computing unit evaluates the future mobility comfort of each of the mobile terminals based on the dynamic map information, and obtains the evaluation value based on the future mobility comfort of each of the mobile terminals. The information providing system according to claim 1 or 2.
  9.  請求項1から請求項8のいずれか一項に記載の情報提供システムから前記予測交通状況を受け付け、ユーザへ前記予測交通状況を出力する移動端末。 A mobile terminal that receives the predicted traffic situation from the information providing system according to any one of claims 1 to 8, and outputs the predicted traffic situation to a user.
  10.  移動端末へ情報提供を行う情報提供方法であって、
     1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算ステップと、
     前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定ステップと、
     前記判定ステップの判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知ステップと、を含む
    情報提供方法。
    An information providing method for providing information to a mobile terminal,
    Based on the dynamic map information in which the dynamic information related to the one or more moving objects is superimposed on the map information of the area where the one or more moving objects are located, at least a part of the one or more moving objects A calculation step for obtaining an evaluation value of a predicted traffic situation, which is a prediction result of the traffic situation of each of the mounted mobile terminals;
    A step of determining for each mobile terminal whether or not to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals based on the evaluation value;
    A notification providing step of notifying the mobile terminal of the predicted traffic situation based on a determination result of the determination step.
  11.  移動端末へ情報提供を行う情報提供処理をコンピュータに実行させるためのコンピュータプログラムであって、
     前記コンピュータに
     1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された前記移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算ステップと、
     前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定ステップと、
     前記判定ステップの判定結果に基づいて前記移動端末へ前記予測交通状況を通知する通知ステップと、を実行させるための
    コンピュータプログラム。
    A computer program for causing a computer to execute an information providing process for providing information to a mobile terminal,
    Based on the dynamic map information in which the dynamic information related to the one or more moving objects is superimposed on the map information of the area where the one or more moving objects are located on the computer, at least one of the one or more moving objects A calculation step for obtaining an evaluation value of a predicted traffic situation that is a prediction result of the traffic situation of each of the mobile terminals mounted in part;
    A step of determining for each mobile terminal whether or not to notify the mobile terminal of the predicted traffic situation of each of the mobile terminals based on the evaluation value;
    A computer program for executing a notification step of notifying the mobile terminal of the predicted traffic situation based on a determination result of the determination step.
  12.  1又は複数の移動体が位置するエリアの地図情報に、前記1又は複数の移動体に関する動的情報が重畳された動的マップ情報に基づいて、前記1又は複数の移動体の少なくとも一部に搭載された移動端末それぞれの交通状況の予測結果である予測交通状況の評価値を求める演算部と、
     前記移動端末それぞれの前記予測交通状況を前記移動端末へ通知するか否かを、前記評価値に基づいて前記移動端末ごとに判定する判定部と、を備えている
    情報提供装置。
    Based on the dynamic map information in which the dynamic information related to the one or more moving objects is superimposed on the map information of the area where the one or more moving objects are located, at least a part of the one or more moving objects A calculation unit that obtains an evaluation value of a predicted traffic situation that is a prediction result of the traffic situation of each of the mounted mobile terminals;
    An information providing apparatus comprising: a determination unit that determines, for each mobile terminal, whether or not to notify the mobile terminal of the predicted traffic situation of each mobile terminal based on the evaluation value.
PCT/JP2019/011739 2018-04-10 2019-03-20 Information provision system, mobile terminal, information provision device, information provision method, and computer program WO2019198449A1 (en)

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