Information processing device

Abstract

To provide a technique for calculating utilization of on-demand traffic with high accuracy.SOLUTION: An information processing device comprises: an acquisition unit that acquires utilization information for on-demand traffic that operates in accordance with users' request; a derivation unit that derives a utilization distribution of on-demand traffic on the basis of the acquired utilization information; and an extraction unit that extracts bias of operation from the utilization distribution derived by the derivation unit. The utilization information acquired contains request information through which a user applied for use of on-demand traffic and information indicating applicability and non-applicability of the request information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a technique for deriving a utilization state in demand-responsive transportation. [Background technology]

[0002] Patent Document 1 discloses a demand transportation operation system that operates a demand transportation system that operates vehicles in response to user requests. This demand transportation operation system receives passenger requests including desired departure and arrival times, departure points and destinations, and creates a dispatch plan for demand transportation vehicles based on the collected passenger requests. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2019 / 106745 Summary of the Invention [Problem to be solved by the invention]

[0004] In order to provide transportation resources appropriately in on-demand transportation, it is preferable to be able to accurately calculate the usage status of on-demand transportation.

[0005] An object of the present invention is to provide a technique for accurately calculating the utilization status of demand-based transportation. [Means for solving the problem]

[0006] In order to solve the above problems, an information processing device according to an embodiment of the present invention includes an acquisition unit that acquires utilization information of on-demand transportation that operates in response to a user request, a derivation unit that derives a utilization distribution of on-demand transportation based on the acquired utilization information, an extraction unit that extracts a bias in operation from the utilization distribution derived by the derivation unit, and an output unit that outputs, in descending order of priority, a number of means for reducing the bias in operation based on the utilization information and the bias in operation. The acquired utilization information includes request information in which a user has applied to use on-demand transportation, and information indicating whether the request information has been established or not. The multiple means include any one or more of changing the number of vehicles operating at a specified time and in a specified location, adding vehicles that operate on a spot basis at a specified time and in a specified location, adding vehicles that travel along a specified route, changing the location of stops, and increasing or decreasing the number of stops. Effect of the Invention

[0007] According to the present invention, a technique for accurately calculating the utilization status of demand-responsive transportation can be provided. [Brief description of the drawings]

[0008] [Figure 1] 1 is a diagram for explaining a user request for dispatching a vehicle through demand-responsive transportation and a travel route according to the request. FIG. [Diagram 2] FIG. 1 is a diagram illustrating a functional configuration of an information processing system according to an embodiment. [Diagram 3] 13 is a flowchart of a process for analyzing the usage status of demand-responsive transportation by an information processing device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Figure 1 is a diagram explaining a user request for on-demand transportation and the route that corresponds to the request. On-demand transportation dispatches a vehicle in response to a user request to transport the user and the user's luggage. Users can also share the dispatched vehicle, like a bus.

[0010] User requests are accepted up to a specified acceptance deadline, such as the day before the operation date or a specified time before the operation time. In demand-responsive transportation, it is desirable to operate in response to all user requests, but since there is a limit to the number of vehicles that can be dispatched, depending on the content of a user request, the request may be rejected. User requests are collected up to the specified acceptance deadline by the operation decision device, and a decision is made as to whether to accept or reject the request. The operation decision device accepts user requests in accordance with preset rules and creates an operation plan corresponding to the accepted requests.

[0011] A user request specifies a departure point, a destination, and a date and time. FIG. 1 shows user requests, with the first request being departure point A and destination abc, the second request being departure point B and destination abc, the third request being departure point C and destination abc, the fourth request being departure point D and destination d, the fifth request being departure point E and destination e, and the sixth request being departure point F and destination f. It is assumed that these requests are intended to depart at the same time. The departure point A to departure point D is the same. Also, the request from departure point A to departure point C is the same destination abc.

[0012] Since the operation decision device determines that many user requests are to be fulfilled, requests with overlapping departure points or destinations are more likely to be fulfilled. Also, the further away the departure point and destination indicated in a request are compared to requests from other users, the more likely the request is to be rejected. Therefore, the first to third requests are fulfilled because they have the same departure point and destination. Also, the fifth request is fulfilled because its departure point E is close to the destination abc indicated in the first to third requests. An operation route 40 is set for the first to third requests and the fifth request.

[0013] On the other hand, since the destination d of the fourth request is far from the destination abc of the first request, etc., the operation route 42 is set for the fourth request. If a vehicle other than the vehicle operating the first request, etc. cannot operate, the fourth request will not be established. Furthermore, the sixth request is farther away from the departure point and destination than the first request to the fifth request, so it is more likely to be established than the fourth request. In this way, a user's request may be established in relation to other requests.

[0014] There are stations from departure point A to departure point D and destination point e, and many requests are collected there. Requests that are outside the areas where requests are concentrated or during the time period after the requests are concentrated result in difficulty in using on-demand transportation. It is desirable to resolve the situation in which some users find it difficult to use. Therefore, in order to find a method for resolving the situation in which some users find it difficult to use, the information processing system of the embodiment derives the bias in the usage distribution and finds the provision of transportation resources that reduce the bias. For example, measures such as introducing many vehicles can be taken in areas where requests are concentrated, which are indicated by the bias in the usage distribution of on-demand transportation. In addition, since the bias in the usage distribution can change in the medium to long term, it is desirable to adjust the number of vehicles introduced in accordance with the change.

[0015] In addition, the departure point and destination in demand transportation may be the location information of a preset bus stop, or may be location information indicated by latitude or longitude. In other words, the vehicle of demand transportation may move between preset bus stops, or may move to any location desired by the user. The date and time indicated in the request may specify the date and time of departure.

[0016] Fig. 2 shows the functional configuration of the information processing system 1 according to the embodiment. In Fig. 2, each element described as a functional block performing various processes can be configured in terms of hardware with a circuit block, memory, or other LSI, and in terms of software, can be realized by a program loaded into memory, etc. Therefore, it will be understood by those skilled in the art that these functional blocks can be realized in various forms by hardware alone, software alone, or a combination thereof, and are not limited to any one of them.

[0017] The information processing system 1 includes an information processing device 10, an operation decision device 12, and a user terminal device 14. The user terminal device 14 may be a portable terminal device held by each user, and holds an application program for requesting vehicle operation. The user terminal device 14 executes the application program to request operation, transmits request information to the operation decision device 12, and receives response information from the operation decision device 12 indicating whether the request has been established or not. In addition, when transmitting the request information, the user terminal device 14 transmits it with a user ID attached.

[0018] The request information includes departure point information, destination information, and date and time information. The departure point information and destination information may be, for example, location information indicated by latitude and longitude, or may be location information of a preset bus stop. The date and time information indicates a desired departure time, and may be a date and a time zone.

[0019] The operation determination device 12 has a communication unit 32, an operation determination unit 34, and a vehicle information storage unit 36. The communication unit 32 is capable of communicating with the operation determination device 12 and the user terminal device 14. The communication unit 32 receives request information from the user terminal device 14, and transmits response information to the request information to the user terminal device 14.

[0020] The vehicle information storage unit 36 ​​stores operating vehicle information of vehicles that operate in response to user requests. The operating vehicle information includes a vehicle ID, the number of occupants of the vehicle, vehicle location information, and the like.

[0021] The operation decision unit 34 receives request information from multiple users and decides whether to accept or reject the request information based on the operating vehicle information. The operation decision unit 34 has a judgment program for judging whether a request is accepted or rejected. The judgment program has, for example, logic for deriving a priority from the request information and derives a judgment result of acceptance or rejection based on the derived priority. In order to accept many requests, the judgment program is more likely to accept requests with a departure point and a destination close to each other. The judgment program may use a neural network method and may be able to derive whether each request is accepted or rejected by inputting operating vehicle information and multiple pieces of request information.

[0022] The operation decision unit 34 associates the request information with response information indicating whether the request information is satisfied or not, and stores the response information as utilization information in the operation decision device 12. The utilization information of the demand transportation is transmitted to the information processing device 10 via the communication unit 32.

[0023] An operation plan for the vehicle is created by the operation decision unit 34's operation decision. The operation plan includes the vehicle's travel route and the target times for arriving at the departure point and destination. The operation plan is transmitted to, for example, a server device of the vehicle's operating company, and the vehicle travels according to the operation plan. The operation decision device 12 may hold a user ID and profile information of the user.

[0024] The information processing device 10 includes a communication unit 20, an acquisition unit 22, a derivation unit 24, an extraction unit 26, an estimation unit 28, and an output unit 30. The communication unit 20 receives usage information of on-demand transportation from the operation determination device 12, and the acquisition unit 22 acquires the usage information of on-demand transportation. The usage information includes request information for applying to use on-demand transportation and response information indicating whether the request information has been granted or not. The usage information may also include profile information of the user who issued the request information.

[0025] The derivation unit 24 derives the utilization distribution of the demand transportation based on the acquired utilization information. When the departure point and the destination are location information indicated by latitude and longitude, the utilization distribution for each area divided into a predetermined range is derived, and when the departure point and the destination are bus stops, the utilization distribution for each bus stop is derived.

[0026] The derivation unit 24 derives the number of accepted requests at the departure point, the number of accepted requests at the destination, the number of successful requests at the destination, the number of unsuccessful requests at the departure point, and the number of unsuccessful requests at the destination as the usage distribution for each time period. The derivation unit 24 may also derive the frequency of accepted requests and the frequency of unsuccessful requests for each time period and location, and may derive the usage frequency per hour for each stop. The derivation unit 24 may also derive the travel distance of the vehicle for the requests, and may derive the total travel distance by adding up the travel distances of each request. In this way, the derivation unit 24 derives the number of accepted requests, the number of successful requests, the number of unsuccessful requests, the frequency of unsuccessful requests, the total travel distance, and the like for each time period and for each stop or a specified area as the usage distribution of demand transportation. The usage distribution derived by the derivation unit 24 includes information on unsuccessful requests, and therefore accurately represents the demand of users.

[0027] The extraction unit 26 extracts the bias of the operation from the utilization distribution derived by the derivation unit 24. The extraction unit 26 extracts, as the bias of the operation, the time period and the place where the number of accepted requests is concentrated to a predetermined number or more, and the time period and the place where the frequency of request failure is higher than a predetermined frequency. For example, if the utilization frequency of a bus stop in a certain time period is higher than a predetermined frequency, it is extracted that the bus stop in that time period has a bias. The extraction unit 26 extracts, as the bias of the operation, the time period and the place where requests are concentrated, and the time period and the place where the refusal of requests is concentrated. In addition, the extraction unit 26 may derive, as the bias of the operation, the bias of the travel distance of the vehicle, that is, the long-distance demand, based on the travel distance of the vehicle. The extraction unit 26 may be a program using a neural network technique, and may input the utilization distribution to extract the time period and the place where the bias of the operation is present.

[0028] By using information on which user requests were not satisfied, it is possible to find users who will be disadvantaged and accurately derive the bias in usage. When operators see the bias in operation, they can take appropriate measures according to the bias.

[0029] The estimation unit 28 executes a simulation based on the bias in operation extracted by the extraction unit 26 and the utilization information of demand transportation, and estimates the utilization status when the operation service is changed. The estimation unit 28 estimates the number of requests that are established and the total riding distance of users when the number of vehicles operating in the time period and place where requests are concentrated is changed.

[0030] The estimation unit 28 also estimates the number of unsuccessful requests and the total riding distance of the user when a vehicle that operates on a spot basis is added to a time period and route where requests are concentrated, and the user is transported. The estimation unit 28 also estimates the number of unsuccessful requests and the total riding distance of the user when a vehicle that travels along a route where requests are concentrated is added, and the user is transported. When the departure point and destination are preset stops, the estimation unit 28 estimates the number of unsuccessful requests and the total riding distance of the user when the location of the stop is changed, a stop is added, or a stop is reduced. In other words, the estimation unit 28 can estimate a change in the usage situation when the vehicle operation service is changed, based on the bias in operation extracted by the extraction unit 26 and the usage information of demand transportation.

[0031] In this way, the estimation unit 28 can estimate the effect of changing the service to eliminate the bias in operation. This estimation makes it possible to grasp the content of the service change that reduces the number of failed requests or increases the total riding distance of users.

[0032] The estimation unit 28 may execute a simulation based on the profile information of the user. A ride-sharing condition is set in the profile information of the user, and the user is refused ride-sharing with a user having profile information of the set attribute. For example, it is possible to set a condition that a woman refuses to ride-sharing with a man, or a condition that an employee of a company refuses to ride-sharing with an employee of a competitor. When a regularly-operated vehicle or a roaming vehicle is added, the estimation unit 28 may estimate that a user who has set a ride-sharing condition will not ride in a regularly-operated vehicle or a roaming vehicle.

[0033] In addition, when a service change is made, such as adjusting the number of vehicles in operation, adding vehicles that make regular spot runs, or adding vehicles that make rounds, the estimation unit 28 may estimate which service change will be more effective, for example, which service change will be able to significantly reduce the number of unsuccessful requests, and derive a priority order for each type of service change based on the estimation result.

[0034] The output unit 30 outputs to a display or an external server device an estimation result indicating the effect of making the service change estimated by the estimation unit 28. The output unit 30 may output recommended service changes based on the priority order for each type of service change.

[0035] 3 is a flowchart of a process for analyzing the usage status of demand transportation by the information processing device 10. The acquisition unit 22 of the information processing device 10 acquires usage information of demand transportation from the operation decision device 12 (S10). This usage information includes user request information and response information indicating whether the request information is established or not.

[0036] The derivation unit 24 derives a utilization distribution from the utilization information of the demand transportation (S12). The utilization distribution includes the utilization frequency for each time period in a certain area or stop, the number of accepted requests, the number of unsuccessful requests, and the like.

[0037] The extraction unit 26 extracts the bias of operation from the utilization distribution derived by the derivation unit 24 (S14). The extracted bias of operation includes, for example, information on time periods and locations where requests are concentrated to a predetermined value or more, and time periods and locations where requests are frequently not satisfied.

[0038] The estimation unit 28 executes a simulation for reducing the bias in operation extracted by the extraction unit 26, and estimates the effect (S16). For example, the estimation unit 28 estimates the number of requests that will not be satisfied when a circulating vehicle or a regularly scheduled vehicle is added to a location where requests are concentrated. The estimation unit 28 derives a priority order for service changes according to the effect from the simulation results. The output unit 30 outputs, in descending order of priority, the multiple service changes estimated by the estimation unit 28 as a means for reducing bias in operation (S30).

[0039] It should be understood that the embodiments are merely illustrative, that various modifications are possible in the combination of the components, and that such modifications are also within the scope of the present invention. [Explanation of symbols]

[0040] 1 information processing system, 10 information processing device, 12 operation decision device, 14 user terminal device, 20 communication unit, 22 acquisition unit, 24 derivation unit, 26 extraction unit, 28 estimation unit, 30 output unit, 32 communication unit, 34 operation decision unit, 36 vehicle information storage unit.

Claims

1. An acquisition unit that acquires information on the use of demand-responsive transportation that operates in response to a user request; A derivation unit that derives a utilization distribution of demand-based transportation based on the acquired utilization information; an extraction unit that extracts a bias in operation from the utilization distribution derived by the derivation unit; an output unit that outputs a plurality of means for reducing the bias in operation in order of priority based on the utilization information and the bias in operation, The acquired usage information includes request information in which the user applies to use demand-responsive transportation and information indicating whether the request information has been established or not; The information processing device, characterized in that the multiple means include changing the number of vehicles operating during a specified time period and at a specified location, adding vehicles that operate on a regular spot basis during a specified time period and at a specified location, adding vehicles that travel along a specified route, changing the location of stops, and increasing or decreasing the number of stops.

2. The information processing device according to claim 1, characterized in that the output unit outputs the priority order of the multiple measures derived based on the estimated result regarding the change in the number of unsuccessful requests due to the implementation of the measures by estimating the implementation of the multiple measures to reduce the bias in operation.

3. The information processing device according to claim 1 or 2, characterized in that the output unit outputs a priority order of the multiple means derived based on an estimated result regarding a change in the user's total travel distance due to the implementation of multiple measures that will reduce the bias in operation, by estimating the implementation of the measures.

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