server

Abstract

To suppress increase in an influence on a traffic network due to a stoppage of a group with a high degree of influence.SOLUTION: A server specifies a first group GR1 and a second group GR2 by referring to predicted moving object information. The server calculates an influence degree IF for each group GR. The server calculates a display state of a traffic rule display device, under which the group GR with the higher influence degree IF between the first group GR1 and the second group GR2 can be continuously traveled. The server transmits a request DM that results in the calculated display state.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a server. [Background technology]

[0002] Patent Document 1 describes a communication system including a vehicle and a server. When a plurality of vehicles travel as a group, the server transmits a control signal to the vehicles traveling in the group. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-167669 Summary of the Invention [Problem to be solved by the invention]

[0004] In a traffic network including a plurality of vehicles, multiple groups may pass through a traffic rule display device such as a traffic light. In a traffic network including a communication system such as that described in Patent Document 1, there is room for improving the efficiency of the entire traffic network. [Means for solving the problem]

[0005] In order to solve the above problem, the present invention provides a server that transmits a control signal based on predicted moving body information after the time when the moving body information, which is information about vehicles in the real world, to a traffic rule display device that displays different traffic rules by changing the display state, the server performing the following operations: based on the predicted moving body information, identifying a first group and a second group different from the first group as groups in which a plurality of the vehicles will travel together; calculating, for each identified group, an impact degree that indicates the degree of impact that will be exerted on a traffic network when the group being calculated stops; when the first group and the second group are located within a peripheral range that includes a range in which the group will travel according to the display on the traffic rule display device, calculating the display state that allows the group with the higher impact degree of the first group and the second group to continue traveling; and transmitting a request to the traffic rule display device to change to the calculated display state.

[0006] The server can send a request to the traffic rule display device to allow the group with the higher influence of either the first or second group to continue driving, thereby reducing the impact on the traffic network caused by the group with the higher influence stopping. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a schematic diagram showing a communication system. [Figure 2] FIG. 2 is a flowchart showing a series of processes for generating predicted moving object information. [Figure 3] FIG. 3 is a flowchart showing a series of processes for determining a group. [Figure 4] FIG. 4 is a flowchart showing a series of processes for calculating the influence degree. [Figure 5] FIG. 5 is a flowchart showing a series of processes for transmitting a request to the traffic rule display device. DETAILED DESCRIPTION OF THE INVENTION

[0008] (One embodiment) An embodiment of the server will be described below with reference to the drawings. Note that the following description will be given of a communication system including the server.

[0009] <Communication system overview> As shown in FIG. 1, the communication system 10 includes a plurality of vehicles 20, a traffic rule display device 30, and a server 40.

[0010] The vehicle 20 has a vehicle communication device 21, a vehicle control device 22, and a plurality of information acquisition devices 23. The vehicle communication device 21 communicates with the server 40 via wireless communication. The vehicle control device 22 controls the communication of the vehicle communication device 21.

[0011] The multiple information acquisition devices 23 acquire various types of information about the vehicle 20. The multiple information acquisition devices 23 are, for example, a GPS receiver 24 and a vehicle speed sensor 25. The GPS receiver 24 receives location information indicating the location of the vehicle 20 from the GPS device. The location information is coordinate values ​​of latitude and longitude. The vehicle speed sensor 25 acquires the traveling speed of the vehicle 20 as the vehicle speed. Each information acquisition device 23 outputs the acquired information about the vehicle 20 to the vehicle control device 22.

[0012] The vehicle control device 22 controls the following running of the vehicle 20. The vehicle control device 22 controls following running of another vehicle 20 running ahead, in response to a user operation. When the vehicle control device 22 is in following running, it generates following information FD indicating that the vehicle is in following running.

[0013] The vehicle control device 22 acquires, as moving object information VI, various types of information about the vehicle 20 acquired from multiple information acquisition devices 23, identification information indicating the vehicle 20, the time when the various types of information were acquired, and following information FD of the vehicle 20. The moving object information VI is information about the vehicle 20 in the real world. The identification information indicating the vehicle 20 includes information indicating whether the vehicle 20 is a large vehicle LV and whether it is an emergency vehicle EV. A large vehicle LV is a vehicle 20 whose total vehicle weight is equal to or greater than a predetermined weight, or whose passenger capacity is equal to or greater than a predetermined number of people. Examples of large vehicles LV include large trucks and route buses. Examples of emergency vehicles EV include ambulances.

[0014] The vehicle control device 22 outputs the moving object information VI to the vehicle communication device 21. Then, the vehicle communication device 21 transmits the moving object information VI to the server 40. Note that in FIG. 1, one vehicle 20 out of the multiple vehicles 20 is illustrated in detail, and the details of the other vehicles 20 are omitted. Each vehicle 20 transmits its own moving object information VI to the server 40.

[0015] The traffic rule display device 30 displays traffic rules. The traffic rule display device 30 can display different traffic rules by changing the display state. The traffic rule display device 30 is, for example, a traffic light installed at a cross-shaped intersection.

[0016] The traffic rule display device 30 includes a display unit 31, a communication unit 32, and a control unit 33. The display unit 31 has a plurality of lamps. The plurality of lamps include red lamps indicating that entry is prohibited at intersections within the range of travel in accordance with the display on the traffic rule display device 30, and blue lamps indicating that entry to the intersection is permitted.

[0017] The communication unit 32 communicates with the server 40 via wireless communication. The communication unit 32 transmits a signal indicating the display state of the display unit 31 to the server 40. The communication unit 32 also receives a signal for controlling the display unit 31 from the server 40.

[0018] The control unit 33 controls the display state of the display unit 31. For example, the control unit 33 controls the display state of the display unit 31 so that the red lamp is turned off and the blue lamp is turned on. The control unit 33 also controls the display state of the display unit 31 based on a signal for controlling the display unit 31 received by the communication unit 32. The control unit 33 acquires, as traffic signal information TS, information indicating the display state of the display unit 31, identification information indicating the traffic rule display device 30, and information indicating the time when the display state was maintained. The control unit 33 then outputs the traffic signal information TS to the communication unit 32. The communication unit 32 then transmits the traffic signal information TS to the server 40.

[0019] The server 40 is capable of communicating with a plurality of vehicles 20. The server 40 is also capable of communicating with the traffic rule display device 30. The server 40 acquires a plurality of pieces of moving object information VI from the plurality of vehicles 20. The server 40 acquires traffic signal information TS from the traffic rule display device 30. The server 40 is capable of transmitting a control signal based on predicted moving object information FI generated based on the moving object information VI, which will be described later, to the traffic rule display device 30. The server 40 includes a communication device 50, an information processing device 60, and a data center 70.

[0020] The communication device 50 communicates with multiple vehicles 20. The communication device 50 receives moving object information VI transmitted from the vehicles 20. The communication device 50 receives traffic signal information TS transmitted from the traffic rule display device 30. The communication device 50 outputs the received moving object information VI and the received traffic signal information TS to the information processing device 60. The communication device 50 also transmits information acquired from the information processing device 60 to the vehicles 20. The communication device 50 transmits the signal acquired from the information processing device 60 to the traffic rule display device 30.

[0021] The information processing device 60 includes a CPU 61, which is an execution device, a peripheral circuit 62, a data storage unit 63, a program storage unit 64, and a bus 65. The bus 65 connects the CPU 61, the peripheral circuit 62, the data storage unit 63, and the program storage unit 64 so that they can communicate with one another. The peripheral circuit 62 includes a circuit that generates a clock signal that regulates internal operation, a power supply circuit, a reset circuit, etc. The data storage unit 63 stores data generated in accordance with the operation of the CPU 61. The program storage unit 64 stores a generation program P1 for predicted moving object information FI, a determination program P2 for a group GR, a calculation program P3 for an influence degree IF, and a control program P4 for the traffic rule display device 30. The CPU 61 performs information processing by executing various programs stored in the program storage unit 64.

[0022] The data center 70 stores predicted mobile object information FI. The predicted mobile object information FI is information generated based on mobile object information VI of multiple vehicles 20, and includes multiple pieces of mobile object information VI from the time the mobile object information VI in a specified area was acquired. The specified area may be, for example, a range including one country, a range including only a portion of one country, or a range including the previous time. In other words, the predicted mobile object information FI is a so-called digital twin. Specifically, the data center 70 stores time series data of the predicted mobile object information FI generated by the information processing device 60. The data center 70 acquires the predicted mobile object information FI generated by the information processing device 60 multiple times over time. As a result, the data center 70 stores time series data of the predicted mobile object information FI.

[0023] <Generation of predicted moving object information> Next, the generation of the predicted moving object information FI performed by the information processing device 60 will be described. The CPU 61 repeatedly generates the predicted moving object information FI by repeating the generation program P1 for the predicted moving object information FI at a predetermined cycle, which is set to, for example, one minute.

[0024] As shown in FIG. 2, when the CPU 61 starts executing the program P1 for generating the predicted moving object information FI, it first performs the process of step S11. In step S11, the CPU 61 acquires the moving object information VI of each vehicle 20 in the communication system 10. When acquiring a plurality of pieces of moving object information VI, the CPU 61 acquires the moving object information VI of each vehicle 20 based on the identification information of the vehicle 20 included in the moving object information VI. Thereafter, the CPU 61 proceeds to step S12.

[0025] In step S12, the CPU 61 acquires the traffic signal information TS from the traffic rule display device 30. After that, the CPU 61 advances the process to step S13. In step S13, the CPU 61 generates predicted mobile object information FI based on the acquired multiple pieces of mobile object information VI and traffic signal information TS. Specifically, the CPU 61 performs the following process to synchronize the mobile object information VI and traffic signal information TS of each vehicle 20, thereby generating predicted mobile object information FI. First, the CPU 61 references information indicating the time of acquisition for each of the acquired multiple pieces of mobile object information VI. Next, the CPU 61 predicts the mobile object information VI at the reference time by using the time of the most recently acquired mobile object information VI as the reference time and correcting the other mobile object information VI by the time difference. For example, the CPU 61 performs the correction based on the mobile object information VI, such as past vehicle speed. Next, the CPU 61 predicts the display state of the traffic rule display device 30 at the reference time based on the acquired traffic signal information TS.

[0026] Then, the CPU 61 generates various information of the predicted mobile object information VI and the display state of the predicted traffic signal information TS as predicted mobile object information FI. As a result, the CPU 61 acquires the mobile object information VI and traffic signal information TS of the multiple vehicles 20 synchronized at the reference time as predicted mobile object information FI. Thereafter, the CPU 61 proceeds to step S14.

[0027] In step S14, the CPU 61 stores the generated predicted mobile object information FI in the data center 70. After that, the CPU 61 ends the series of processes. As a result, the data center 70 stores the acquired predicted mobile object information FI. As the CPU 61 repeatedly executes the generation program P1 for the predicted mobile object information FI, the data center 70 acquires and stores the predicted mobile object information FI at predetermined intervals. Therefore, the data center 70 stores the time series data of the predicted mobile object information FI.

[0028] <Group decision> Next, the determination of the group GR traveling together performed by the information processing device 60 will be described.

[0029] The CPU 61 repeats the group GR determination program P2 at a predetermined cycle. The predetermined cycle is set to, for example, one minute. As a result, the CPU 61 determines which vehicles 20 in a predetermined area belong to the group GR and which vehicles 20 do not belong to the group GR.

[0030] 3, when the CPU 61 starts execution of the judgment program P2 for the group GR, it first starts processing in step S21. In step S21, the CPU 61 acquires time-series data of the predicted moving object information FI in the data center 70 for a predetermined past period. The predetermined past period is, for example, 10 minutes. Thereafter, the CPU 61 proceeds to processing in step S22.

[0031] In step S22, the CPU 61 extracts multiple vehicles 20 that have been present within a specified range for the past specified period based on the time-series data of the predicted moving object information FI acquired in step S21. The specified range is, for example, a range in which the distance between multiple vehicles 20 is within 100 meters. The CPU 61 then proceeds to step S23. Note that if the CPU 61 is unable to extract multiple vehicles 20 in step S22, the CPU 61 adds non-component information indicating that all vehicles 20 do not constitute a group GR to the predicted moving object information FI, and ends this series of processes.

[0032] In step S23, the CPU 61 determines whether or not a specified percentage or more of the vehicles 20 are currently being followed among the plurality of vehicles 20 extracted in step S22. The specified percentage is set to, for example, 80%. Specifically, the CPU 61 determines whether or not the moving object information VI of the plurality of vehicles 20 extracted in step S22 includes following information FD. Then, the CPU 61 compares the number of moving object information VI that includes following information FD with the number extracted in step S22.

[0033] If the number of following information FDs is equal to or greater than the specified ratio (S23: YES), the CPU 61 proceeds to step S24. In step S24, the CPU 61 determines that the plurality of vehicles 20 extracted in step S22 are a group GR traveling together. Thereafter, the CPU 61 proceeds to step S25.

[0034] In step S25, the CPU 61 adds, to the predicted moving object information FI, configuration information indicating that the vehicles 20 are in one group GR and group identification information identifying the group GR, for the plurality of vehicles 20 determined to be in one group GR in step S24. Thereafter, the CPU 61 ends the series of processes.

[0035] On the other hand, if the number of pieces of following information FD does not exceed the specified ratio (S23: YES), the CPU 61 proceeds to step S31. In step S31, the CPU 61 does not determine that the multiple vehicles 20 extracted in step S22 form one group. Thereafter, the CPU 61 proceeds to step S32.

[0036] In step S32, the CPU 61 adds non-constitution information indicating that the vehicles 20 do not constitute a group GR to the predicted moving object information FI for the vehicles 20 that were not determined to constitute a group GR in step S31. The CPU 61 then terminates the series of processes. By executing the group GR determination program P2 in this manner, the predicted moving object information FI comes to include information indicating whether or not the vehicles 20 constitute a group GR.

[0037] <Calculation of impact> Next, the calculation of the influence IF of the group GR performed by the information processing device 60 will be described. The CPU 61 repeats the calculation program P3 for the impact IF at a predetermined cycle. The predetermined cycle is set to, for example, one minute. The impact IF is a value indicating the degree of impact on the transportation network of a predetermined area when the group GR to be calculated stops. In this way, the CPU 61 calculates the impact IF for each group GR made up in the predetermined area.

[0038] In detail, the CPU 61 refers to the predicted moving object information FI to identify a first group GR1 and a second group GR2 different from the first group GR1 among the multiple groups GR. Specifically, the CPU 61 refers to information for identifying the groups GR included in the predicted moving object information FI to identify the first group GR1 and the second group GR2. The CPU 61 calculates the influence IF of the first group GR1 and the influence IF of the second group GR2, respectively.

[0039] 4, when the CPU 61 starts execution of the calculation program P3 for the influence degree IF, the CPU 61 first starts the processing of step S41. In step S41, the CPU 61 calculates the number NM of vehicles 20 that constitute the group GR to be calculated. Specifically, the CPU 61 refers to the predicted moving object information FI to calculate the number NM of vehicles 20 that have information that identifies the group GR to be calculated. Thereafter, the CPU 61 proceeds to the processing of step S42.

[0040] In step S42, the CPU 61 calculates the average speed AV of the vehicles 20 included in the group GR. Specifically, the CPU 61 refers to the predicted moving object information FI of the vehicles 20 included in the group GR to be calculated, and acquires the speed of the vehicle 20 having information that identifies the group GR to be calculated. Next, the CPU 61 calculates the average value of the acquired speeds of the multiple vehicles 20 as the average speed AV of the vehicles 20 included in the group GR. Thereafter, the CPU 61 proceeds to step S43.

[0041] In step S43, the CPU 61 determines whether or not there is an emergency vehicle EV included in the group GR that is the calculation target. Specifically, the CPU 61 determines whether or not the various information in the predicted moving object information FI of the vehicle 20 included in the group GR includes information indicating that the vehicle is an emergency vehicle EV. Thereafter, the CPU 61 proceeds to step S44.

[0042] In step S44, the CPU 61 calculates whether or not a large vehicle LV is present in the group GR that is the calculation target. The CPU 61 determines whether or not the various types of information in the predicted moving object information FI of the vehicle 20 included in the group GR include information indicating that the vehicle is a large vehicle LV. Thereafter, the CPU 61 proceeds to step S45.

[0043] In step S45, the CPU 61 calculates the influence IF of the group GR to be calculated. Specifically, the greater the number of vehicles 20 constituting the group GR to be calculated, the greater the calculated influence IF. The CPU 61 calculates the influence IF to be greater the greater the average speed AV of the vehicles 20 constituting the group GR to be calculated. The CPU 61 calculates the influence IF to be greater when an emergency vehicle EV is included in the group GR to be calculated, than when an emergency vehicle EV is not included. The CPU 61 calculates the influence IF to be greater when a large vehicle LV is included in the group GR to be calculated, than when a large vehicle LV is not included. Thereafter, the CPU 61 adds information indicating the influence IF of the group GR to the predicted moving object information FI, and ends the series of processes.

[0044] <Control of traffic rule display device> Next, the control of the traffic rule display device 30 performed by the information processing device 60 based on the influence IF of the group GR will be described.

[0045] The CPU 61 starts executing the control program P4 of the traffic rule display device 30 when the first group GR1 and the second group GR2 are located within a peripheral range that includes the range in which the vehicles travel in accordance with the display of the traffic rule display device 30. The peripheral range is defined in advance as a range that includes the range in which the vehicles travel in accordance with the display of the traffic rule display device 30, but is wider than that range. For example, the peripheral range is defined as a range with a radius of 100 meters from the center of the intersection, including the range of the intersection where the traffic rule display device 30 is installed.

[0046] 5, when the CPU 61 starts executing the control program P4 of the traffic rule display device 30, it first performs the process of step S51. In step S51, the CPU 61 determines whether the influence IF of the first group GR1 is equal to or greater than the influence IF of the second group GR2. Specifically, the CPU 61 refers to the predicted moving object information FI to obtain the influence IF of the first group GR1 and the influence IF of the second group GR2. Next, the CPU 61 compares the obtained influence IFs.

[0047] If the influence IF of the first group GR1 is equal to or greater than the influence IF of the second group GR2 (S51: YES), the CPU 61 proceeds to step S52. In step S52, the CPU 61 calculates a display state that allows the first group GR1 to continue traveling. Thereafter, the CPU 61 proceeds to step S53.

[0048] In step S53, the CPU 61 transmits a request DM for changing the display state to allow the first group GR1 to continue traveling to the traffic rule display device 30. After that, the CPU 61 ends the current series of processes.

[0049] On the other hand, if the influence IF of the first group GR1 is less than the influence IF of the second group GR2 (S51: NO), the CPU 61 proceeds to step S61. In step S61, the CPU 61 calculates a display state that allows the second group GR2 to continue traveling. Thereafter, the CPU 61 proceeds to step S62.

[0050] In step S62, the CPU 61 transmits a control signal indicating a request DM that will be displayed in a state that allows the second group GR2 to continue driving to the traffic rule display device 30. The CPU 61 then terminates this series of processes. In this way, the CPU 61 calculates a display state that allows the group GR with the higher influence level IF of the first group GR1 or the second group GR2 to continue driving, and transmits a request DM that will be displayed in this state to the traffic rule display device 30.

[0051] (Operation of the embodiment) Here, suppose that a first group GR1 is traveling on a road in a first direction and reaches an intersection where a traffic rule display device 30 is installed. Suppose that a second group GR2 is traveling on a road in a second direction that intersects with the road in the first direction and reaches the intersection where the traffic rule display device 30 is installed. When the first group GR1 and the second group GR2 are located within a peripheral range that includes the range in which they will travel in accordance with the display of the traffic rule display device 30, the CPU 61 starts executing the control program P4 of the traffic rule display device 30. If the influence IF of the first group GR1 is greater than the influence IF of the second group GR2, the traffic rule display device 30 receives a request DM that changes the display state to allow the first group GR1 to continue traveling. In the traffic rule display device 30 that has received the request DM, the control unit 33 controls the display unit 31 to illuminate blue lights on the road in the first direction and red lights on the road in the second direction at the intersection where the traffic rule display device 30 is installed.

[0052] (Effects of the embodiment) (1) According to the above embodiment, the server 40 transmits a request DM to the traffic rule display device 30 to request that the first group GR1 continue traveling. Therefore, when the first group GR1 and the second group GR2 approach a range where they are traveling in accordance with the display of the traffic rule display device 30, the server 40 can allow the group GR with a high influence IF out of the first group GR1 and the second group GR2 to continue traveling. Therefore, in a transportation network in which multiple vehicles 20 travel, the server 40 can prevent a large impact on the transportation network caused by the group GR with a high influence IF stopping.

[0053] (2) According to the above embodiment, in calculating the impact IF, the server 40 calculates a larger impact IF as the number NM of the vehicles 20 constituting the group GR increases. Therefore, the server 40 is more likely to allow the group GR, which has a larger number NM of the vehicles 20 constituting the group GR, to continue traveling, out of the first group GR1 and the second group GR2.

[0054] (3) According to the above embodiment, in calculating the influence IF, the server 40 calculates a larger influence IF as the average speed AV of the vehicles 20 constituting the group GR increases. Therefore, the server 40 is more likely to allow the group GR, which has the larger average speed AV of the vehicles 20 constituting the group GR, to continue traveling, out of the first group GR1 and the second group GR2.

[0055] (4) According to the above embodiment, when calculating the influence IF, the server 40 calculates a larger influence IF when an emergency vehicle EV is included in the group GR than when an emergency vehicle EV is not included. This makes it easier for the server 40 to allow the emergency vehicle EV to continue traveling.

[0056] (5) According to the above embodiment, when calculating the impact factor IF, the server 40 calculates a larger impact factor IF when a large vehicle LV is included in the group GR than when a large vehicle LV is not included. This makes it easier for the server 40 to allow the large vehicle LV to continue traveling.

[0057] (Other embodiments) This embodiment can be modified as follows: This embodiment and the following modifications can be combined and implemented within the scope of technical compatibility.

[0058] The method of calculating the impact IF is not limited to the example of the above embodiment. For example, when calculating the impact IF, the CPU 61 may calculate the impact IF of a group GR that includes an emergency vehicle EV to be greater than the impact IF of a group GR that does not include an emergency vehicle EV. Furthermore, when calculating the impact IF, the CPU 61 may calculate a larger impact IF the larger the average size of the vehicles 20 that make up the group GR. In other words, the CPU 61 may calculate the impact IF without depending on some or all of the number NM of vehicles 20, the average speed AV of the vehicles 20, the presence or absence of emergency vehicles EV, and the presence or absence of large vehicles LV.

[0059] The method of determining a group GR is not limited to the example of the above embodiment. For example, the CPU 61 may identify a group GR by processing in step S22, omitting the processing of step S21. Alternatively, the CPU 61 may identify a plurality of vehicles 20 extracted by the processing of step S21 as a group GR, omitting the processing of step S22. Alternatively, for example, in addition to or instead of the processing of steps S21 and S22, when the moving object information VI includes information indicating the destination of the vehicle 20, the CPU 61 may identify a group GR based on the information indicating the destination. Specifically, the CPU 61 may identify vehicles 20 whose information indicating the destination indicates the same location as a group GR.

[0060] The method for generating the predicted moving object information FI is not limited to the example of the above embodiment. For example, the reference time may be set to a time that is later than the acquisition times of all vehicles 20. Even in this case, the CPU 61 can generate the predicted moving object information FI after acquiring the moving object information VI.

[0061] The mobile object information VI is not limited to information acquired from the vehicle 20. For example, the mobile object information VI may be information about the vehicle 20 acquired by a camera installed in a transportation network, which information is acquired by the server 40 from the camera.

[0062] The configuration of the display unit 31 of the traffic rule display device 30 is not limited to the example in the above embodiment. For example, in addition to red and blue lamps, the display unit 31 may have lamps that allow driving in each direction at the intersection.

[0063] The traffic rule display device 30 is not limited to a traffic light. For example, it may be an electronic signboard that displays traffic rules, or multiple road studs. The traffic rule display device 30 may be any device that displays different traffic rules by changing the display state.

[0064] The display state in the traffic rule display device 30 that the first group GR1 can continue driving does not necessarily mean that the second group GR2 cannot continue driving. As in the above embodiment, if the first group GR1 or the second group GR2 is in a situation where they can continue driving, the server 40 may set the display state to allow the first group GR1 to continue driving and at the same time set the display state to prevent the second group GR2 from continuing driving.

[0065] The server 40 may refer to the display state of the traffic rule display device 30 in the predicted moving object information FI to determine whether to execute the processes of steps S53 and S62. For example, when executing the process of step S53, the server 40 may execute the process of step S53 only when the display state of the traffic rule display device 30 in the predicted moving object information FI is not a display state that allows the first group GR1 to continue traveling.

[0066] The information processing device 60 may be configured as a circuit including one or more processors that execute various processes according to a computer program (software). The information processing device 60 may also be configured as a circuit including one or more dedicated hardware circuits, such as an application-specific integrated circuit (ASIC), that execute at least some of the various processes, or a combination thereof. The processor includes a CPU and memory such as RAM and ROM. The memory stores program code or instructions configured to cause the CPU to execute processes. The memory, i.e., computer-readable medium, includes any available medium that can be accessed by a general-purpose or dedicated computer. [Explanation of symbols]

[0067] 10...communication system, 20...vehicle, 30...traffic rule display device, 40...server, 50...communication device, 60...information processing device, 70...data center, AV...average speed, DM...request, EV...emergency vehicle, FI...predicted moving object information, GR...group, GR1...first group, GR2...second group, IF...impact level, LV...large vehicle, VI...moving object information

Claims

1. A server that transmits a control signal based on predicted moving body information after a time when the moving body information is acquired, which is generated based on moving body information that is information about a vehicle in the real world, to a traffic rule display device that displays different traffic rules by changing a display state, Identifying a first group and a second group different from the first group as groups in which the plurality of vehicles will travel together based on the predicted moving object information; Calculating an impact degree indicating the degree of impact on the transportation network when the group to be calculated stops for each of the identified groups; When the first group and the second group are located within a peripheral range including a range in which the first group and the second group travel in accordance with the display of the traffic rule display device, calculating the display state in which the group with the higher influence degree among the first group and the second group can continue traveling; transmitting a request for the calculated display state to the traffic rule display device; A server that runs

2. When calculating the degree of influence, the greater the number of vehicles constituting the group to be calculated, the greater the degree of influence is calculated to be. The server of claim 1 .

3. When calculating the degree of influence, the higher the average speed of the vehicles constituting the group to be calculated, the greater the degree of influence is calculated to be. The server of claim 1 .

4. When calculating the degree of influence, if an emergency vehicle is included in the group to be calculated, the degree of influence is calculated to be larger than if the emergency vehicle is not included. The server of claim 1 .

5. When calculating the degree of influence, if a large vehicle is included in the group to be calculated, the degree of influence is calculated to be larger than if the large vehicle is not included. The server of claim 1 .

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