Operation management device and maas providing method

Abstract

The invention relates to an operation management apparatus and a MaaS providing method. The operation management device is provided with a control unit that: acquires plan data indicating an operation plan for operating autonomous vehicles on a plurality of routes at fixed intervals; an actual performance acquisition unit that acquires actual performance data indicating actual performance of operation including the time at which the autonomous vehicle of each route arrives at each station specified for each route; when an autonomous vehicle whose delay exceeds a threshold value is detected as a delayed vehicle from among autonomous vehicles of a plurality of routes, an autonomous vehicle of one or more routes whose operation interval is to be adjusted is selected as an influencing vehicle from among autonomous vehicles of a plurality of routes. The delay is the delay of the time of arriving at any station included in the operation performance indicated by the acquired performance data relative to the time corresponding to the operation plan indicated by the acquired plan data; and instructing the selected influencing vehicle on the basis of the operation actual performance indicated by the actual performance data.

Description

Technical Field

[0001] The present disclosure relates to an operation management device and a MaaS provision method. Background Art

[0002] In Japanese Unexamined Patent Application Publication No. 2023 - 132714, an operation management system is disclosed. The operation management system predicts the occurrence of an abnormal event on the road on which an autonomous driving vehicle is running, and updates the recommended speed set for the road according to the prediction result.

[0003] In the existing operation management system, the countermeasures against the delay of autonomous driving vehicles are insufficient. Summary of the Invention

[0004] An object of the present disclosure is to improve the countermeasures against the delay of autonomous driving vehicles.

[0005] The operation management device of the present disclosure includes a control unit,

[0006] The control unit performs the following operations:

[0007] Obtain plan data representing an operation plan for causing autonomous driving vehicles on a plurality of routes to run at fixed intervals;

[0008] Obtain actual data representing actual operation results, where the actual operation results include the times when the autonomous driving vehicles on each route arrive at each station specified for each route;

[0009] When an autonomous driving vehicle with a delay exceeding a threshold is detected as a delayed vehicle among the autonomous driving vehicles on the plurality of routes, select one or more autonomous driving vehicles on the plurality of routes whose operation intervals are to be adjusted as affected vehicles, where the delay is the delay of the time of arrival at any station included in the actual operation results shown by the obtained actual data relative to the time corresponding to the operation plan shown by the obtained plan data;

[0010] Calculate the waiting time at the next station to be indicated to the selected affected vehicles based on the actual operation results shown by the actual data; and

[0011] Output time data representing the calculated waiting time.

[0012] According to the present disclosure, the countermeasures against the delay of autonomous driving vehicles can be improved. Brief Description of the Drawings

[0013] Hereinafter, with reference to the drawings, the features, advantages, and technical and industrial significance of the exemplary embodiments of the present invention will be described, where the same reference numerals denote the same elements, and:

[0014] Figure 1 This is a diagram showing the configuration of the system according to an embodiment of the present disclosure.

[0015] Figure 2 This is a block diagram showing the configuration of the operation management device according to an embodiment of the present disclosure.

[0016] Figure 3 This is a diagram showing an operation example of one route according to an embodiment of the present disclosure.

[0017] Figure 4 This is a diagram showing an operation example of one route when the first method is adopted according to an embodiment of the present disclosure.

[0018] Figure 5 This is a diagram showing an operation example of one route when the first method is adopted according to an embodiment of the present disclosure.

[0019] Figure 6 This is a flowchart showing the operation of the operation management device according to an embodiment of the present disclosure. Detailed Embodiment

[0020] Hereinafter, an embodiment of the present disclosure will be described with reference to the accompanying drawings.

[0021] In each figure, the same or corresponding parts are denoted by the same reference numerals. In the description of each embodiment, the same or corresponding parts are appropriately omitted or simplified.

[0022] An embodiment of the present disclosure will be described.

[0023] With reference to Figure 1 , the configuration of the system 1 of the present embodiment will be described.

[0024] The system 1 of the present embodiment includes an operation management device 10, an autonomous driving control device 20, and autonomous driving vehicles 30 on multiple routes. The operation management device 10 and the autonomous driving control device 20 are connected in a communicable manner. The autonomous driving control device 20 can communicate with the autonomous driving vehicles 30 on multiple routes via the network 50. Alternatively, the operation management device 10 can communicate with the autonomous driving control device 20 via the network 50.

[0025] The operation management device 10 is provided in a facility such as a data center. The operation management device 10 is a computer such as a server belonging to a cloud computing system or other computing systems.

[0026] The autonomous driving control device 20 is provided in a facility such as a data center. The autonomous driving control device 20 is a computer such as a server belonging to a cloud computing system or other computing systems.

[0027] Autonomous vehicles 30 on multiple routes are, for example, any type of vehicle such as a gasoline vehicle, a diesel vehicle, a hydrogen energy vehicle, an HEV, a PHEV, a BEV, or an FCEV. "HEV" is an abbreviation for a hybrid electric vehicle. "PHEV" is an abbreviation for a plug-in hybrid electric vehicle. "BEV" is an abbreviation for a battery electric vehicle. "FCEV" is an abbreviation for a fuel cell electric vehicle. In the present embodiment, the autonomous vehicles 30 on multiple routes are AVs, enabling driving automation at a high level. "AV" is an abbreviation for an autonomous vehicle. The level of automation is, for example, either level 3 or level 4 in the classification of SAE. "SAE" is the abbreviation for the Society of Automotive Engineers. The autonomous vehicles 30 on multiple routes may also be MaaS dedicated vehicles. "MaaS" is an abbreviation for Mobility as a Service.

[0028] The network 50 includes the Internet, at least one WAN, at least one MAN, or any combination thereof. "WAN" is an abbreviation for a wide area network. "MAN" is an abbreviation for a metropolitan area network. The network 50 may also include at least one wireless network, at least one optical network, or any combination thereof. The wireless network is, for example, an ad hoc network, a cellular network, a wireless LAN, a satellite communication network, or a terrestrial microwave network. "LAN" is an abbreviation for a local area network.

[0029] Refer to Figure 1 , and an overview of the present embodiment will be described.

[0030] The operation management device 10 acquires schedule data representing a schedule for operating the autonomous vehicles 30 on multiple routes at fixed intervals. The operation management device 10 acquires performance data representing the operation performance, where the operation performance includes the times when the autonomous vehicles on each route arrive at each station specified for each route. The operation management device 10 detects, among the autonomous vehicles 30 on multiple routes, an autonomous vehicle whose delay exceeds a threshold as a delayed vehicle DeV, where the delay is the delay of the arrival time at any station included in the operation performance shown by the acquired performance data relative to the time corresponding to the operation schedule shown by the acquired schedule data. In this way, the operation management device 10 selects one or more autonomous vehicles on one or more routes whose operation intervals are to be adjusted from the autonomous vehicles 30 on multiple routes as affected vehicles AfV. The operation management device 10 calculates, based on the operation performance shown by the performance data, the waiting time at the next station to be indicated to the selected affected vehicles AfV. The operation management device 10 outputs time data representing the calculated waiting time.

[0031] According to the present embodiment, the operation interval of the autonomous vehicle can be adjusted according to the delay situation. Therefore, the countermeasures against the delay of the autonomous vehicle can be improved.

[0032] In Figure 3 the example, the autonomous vehicle VE belonging to one route among the autonomous vehicles 30 on multiple routes stops at the stations ST on that route. The autonomous vehicle VE includes a first autonomous vehicle V1, a second autonomous vehicle V2, and a third autonomous vehicle V3. In Figure 3 the example, the number of autonomous vehicles is three, but it can also be two or four or more. The stations ST include a first station S1, a second station S2, and a third station S3. In Figure 3 the example, the number of stations is three, but it can also be two or four. The number of stations can be more than the number of autonomous vehicles or less than the number of autonomous vehicles. The operation of the autonomous vehicle VE is planned such that the operation interval of each autonomous vehicle is 20 minutes. In Figure 3In the example, for the first station S1, the operation is planned as follows: the first autonomous vehicle V1 arrives at the first station S1 at 10:00, the second autonomous vehicle V2 arrives at the first station S1 at 10:20, and the third autonomous vehicle V3 arrives at the first station S1 at 10:40. For the second station S2, the operation is planned as follows: the first autonomous vehicle V1 arrives at the second station S2 at 9:40, the second autonomous vehicle V2 arrives at the second station S2 at 10:00, and the third autonomous vehicle V3 arrives at the second station S2 at 10:20. That is, the first autonomous vehicle V1 is the vehicle that travels first, the second autonomous vehicle V2 is the next subsequent vehicle, and the third autonomous vehicle V3 is the further subsequent vehicle. During the operation, depending on the weather, road conditions, or the situation of passengers, the arrival time may sometimes change forward or backward. When the autonomous vehicle VE arrives at the station ST, it sends the time data indicating the actual arrival time to the autonomous driving control device 20.

[0033] In one example, the operation management device 10 can be used to provide MaaS as a service for effectively utilizing mobility.

[0034] Refer to Figure 2 , and the configuration of the operation management device 10 of the present embodiment will be described.

[0035] The operation management device 10 includes a control unit 11, a storage unit 12, and a communication unit 13.

[0036] The control unit 11 includes at least one processor, at least one programmable circuit, at least one dedicated circuit, or any combination thereof. The processor is a general-purpose processor such as a CPU or GPU, or a dedicated processor dedicated to specific processing. "CPU" is an abbreviation for central processing unit. "GPU" is an abbreviation for graphicsprocessing unit. The programmable circuit is, for example, an FPGA. "FPGA" is an abbreviation for field-programmable gate array. The dedicated circuit is, for example, an ASIC. "ASIC" is an abbreviation for application specific integrated circuit. The control unit 11 controls each part of the operation management device 10 while executing the processing related to the operation of the operation management device 10.

[0037] The storage unit 12 includes at least one semiconductor memory, at least one magnetic memory, at least one optical memory, or any combination thereof. The semiconductor memory is, for example, a RAM or a ROM. "RAM" is an abbreviation for random access memory. "ROM" is an abbreviation for read only memory. The RAM is, for example, an SRAM or a DRAM. "SRAM" is an abbreviation for static random access memory. "DRAM" is an abbreviation for dynamic random access memory. The ROM is, for example, an EEPROM. "EEPROM" is an abbreviation for electrically erasable programmable read only memory. The storage unit 12 functions as, for example, a main storage device, an auxiliary storage device, or a cache memory. Data used in the operation of the operation management device 10 and data obtained through the operation of the operation management device 10 are stored in the storage unit 12.

[0038] The communication unit 13 includes at least one communication interface. The communication interface is, for example, a LAN interface. The communication unit 13 receives data used in the operation of the operation management device 10 and also transmits data obtained through the operation of the operation management device 10.

[0039] The functions of the operation management device 10 are implemented by a processor, which is the control unit 11, executing the operation management program of the present embodiment. That is, the functions of the operation management device 10 are implemented by software. The operation management program causes a computer to function as the operation management device 10 by causing the computer to execute the operations of the operation management device 10. That is, the computer executes the operations of the operation management device 10 in accordance with the operation management program and thereby functions as the operation management device 10.

[0040] The program can be pre-stored in a non-transitory computer-readable medium. The non-transitory computer-readable medium is, for example, a flash memory, a magnetic recording device, an optical disc, a magneto-optical recording medium, or a ROM. The distribution of the program is carried out, for example, by selling, transferring, or renting a portable medium such as an SD card, a DVD, or a CD-ROM storing the program. "SD" is an abbreviation for Secure Digital. "DVD" is an abbreviation for digital versatile disc. "CD-ROM" is an abbreviation for compact disc read only memory. The program can also be distributed by pre-storing the program in the memory of a server and transferring the program from the server to other computers. The program can also be provided as a program product.

[0041] A computer, for example, temporarily stores the program stored in a portable medium or the program transferred from a server in a main storage device. Then, the computer reads the program stored in the main storage device through a processor and executes the processing according to the read program through the processor. The computer can also directly read the program from the portable medium and execute the processing according to the program. The computer can also execute the processing according to the received program sequentially each time the program is transferred from the server to the computer. The processing can also be executed through a so-called ASP-type service, in which the transfer of the program from the server to the computer is not performed, but the function is realized only through the execution instruction and the result acquisition. "ASP" is an abbreviation for application service provider. The program includes information for the processing to be performed by an electronic computer and conforms to the program standard. For example, data that is not a direct instruction to the computer but has the nature of specifying the processing of the computer is equivalent to "information conforming to the program standard".

[0042] Part or all of the functions of the operation management device 10 can also be realized by a programmable circuit or a dedicated circuit as the control unit 11. That is, part or all of the functions of the operation management device 10 can also be realized by hardware.

[0043] Refer to Figure 6 , the operation of the operation management device 10 of the present embodiment will be described. This operation corresponds to the operation management method of the present embodiment.

[0044] In Figure 6 S101, the control unit 11 of the operation management device 10 acquires schedule data. The schedule data represents an operation plan for causing the autonomous driving vehicles 30 on a plurality of routes including the autonomous driving vehicle VE to run at regular intervals. For example, the schedule data is registered by an operation management operator. In Figure 3In the example, the operation plan includes the time when the autonomous vehicle VE arrives at the station ST. S101 is performed only once before the start of the operation of the autonomous vehicle VE, but it can also be performed once every day before the start time of the operation of the autonomous vehicle VE.

[0045] In Figure 6 In S102, the control unit 11 of the operation management device 10 acquires actual performance data. The actual performance data represents the operation actual performance including the time when the autonomous vehicles on each route, such as the autonomous vehicle VE, arrive at each station specified for each route, such as the station ST. Specifically, the communication unit 13 of the operation management device 10 receives the actual performance data received by the autonomous driving control device 20 from the autonomous vehicles 30 on multiple routes from the autonomous driving control device 20. The control unit 11 acquires the actual performance data received through the communication unit 13. In Figure 3 the example, the operation actual performance includes the time when the autonomous vehicle VE arrives at the station ST. The processing after S102 is performed every ten minutes, but it can also be performed every minute or at any other arbitrary interval.

[0046] In Figure 6 S103, the control unit 11 of the operation management device 10 detects an autonomous vehicle with a delay exceeding the threshold in the autonomous vehicle VE as a delayed vehicle DeV, where the delay is the delay of the arrival time at any station included in the operation actual performance indicated by the actual performance data acquired in S102 relative to the time corresponding to the operation plan indicated by the planned data acquired in S101. The threshold is, for example, 5 minutes. Specifically, the control unit 11 calculates the delay by subtracting the time corresponding to the operation plan from the time when each vehicle of the autonomous vehicle VE arrives at any station. The control unit 11 detects an autonomous vehicle for which the calculated delay exceeds the threshold as a delayed vehicle DeV. In Figure 3In the example, in the operation plan, at the time point of 10:00, the first autonomous driving vehicle V1 should arrive at the first station S1. In the actual operation results, the time when the first autonomous driving vehicle V1 arrives at the first station S1 is 10:10, which is 10 minutes later than the operation plan. The second autonomous driving vehicle V2 arrives at the second station S2 at 9:50 and is about to arrive at the first station S1 at the time point of 10:10. The third autonomous driving vehicle V3 arrives at the third station S3 at 10:00 and is on the way to the second station S2 at the time point of 10:10. The control unit 11 calculates the delay of the first autonomous driving vehicle V1 as +10 minutes at the time point of 10:10. The control unit 11 calculates the delay of the second autonomous driving vehicle V2 as -10 minutes. The control unit 11 calculates the delay of the third autonomous driving vehicle V3 as 0 minutes. The control unit 11 detects the first autonomous driving vehicle V1 with a delay exceeding 5 minutes as the delayed vehicle DeV. The control unit 11 repeatedly performs the processes of S102 and S103 until the delayed vehicle DeV is detected.

[0047] In Figure 6 In S104, the control unit 11 of the operation management device 10 selects an autonomous driving vehicle to adjust the operation interval from the autonomous driving vehicles VE as the affected vehicle AfV. As a method for selecting the affected vehicle AfV, any method can be adopted. In Figure 3 the example, the second autonomous driving vehicle V2 and the third autonomous driving vehicle V3 are candidates for the affected vehicle AfV.

[0048] As the first method, the control unit 11 selects all other autonomous driving vehicles on the route to which the delayed vehicle DeV belongs as the affected vehicle AfV. In Figure 3 the example, the control unit 11 selects the second autonomous driving vehicle V2 and the third autonomous driving vehicle V3 as the affected vehicle AfV.

[0049] As the second method, the control unit 11 determines which other autonomous driving vehicle on the route to which the delayed vehicle DeV belongs to be selected as the affected vehicle AfV according to the magnitude of the delay calculated in S103. For example, when the delay calculated in S103 exceeds 5 minutes and is less than or equal to 10 minutes, the control unit 11 selects only the subsequent one of the delayed vehicle DeV as the affected vehicle AfV. When the delay calculated in S103 exceeds 10 minutes, the control unit 11 selects all other autonomous driving vehicles on the route to which the delayed vehicle DeV belongs as the affected vehicle AfV. In Figure 3 the example, the delay of the first autonomous driving vehicle V1 calculated in S103 is +10 minutes. Therefore, the control unit 11 selects only the second autonomous driving vehicle V2, which is the subsequent one of the first autonomous driving vehicle V1, as the affected vehicle AfV.

[0050] As a third method, the control unit 11 determines which other autonomous vehicle belonging to the route of the delayed vehicle DeV to select as the influencing vehicle AfV based on the magnitude of the difference between the running interval and the desired interval. Specifically, the control unit 11 calculates the running interval of the autonomous vehicle VE on the route to which the delayed vehicle DeV belongs based on the running performance. The control unit 11 calculates the difference between the calculated running interval and the desired interval. The control unit 11 selects the autonomous vehicle for which the calculated difference is greater than the desired interval as the influencing vehicle AfV. For example, the control unit 11 selects an autonomous vehicle whose running interval deviates from 20 minutes, which is the desired interval, by more than 5 minutes, that is, an autonomous vehicle whose running interval is less than 15 minutes or more than 25 minutes, as the influencing vehicle AfV. In Figure 3 the example, at the time point of 10:10, the control unit 11 calculates the running interval H12 between the first autonomous vehicle V1 and the second autonomous vehicle V2 as "desired interval (20 minutes) + delay of the second autonomous vehicle V2 (-10 minutes) - delay of the first autonomous vehicle V1 (+10 minutes) = 0 minutes". The difference between the running interval H12 and the desired interval is 20 minutes. The control unit 11 calculates the running interval H23 between the third autonomous vehicle V3 and the second autonomous vehicle V2 as the desired interval (20 minutes) + delay of the third autonomous vehicle V3 (+0 minutes) - delay of the second autonomous vehicle V2 (-10 minutes) = 30 minutes. The difference between the running interval H23 and the desired interval is 10 minutes. Therefore, the control unit 11 selects the second autonomous vehicle V2 and the third autonomous vehicle V3 as the influencing vehicles AfV.

[0051] In Figure 6 S105, the control unit 11 of the operation management device 10 calculates the waiting time at the next station to be indicated to the influencing vehicle AfV selected in S104 based on the running performance shown in the performance data obtained in S102. In Figure 3 the example, in the case of adopting the first method, the control unit 11 calculates the waiting time of the second autonomous vehicle V2, which is the selected influencing vehicle AfV, at the first station S1 and the waiting time of the third autonomous vehicle V3 at the second station S2. In the case of adopting the second method, the control unit 11 calculates the waiting time of the second autonomous vehicle V2, which is the influencing vehicle AfV, at the first station S1. In the case of adopting the third method, it is the same as the first method. As a method for calculating the waiting time, any method can be adopted. For example, the control unit 11 calculates the time when the running interval in the running performance is the same as the running interval in the operation plan as the waiting time. In Figure 3In the example, in the case of adopting the first method, the control unit 11 calculates the waiting time of the second autonomous vehicle V2 at the first station S1 as 20 minutes. Thus, the control unit 11 changes the running interval between the first autonomous vehicle V1 as the delayed vehicle DeV and the second autonomous vehicle V2 as the affected vehicle AfV from 0 minute to 20 minutes. The control unit 11 calculates the waiting time of the third autonomous vehicle V3 at the second station S2 as 10 minutes to change the running interval between the second autonomous vehicle V2 as the affected vehicle AfV and the third autonomous vehicle V3 as the affected vehicle AfV from 30 minutes to 20 minutes. In the case of adopting the second method, the control unit 11 only calculates the waiting time of the second autonomous vehicle V2 at the first station S1 as 20 minutes. In the case of adopting the third method, it is the same as the first method.

[0052] In Figure 6 S106, the control unit 11 of the operation management device 10 outputs time data indicating the waiting time calculated in S105. Specifically, the control unit 11 causes the time data to be sent to the communication unit 13. The communication unit 13 sends the time data to the autonomous driving control device 20. The autonomous driving control device 20 receives the time data from the operation management device 10. The autonomous driving control device 20 sends the received time data to the affected vehicle AfV. The affected vehicle AfV receives the time data from the autonomous driving control device 20. The affected vehicle AfV waits at the next station according to the waiting time indicated by the received time data. In Figure 3 the example, in the case of adopting the first method, the second autonomous vehicle V2 as the affected vehicle AfV starts waiting at the first station S1 as the next station at 10:10 for 20 minutes. The third autonomous vehicle V3 as the affected vehicle AfV waits at the second station S2 as the next station for 10 minutes. In the case of adopting the second method, the second autonomous vehicle V2 as the affected vehicle AfV waits at the first station S1 as the next station for 20 minutes. In the case of adopting the third method, it is the same as the first method. Thus, by sharing the delay information of some autonomous vehicles with other autonomous vehicles, the balance of the overall operation can be achieved. As a result, the congestion situation where passengers concentrate on some autonomous vehicles can be balanced.

[0053] Figure 4This is a diagram showing the operating conditions of the second autonomous vehicle V2 and the third autonomous vehicle V3 at the 10:20 time point in the case of adopting the first method. At the 10:20 time point, 10 minutes have just passed since the second autonomous vehicle V2, which is an affected vehicle AfV, started waiting at the first station S1. The departure time of the second autonomous vehicle V2 is 10:30, 10 minutes after waiting again. The third autonomous vehicle V3, which is an affected vehicle AfV, has just arrived at the second station S2. The departure time of the third autonomous vehicle V3 is 10:30 after waiting for 10 minutes.

[0054] Figure 5 This is a diagram showing the operating conditions of the second autonomous vehicle V2 and the third autonomous vehicle V3 at the 10:30 time point in the case of adopting the first method. At the 10:30 time point, the second autonomous vehicle V2, which is an affected vehicle AfV, has just departed from the first station S1. The third autonomous vehicle V3, which is an affected vehicle AfV, has just departed from the second station S2.

[0055] After S106, the control unit 11 performs the process of S102. After S106, the control unit 11 may also perform the process of S102 after changing the operation plan shown in the operation plan data obtained in S101. That is, the control unit 11 can reflect the waiting time calculated in S105 in the operation plan and use the operation plan reflecting the waiting time to detect the delayed vehicle DeV in S103.

[0056] Alternatively, in S106, when outputting the time data, the control unit 11 also outputs indication data for indicating that the affected vehicle AfV will notify the passengers in the affected vehicle AfV or the vehicles around the affected vehicle AfV of the adjusted operation interval. Specifically, the control unit 11 may send the indication data to the communication unit 13. In such a modification, the communication unit 13 sends the indication data to the autonomous driving control device 20. The autonomous driving control device 20 receives the indication data from the operation management device 10. The autonomous driving control device 20 sends the received indication data to the affected vehicle AfV. The affected vehicle AfV receives the indication data from the autonomous driving control device 20. The affected vehicle AfV notifies the passengers in the affected vehicle AfV or the vehicles around the affected vehicle AfV of the condition of the adjusted operation interval according to the received indication data. In Figure 3 and Figure 4In the example, when the first method is adopted, at the time point of 10:10, as the second autonomous driving vehicle V2 affecting the vehicle AfV, it starts waiting at the first station S1 which is the next station. The second autonomous driving vehicle V2 starts to output messages such as "Adjusting running interval", "Depart at 10:30", or "Wait for another 20 minutes" on the signage inside and outside the vehicle. The second autonomous driving vehicle V2 can also output the same messages audibly inside the vehicle. At this time, the third autonomous driving vehicle V3 affecting the vehicle AfV does not output a notice. At the time point of 10:20, the second autonomous driving vehicle V2 outputs messages such as "Adjusting running interval", "Depart at 10:30", or "Wait for another 10 minutes" on the signage inside and outside the vehicle. When the third autonomous driving vehicle V3 starts waiting at the second station S2 which is the next station, it starts to output messages such as "Adjusting running interval", "Depart at 10:30", or "Wait for another 10 minutes" on the signage inside and outside the vehicle. At the time point of 10:30, the second autonomous driving vehicle V2 and the third autonomous driving vehicle V3 end the output of messages. When the second method is adopted, only the second autonomous driving vehicle V2 outputs messages. When the third method is adopted, it is the same as the first method. In this way, the notification is automated. Thus, compared with the case where the crew of the autonomous driving vehicle manually makes notifications, the burden on the crew can be reduced and correct guidance can be provided. Not only can notifications be made automatically inside the vehicle but also outside the vehicle, and the situation of adjusting the running interval can be shared with passengers and surrounding autonomous driving vehicles, making the situation visible.

[0057] The autonomous driving control device 20 can also be integrated with the operation management device 10. In this case, it can also be that the control unit 11 of the operation management device 10 obtains the actual performance data by receiving the actual performance data from the autonomous driving vehicles 3 on multiple routes through the communication unit 13 in S102. It can also be that the control unit 11 outputs the time data and the instruction data by sending the time data and the instruction data to the affected vehicle AfV through the communication unit 13 in S106.

[0058] In one example, the above processing procedure can be executed when providing a service (MaaS) using the autonomous driving vehicles 30 on multiple routes. In this case, the information processing method implemented by the above processing procedure is an example of a method for providing a service (MaaS) using the autonomous driving vehicles 30 on multiple routes.

[0059] As described above, in the present embodiment, the control unit 11 of the operation management device 10 acquires plan data representing an operation plan for causing the autonomous driving vehicles 30 on a plurality of routes to operate at fixed intervals. The control unit 11 of the operation management device 10 acquires actual data representing the operation results, where the operation results include the times when the autonomous driving vehicles on each route arrive at each station specified for each route. The control unit 11 of the operation management device 10 detects, as delayed vehicles DeV, the autonomous driving vehicles whose delay exceeds a threshold among the autonomous driving vehicles 30 on a plurality of routes, where the delay is the delay of the arrival time at any station included in the operation results shown by the acquired actual data with respect to the time corresponding to the operation plan shown by the acquired plan data. In this way, the control unit 11 selects, as affected vehicles AfV, one or more autonomous driving vehicles on a route whose operation interval is to be adjusted from among the autonomous driving vehicles 30 on a plurality of routes. The control unit 11 of the operation management device 10 calculates, based on the operation results shown by the actual data, the waiting time at the next station to be indicated to the selected affected vehicles AfV. The control unit 11 of the operation management device 10 outputs time data representing the calculated waiting time.

[0060] According to the present embodiment, the operation interval of the autonomous driving vehicle can be adjusted according to the delay situation. Therefore, the countermeasures against the delay of the autonomous driving vehicle can be improved.

[0061] In the present embodiment, the affected vehicles AfV are selected from the routes to which the delayed vehicles DeV belong, but the affected vehicles AfV may also be selected from other routes to which the delayed vehicles DeV do not belong. When autonomous driving vehicles on other routes are also selected as the affected vehicles AfV, it may be manually set which route is to be the object of selection, that is, which route is to be considered as the transfer object. By collaborating with the autonomous driving vehicles on other routes as well, the transfer time and waiting time of passengers can be optimized.

[0062] The present disclosure is not limited to the above-described embodiment. For example, two or more function blocks described in the block diagram may be integrated, or one function block may be divided. Instead of executing two or more steps described in the flowchart in chronological order as described, two or more steps described in the flowchart may be executed in parallel or in a different order according to the processing ability of the device that executes each step or as needed. In addition, changes may be made within the scope not departing from the gist of the present disclosure.

Claims

1. An operation management device includes a control unit, and the control unit performs the following operations: Obtain plan data representing an operation plan for enabling autonomous vehicles on multiple routes to operate at fixed intervals; Obtain performance data representing the actual performance, where The operation results include the times when the autonomous vehicles on each route arrive at each station specified for each route; When a delayed vehicle is detected among the autonomous vehicles on the multiple routes, and the delay exceeds a threshold, one or more routes of autonomous vehicles to be adjusted in operation interval are selected from the autonomous vehicles on the multiple routes as affected vehicles, where the delay is the delay of the arrival time at any station included in the operation results shown by the obtained actual performance data relative to the time corresponding to the operation plan shown by the obtained plan data; Calculate the waiting time at the next station to be indicated to the selected affected vehicles based on the operation results shown by the actual performance data; and Output time data representing the calculated waiting time.

2. The operation management device according to claim 1, wherein when the delayed vehicle is detected, the control unit selects all other autonomous vehicles on the route to which the delayed vehicle belongs as the affected vehicles.

3. The operation management device according to claim 1, wherein when the delayed vehicle is detected, the control unit determines which other autonomous vehicle on the route to which the delayed vehicle belongs is to be selected as the affected vehicle according to the magnitude of the delay.

4. The operation management device according to claim 1, wherein when the delayed vehicle is detected, the control unit determines which other autonomous vehicle on the route to which the delayed vehicle belongs is to be selected as the affected vehicle according to the magnitude of the difference between the operation interval and the desired interval.

5. The operation management device according to any one of claims 1 to 4, wherein when outputting the time data, the control unit also outputs indication data, and the indication data is data for indicating that the affected vehicles notify the passengers in the affected vehicles or the vehicles around the affected vehicles that the operation interval is being adjusted.

6. A Mobility as a Service (MaaS) provision method that uses the operation management device according to claim 1.

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