Vehicle allocation system, vehicle allocation method, vehicle allocation program

Abstract

To provide a vehicle allocation plan for a plurality of passengers ride-sharing a vehicle; more specifically, to provide an efficient vehicle allocation plan for group ride-sharing.SOLUTION: A vehicle allocation system is configured to: register ride-sharing group information that defines a relationship between a plurality of passengers who approve ride-sharing; acquire vehicle allocation reservation information for the plurality of passengers including boarding and disembarking locations; and generate a vehicle allocation plan based on the boarding and disembarking locations included in the plurality of pieces of vehicle allocation reservation information so that a vehicle allocation cost for one or the plurality of vehicles is minimized and only passengers who are approved for ride-sharing based on the ride-sharing group information can ride-share.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a vehicle dispatch system, a vehicle dispatch method, and a vehicle dispatch program that generate a joint vehicle dispatch plan. [Background technology]

[0002] In the past, public transportation such as buses allowed multiple passengers to share a ride. However, this type of ride sharing was operated on a fixed route like a route bus, and it was not possible to change the route according to the requests of each passenger.

[0003] The Ministry of Land, Infrastructure, Transport and Tourism decided to introduce a taxi ride-sharing service system on October 29, 2021. Under the new ride-sharing service system, passengers will share buses, taxis, etc., and will be able to flexibly change routes according to the requests of each passenger.

[0004] Patent Document 1 discloses a technology aimed at suitably dynamically generating operation plans. Patent Document 1 describes a method for acquiring multiple operation plans that indicate routes for operating a vehicle while passengers board or disembark, generated based on passenger information including boarding or disembarking points and boarding or disembarking times for multiple passengers sharing the vehicle. A list of the acquired operation plans is displayed on the terminal device of each of multiple operation companies, and a selection input is received from the terminal device of any of the operation companies to select from the list the operation plan for which an order is accepted. Patent Document 1 also describes a method for generating an operation plan by clustering passengers and assigning one bus to each cluster.

[0005] Patent Document 1 discloses technology related to a ride-sharing service that is characterized by generating multiple operation plans based on passenger information including boarding or disembarking points and boarding or disembarking times, and selecting an operation plan to be ordered from a list of the multiple operation plans.

[0006] Patent Document 2 discloses a demand-based operation management system applicable to public transportation services such as buses. Patent Document 2 describes a control method for a demand-based operation management system including a vehicle operating according to an operation plan, a first user terminal, a second user terminal, and an operation management device communicably connected to the vehicle, the first user terminal, and the second user terminal, in which, after the vehicle starts operating according to a first operation plan, if the operation management device receives a first use request from the first user terminal that includes a first boarding / alighting point and also receives a second use request from the second user terminal that includes a second boarding / alighting point, the operation management device notifies the vehicle of a second operation plan that includes stops at points between the first boarding / alighting point and the second boarding / alighting point, and the vehicle, having received the notification of the second operation plan, starts operating according to the second operation plan.

[0007] Patent document 2 discloses technology related to a demand-based operation service, which is characterized by generating a second operation plan with a stop location between a first user terminal and a second user terminal after starting operation according to a first operation plan and receiving usage requests from the first user terminal and the second user terminal. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] International Publication No. 2020 / 262673 [Patent Document 2] Patent No. 6273656 Summary of the Invention [Problem to be solved by the invention]

[0009] Demand for ride-sharing services is increasing in order to alleviate the shortage of taxi and bus drivers and to reduce the financial burden on individual passengers. However, ride-sharing with strangers poses challenges, such as the risk of conflict between passengers and the lack of clarity regarding contractual responsibility between passengers and crew.

[0010] Furthermore, under the new ride-sharing service system, determining an appropriate route based on the boarding and disembarking locations of multiple passengers would require complex calculations, making it difficult to implement.

[0011] In view of the above-mentioned problems, an object of the present invention is to provide a vehicle allocation plan for vehicles in which multiple passengers share a ride. More specifically, an object of the present invention is to provide an optimal vehicle allocation plan that takes into account the relationships between passengers who approve ride-sharing in a ride-sharing service. [Means for solving the problem]

[0012] [1] A vehicle dispatch system that provides a vehicle dispatch plan for vehicles shared by multiple passengers, a group registration unit that registers sharing group information that defines the relationship between a plurality of passengers who approve sharing; an acquisition unit that acquires ride reservation information of a plurality of passengers, including boarding locations and / or disembarking locations; A vehicle dispatch system comprising: a vehicle dispatch plan generation unit that generates a vehicle dispatch plan based on the boarding locations and / or disembarking locations included in the plurality of vehicle dispatch reservation information so that the dispatch cost of one or more vehicles is minimized and only passengers approved to share the vehicle according to the shared group information share the vehicle. [2] The acquisition unit acquires vehicle information of one or more vehicles, including a vehicle current location; The vehicle dispatching system described in [1], wherein the vehicle dispatching plan generation unit obtains an optimal combination solution that minimizes the dispatching cost of one or more vehicles from among combinations of arrival orders of one or more vehicles, the boarding and / or disembarking locations of multiple passengers approved for sharing based on the synergistic group information, and the order of arrival at the boarding and / or disembarking locations. [3] The acquisition unit acquires vehicle information of one or more vehicles, including a vehicle current location; The vehicle dispatch system described in [1] or [2], wherein the vehicle dispatch plan generation unit obtains an optimal combination solution for a combination of arrival orders of one or more vehicles, the boarding and / or disembarking locations of multiple passengers, and the order of arrival at the boarding and / or disembarking locations, which satisfies the condition that only passengers approved to share according to the synergistic group information can share, and which minimizes the dispatch cost of one or more vehicles. [4] The acquisition unit acquires vehicle information of one or more vehicles, including the number of passengers in the vehicle and the current location of the vehicle; The dispatch system described in any of [1] to [3], wherein the dispatch plan generation unit generates the dispatch plan based on the boarding locations and / or disembarking locations of the plurality of dispatch reservation information and the current vehicle locations of one or more of the vehicle information. [5] A dispatch system according to any one of [1] to [4], wherein the dispatch plan generation unit obtains a combinatorial optimal solution that satisfies at least one or more constraints selected from the following: a condition that the arrival order is a consecutive number starting from 1; a condition that a passenger has only one arrival order in one or more vehicles; and a condition that the number of passengers in the vehicles does not exceed the vehicle capacity. [6] A dispatch system described in any of [1] to [5], wherein the dispatch plan generation unit obtains a combination optimal solution that minimizes the dispatch cost of one or more vehicles from among combinations of one or more vehicles, a specified boarding location, multiple disembarking locations, and the disembarking order of passengers. [7] A dispatch system described in any of [1] to [6], wherein the dispatch plan generation unit obtains a combination optimal solution that minimizes the dispatch cost of one or more vehicles from among combinations of one or more vehicles, multiple boarding locations, specified disembarking locations, and passenger boarding order. [8] The acquisition unit acquires vehicle reservation information of a plurality of passengers, including desired boarding times or desired disembarking times, a group generation unit that classifies a plurality of passengers into one or a plurality of passenger groups based on at least one of a desired boarding time, a desired disembarking time, a boarding location, and a disembarking location included in the plurality of pieces of vehicle dispatch reservation information; The vehicle allocation system according to any one of [1] to [7], wherein the vehicle allocation plan generating unit generates a vehicle allocation plan for each of the passenger groups so as to minimize the cost of allocating one or more vehicles. [9] The acquisition unit acquires vehicle information of one or more vehicles, including the number of passengers in the vehicle and the current location of the vehicle; The vehicle dispatch system described in [8], wherein the group generation unit assigns one or more vehicles to the passenger group based on multiple pieces of vehicle dispatch reservation information and one or more pieces of vehicle information.

[10] The vehicle dispatch system described in [9], wherein the group generation unit allocates the vehicles so that the sum of the vehicle capacities included in one or more of the vehicle information is greater than or equal to the number of passengers included in the passenger group.

[11] A dispatch system according to any one of [8] to

[10] , wherein the group generation unit classifies multiple passengers who are in a relationship in which they approve of synergy based on the synergistic group information into the passenger group.

[12] A map information storage unit is provided that stores the results of pre-calculating the route distance or route time between two points in association with map information; The vehicle dispatch system described in any of [1] to

[11] , wherein the vehicle dispatch plan generation unit generates the vehicle dispatch plan using the route distance or the route time acquired from the map information storage unit for the vehicle dispatch cost between the acquired multiple boarding locations and / or disembarking locations.

[13] A vehicle dispatching system according to any one of [1] to

[12] , wherein the vehicle dispatching plan generation unit requests a combinatorial optimization engine to process a combinatorial optimization problem in which variables for each element related to the combination of arrival orders are defined, and obtains a combinatorial optimal solution from the combinatorial optimization engine.

[14] A vehicle dispatch system that provides a dispatch plan for vehicles shared by multiple passengers, an acquisition unit that acquires vehicle reservation information of a plurality of passengers, including boarding locations and / or disembarking locations, and vehicle information of one or more vehicles, including vehicle current locations; a dispatch plan generation unit that issues a processing request to a combinatorial optimization engine for a combination model that defines variables including one or more vehicles, multiple boarding locations and / or disembarking locations included in multiple pieces of dispatch reservation information, and the order of arrival at the boarding locations and / or disembarking locations, obtains from the combinatorial optimization engine a combinatorial optimal solution that minimizes the dispatch cost of one or more vehicles, and generates a dispatch plan based on the combinatorial optimal solution.

[0013] The invention of [1] allows the provision of a ride-sharing service that solves various problems associated with ride-sharing by registering a ride-sharing group and generating a ride-sharing plan that includes only passengers who are approved to ride-sharing. According to the invention of [2], by using the boarding and / or disembarking locations of passengers who have been approved for ride-sharing, an optimal vehicle dispatch plan can be generated based on the optimal combination of passengers who have been approved for ride-sharing. The invention of [3] makes it possible to process passengers who have been approved to ride-share and passengers who have not been approved to ride-share, and to generate an optimal vehicle dispatch plan based on the optimal combination of passengers who have been approved to ride-share. The invention according to [4] makes it possible to generate a vehicle dispatch plan that takes into account the current location of the vehicle. The invention related to [5] prevents an inappropriate combination from being adopted as the optimal solution. The invention according to [6] makes it possible to generate a dispatch plan for delivery services. The invention according to [7] makes it possible to generate a vehicle dispatch plan with pick-up service. According to the invention of [8], by targeting passenger groups, the processing load for generating a vehicle dispatch plan can be reduced. The inventions in [9] and

[10] can reduce the processing load by appropriately allocating vehicles to passenger groups and generating a vehicle dispatch plan. According to the invention of

[11] , by classifying passengers based on their shared groups, it is possible to reduce the processing load of generating a ride-sharing plan and generate an optimal ride-sharing plan in which only passengers who have been approved to ride-sharing can ride-sharing. The invention according to

[12] contributes to shortening processing time and reducing processing load by deriving distance and time in advance. The invention according to

[13] makes it possible to execute combinatorial optimization processing in real time. The invention of

[14] makes it possible to execute in real time the process of determining an appropriate route in response to the requests of multiple passengers, such as boarding and disembarking locations, in a new ride-sharing service system. [Effects of the Invention]

[0014] According to the present invention, it is possible to provide a vehicle allocation plan for vehicles in which a plurality of passengers share a ride, and in particular, to provide an efficient vehicle allocation plan for ride-sharing by a group. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a block diagram of a system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram illustrating a hardware configuration of the present embodiment. [Figure 3] FIG. 2 is a data structure diagram of the present embodiment. [Figure 4] FIG. 2 is a diagram illustrating an outline of a vehicle allocation plan according to the present embodiment. [Figure 5] An example of passenger group classification. [Figure 6] 10 shows an example of a display on a screen of a terminal device according to the present embodiment. [Figure 7] 10 is a flowchart of a vehicle dispatch process according to the first embodiment. [Figure 8] 1 shows an example of a data configuration used in the first embodiment. [Figure 9] 1 is an example of a QUBO matrix according to the first embodiment. [Figure 10] 10 is an example of an execution result of the combinatorial optimization process of the first embodiment. [Figure 11] 10 shows an example of a data configuration used in the second embodiment. [Figure 12] FIG. 10 is a diagram illustrating an outline of constraint conditions used in the second embodiment. [Figure 13] 10 is an example of a QUBO matrix in Example 2. [Figure 14] 10 is an example of an execution result of the combinatorial optimization process of the second embodiment. [Figure 15] 13 shows an example of a data configuration used in the third embodiment. [Figure 16] 10 is an example of a QUBO matrix according to the third embodiment. [Figure 17] 10 is an example of a QUBO matrix according to the third embodiment. [Figure 18] 13 shows an example of a result of execution of the combinatorial optimization process of the third embodiment. [Figure 19] 10 is a flowchart of a vehicle dispatch process according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, a vehicle dispatch system and a vehicle dispatch method according to an embodiment of the present invention will be described with reference to the drawings. Note that the embodiment shown below is an example of the present invention, and the present invention is not limited to the embodiment below, and various configurations can be adopted.

[0017] In this embodiment, the configuration, operation, etc. of a vehicle dispatching system and a vehicle dispatching device are described, but a vehicle dispatching method, a computer program, and a program recording medium on which the program is recorded, each having a similar configuration, also achieve the same effects. For example, by using a program recording medium, the program can be installed on a computer. The series of processes according to this embodiment described below are provided as a computer-executable program, and can be provided via a non-transitory computer-readable recording medium such as a CD-ROM or a flexible disk, or even via a communication line.

[0018] The vehicle dispatch system is composed of a computer device. The computer device has an arithmetic unit such as a CPU (Central Processing Unit) and a storage device. The computer device can function as a vehicle dispatch device by executing a vehicle dispatch program stored in the storage device using the arithmetic unit. The vehicle dispatch method is realized by processing the computer device including the vehicle dispatch device.

[0019] In this description, carpooling refers to an operation in which multiple passengers ride together in a vehicle such as a bus or taxi, and the route can be flexibly changed according to the passengers' requests for boarding and disembarking locations, etc. Group carpooling refers to an operation in which multiple passengers who have an approved relationship for such carpooling are grouped together to provide a carpooling service.

[0020] A vehicle dispatch plan indicates the order in which one or more vehicles will travel between multiple passenger pick-up and / or drop-off locations (points). In a vehicle dispatch plan, there are multiple combinations of how to travel to each point. By adopting the combination that results in the shortest route and shortest time from these combinations as the vehicle dispatch plan, an efficient vehicle dispatch service can be realized.

[0021] In this embodiment, the vehicle dispatch plan includes three modes: a drop-off service, a pick-up service, and a mixed service. A drop-off service refers to a vehicle dispatch plan in which a vehicle simultaneously boards multiple passengers from a specified boarding location and transports them to different disembarkation locations. A pick-up service refers to a vehicle dispatch plan in which a vehicle picks up multiple passengers at different boarding locations, boards each of them, and disembarks them simultaneously at a specified disembarkation location. A mixed service refers to a vehicle dispatch plan in which a vehicle simultaneously picks up multiple passengers at different boarding locations, boards each of them, and transports them to different disembarkation locations.

[0022] In this specification, a destination refers to the boarding or disembarking location of passengers picked up or dropped off by a vehicle. A departure point refers to the starting point in a vehicle dispatch plan. For drop-off trips, the departure point can be a predetermined boarding location or the current location of the vehicle. For pick-up trips and mixed trips, the departure point can be the current location of the vehicle.

[0023] In this specification, the arrival order refers to the order in which a vehicle arrives at multiple destinations (boarding and disembarking locations). The boarding order refers to the order in which a vehicle arrives at each of multiple passengers' boarding locations. The disembarking order refers to the order in which a vehicle arrives at each of multiple passengers' disembarking locations.

[0024] A combinatorial optimization problem is a problem of finding the optimal combination from multiple combinations such as those described above. An efficient vehicle dispatch plan can be derived by solving a type of traveling salesman problem. Calculating a combinatorial optimization problem results in a combinatorial explosion, where the number of solution candidates increases rapidly with the size of the problem. In the combinatorial optimization problem of this embodiment, when the number of locations is n, the number of combinations is expressed as (n-1)!. According to this, the number of combinations is 24 when n = 5, 720 when n = 7, and 8.8e+30 when n = 30, making real-time calculations impractical when processing by brute force.

[0025] Combinatorial optimization problems can be formulated and an exact or approximate solution can be derived using a solver, a combinatorial optimization engine. Furthermore, combinatorial optimization problems can be formulated as QUBO equations and expressed as QUBO matrices incorporating actual data. This QUBO matrix can be used to derive an exact or approximate solution using a QUBO solver, a combinatorial optimization engine. QUBO solvers are implemented using quantum annealing quantum computers or classical computers using simulated annealing algorithms. In the future, QUBO solvers may also be implemented using gate-type quantum computers. While QUBO solvers can solve combinatorial optimization problems in a relatively short time, even when the number of combinations is large, the scale of the problem they can handle (the number of combinations) and the time required to derive a solution depend on the implementation method of the QUBO solver. Therefore, it is necessary to select a QUBO solver that can handle the complexity of the problem and derive a solution in a practical amount of time. In this embodiment, an efficient vehicle dispatch plan can be generated using a combinatorial optimization engine that can process combinatorial optimization problems. In this embodiment, a specific implementation example using a QUBO solver will be described as a combinatorial optimization engine, but this is not limiting and any solver including mathematical programming can be used. Furthermore, in this embodiment, the solution derived as a result of combinatorial optimization is referred to as an optimal solution, but its accuracy depends on the implementation and usage of the solver, and it is sufficient if it has practical accuracy as an exact solution or approximate solution. Note that exact solutions include typical solutions that are applied to specific problems and general-purpose solutions that are applied to general-purpose problems.

[0026] Table 1 shows a comparison of each solver based on the evaluation criteria. Table 1 compares the evaluation criteria of processing speed, problem scale, versatility, and solution accuracy for solvers such as quantum annealing, pseudo-quantum annealing, typical solution methods, and general-purpose solution methods. Note that Table 1 is the evaluation of each solver at the time of filing, and will change as technology evolves. The combinatorial optimization engine can adopt an appropriate solver according to the requirements of the desired evaluation criteria.

[0027] [Table 1]

[0028] FIG. 1 shows a block diagram of a vehicle dispatch system 1. The vehicle dispatch system 1 includes a vehicle dispatch device 2, a passenger terminal 3, a vehicle 4, a vehicle terminal 5, and a memory unit DB. The vehicle dispatch device 2, the passenger terminal 3, and the vehicle terminal 5 are each connected to a communication network NW and configured to be able to communicate with each other. The memory unit DB is configured as a database installed inside or outside the vehicle dispatch device 2, and is configured to be able to communicate data with at least the vehicle dispatch device 2. The memory unit DB may be connected to the communication network NW and configured to communicate with the vehicle dispatch device 2. There may be multiple passenger terminals 3, multiple vehicles 4, and multiple vehicle terminals 5.

[0029] The vehicle dispatching device 2 includes, as functional components, a group registration unit 20 that registers a sharing group in which multiple passengers approve sharing, an acquisition unit 21 that acquires various information, a group generation unit 22 that classifies multiple passengers into passenger groups, a vehicle dispatching plan generation unit 23 that generates a vehicle dispatching plan for multiple passengers sharing, and an output unit 24 that outputs the vehicle dispatching plan to an external device. Note that the group generation unit 22 does not necessarily have to be included in the vehicle dispatching device 2 according to the first embodiment.

[0030] The passenger terminal 3 is a terminal device operated by a passenger who receives the allocation of a vehicle 4. The passenger terminal 3 accepts input of vehicle allocation reservation information from each passenger and transmits a vehicle allocation request to the vehicle allocation device 2, thereby enabling the vehicle allocation system 1 to provide a vehicle allocation service.

[0031] Vehicle 4 is a vehicle in which multiple passengers share a ride, such as a taxi or bus that is dispatched to passengers. These vehicles 4 are equipped with a vehicle terminal 5, such as a mobile terminal device or car navigation device owned by the driver, either in a fixed or portable form. Note that vehicle 4 may also be an autonomous vehicle, and may be one with or without a driver.

[0032] The vehicle terminal 5 transmits a request including vehicle information to the vehicle dispatch device 2. The vehicle terminal 5 receives a vehicle dispatch instruction from the vehicle dispatch device 2. The vehicle terminal 5 approves or rejects the vehicle dispatch instruction. If the vehicle terminal 5 approves the vehicle dispatch instruction, it transports passengers according to the vehicle dispatch plan included in the vehicle dispatch instruction. By optimizing the vehicle dispatch plan, vehicles can be operated efficiently to provide a vehicle dispatch service.

[0033] The storage unit DB is configured as a database including a vehicle allocation information storage unit DB1 that stores vehicle allocation information, and a map information storage unit DB2 that stores map information.

[0034] The dispatch device 2 is connected to the QUBO solver 6 so that data communication is possible. The dispatch device 2 acquires various information related to the combinatorial optimization problem using the acquisition unit 21, and generates a QUBO matrix related to the combinatorial optimization problem based on that information. The QUBO solver 6 receives a processing command for the QUBO matrix related to the combinatorial optimization problem from the dispatch device 2, and returns the solution of the QUBO matrix to the dispatch device 2 as the execution result. The dispatch device 2 can generate an efficient dispatch plan using the obtained combinatorial optimal solution. The QUBO solver 6 is configured as a quantum computer or a classical computer that implements a search algorithm such as simulated annealing in the application layer.

[0035] FIG. 2(a) shows a hardware configuration diagram of the vehicle dispatching device 2. The vehicle dispatching device 2 includes a control device 201, a storage device 202, and a communication device 203 as its hardware configuration, and each component device is connected via a bus interface. In this embodiment, the vehicle dispatching device 2 may use a computer device such as a server device or a personal computer. Note that the vehicle dispatching device 2 may be configured with multiple computer devices, and is not limited to the configuration shown in FIG. 2, as long as it can realize the above-described functional components (20-24) as a whole.

[0036] The control device 201 is configured with one or more processors such as a CPU, and controls the overall processing of the vehicle dispatch device 2 by executing a vehicle dispatch program, an OS (Operating System), and other applications. The storage device 202 is a hard disk drive (HDD), solid state drive (SSD), flash memory, RAM (Random Access Memory), etc., and stores the vehicle dispatch program and various data. The communication device 203 is a communication interface for wired communication, wireless communication, etc., and controls data communication with external devices. The communication device 203 is also capable of performing data communication with external devices by controlling communication with the communication network NW.

[0037] FIG. 2(b) shows a modified example of the hardware configuration diagram of the dispatch device 2. According to FIG. 2(b), the dispatch device 2 further includes a QUBO solver 6. The QUBO solver 6 is connected to a control device 201, a storage device 202, and a communication device 203. In FIG. 2(b), at least the control device 201, the storage device 202, and the communication device 203 are configured as classical computers. If the QUBO solver 6 is implemented using a quantum computer, it operates according to control instructions from the classical computer. If the QUBO solver 6 is implemented using simulated annealing, it is configured as a classical computer.

[0038] FIG. 2(c) shows a hardware configuration diagram of a terminal device 9 such as the passenger terminal 3 and the vehicle terminal 5. The terminal device 9 includes, as its hardware configuration, a control device 901, a storage device 902, a communication device 903, an input device 904, and an output device 905. The terminal device 9 may also include a GPS communication device. In this embodiment, the terminal device 9 may be a smartphone, a personal computer, a tablet terminal, or the like. The vehicle terminal 5 may also be a car navigation device.

[0039] The control device 901 is composed of one or more processors such as a CPU, and controls the overall processing of the terminal device 9 by executing terminal programs, an OS, other applications, etc. The storage device 902 is an HDD, SSD, flash memory, RAM, etc., and stores a browser application and various data. The communication device 903 controls communication with the communication network NW and realizes data communication with at least the vehicle dispatch device 2. The input device 904 is an input interface that accepts input operations by the user, and is composed of a microphone, touch panel, mouse, keyboard, etc. The output device 905 is composed of a display that displays and outputs, etc. The GPS communication device can acquire the position coordinates of the terminal device 9 via GPS communication.

[0040] FIG. 3 shows an example of the data structure of various information. The dispatch information includes dispatch reservation information and vehicle information. FIG. 3 illustrates one example of a farewell service that transports passengers from the same boarding location Ps to their respective disembarking locations. In a farewell service, all passengers board from the same boarding location Ps, so the boarding order is 1 (simultaneous boarding). The current vehicle location of each vehicle can also be the boarding location Ps. It is also possible to transport passengers from different boarding locations, and the configuration is not limited to this.

[0041] The vehicle dispatch reservation information is input as a vehicle dispatch reservation by a passenger via the passenger terminal 3 and stored in the vehicle dispatch information storage unit DB1. As shown in FIG. 3(a), the vehicle dispatch reservation information includes a vehicle dispatch reservation ID, a passenger ID, a boarding location, a disembarking location, the number of passengers, a desired boarding time, and a desired disembarking time. The boarding location and disembarking location are location coordinates expressed in latitude and longitude. The boarding location and disembarking location can be determined by inputting a landmark or the like with which an address or location coordinate is previously associated, and the corresponding location coordinates can be obtained using so-called geocoding or address matching. The vehicle dispatch reservation information can identify the passenger who made the vehicle dispatch reservation by the passenger ID, and passenger information corresponding to the passenger ID can be referenced.

[0042] The vehicle information is transmitted from the vehicle terminal 5 and stored in the vehicle dispatch information storage unit DB1. As shown in FIG. 3(b), the vehicle information includes a vehicle ID, a current vehicle location, the number of passengers in the vehicle, and the time the vehicle is available to depart. The current vehicle location is a position coordinate acquired by GPS communication or the like. The vehicle information is transmitted from the vehicle terminal 5 at predetermined intervals or in response to the start of a vehicle dispatch plan.

[0043] Passenger information is stored in the dispatch information storage unit DB1 upon a passenger's advance registration request. As shown in FIG. 3(c), the passenger information includes a passenger ID, name, gender, age, and identification information of the shared group (shared group ID) to which the passenger belongs. A shared group is a group formed by multiple passengers who mutually approve sharing. Shared groups include, for example, organizations such as companies, schools, government agencies, and various institutions, as well as groups formed by acquaintances. Furthermore, when a ridesharing agreement is approved between one shared group and another, passengers belonging to different approved shared groups can also share a ride. For example, passengers from the same organization or related organizations are more likely to share a ridesharing agreement. In one embodiment, the present invention provides a ridesharing service specifically tailored to passengers approved for ridesharing by a shared group that is expected to greatly benefit from the ridesharing service.

[0044] In this embodiment, the vehicle dispatch plan includes a boarding order indicating the order in which one or more vehicles will pick up multiple passengers at their respective boarding locations and board each passenger. In this embodiment, the vehicle dispatch plan includes a disembarking order indicating the order in which one or more vehicles will deliver multiple passengers to their respective disembarking locations and disembark each passenger. The vehicle dispatch plan may include at least one of a boarding order and a disembarking order, or may include both. In a mixed service, the vehicle dispatch plan includes both a boarding order and a disembarking order, in a pick-up service, the vehicle dispatch plan includes at least a boarding order, and in a drop-off service, the vehicle dispatch plan includes at least a disembarking order.

[0045] FIG. 3(d) shows an example of the data structure of a vehicle dispatch plan. The vehicle dispatch plan includes a vehicle dispatch plan ID, a vehicle dispatch reservation ID, a vehicle ID, a boarding order, and a disembarking order. The vehicle dispatch plan may also include the travel distance and travel time for the entire route or for individual routes. An individual route refers to a route between two points, such as two boarding locations, two disembarking locations, or a boarding location and a disembarking location.

[0046] FIG. 3(e) shows an example of the data structure of synergistic group information that defines the relationship between multiple passengers who approve ride-sharing. The synergistic group information includes a synergistic group ID, a related synergistic group ID, and an administrator ID. The administrator ID is identification information for the administrator of the synergistic group. The administrator refers to a person in an organization who approves passengers who use the synergistic service. The administrator may also be selected from among the passengers. Note that one passenger may belong to multiple synergistic groups.

[0047] The related synergy group ID is the identification information of other synergy groups that approve ride-sharing. In the example of Figure 3(e), passengers in synergy group G1 are approved to ride-sharing with passengers belonging to synergy group G3. Multiple related synergy group IDs may be set. If no related synergy group ID is set, ride-sharing is approved only between passengers belonging to the synergy group. In other words, ride-sharing is approved between passengers belonging to the same synergy group or related synergy groups.

[0048] Furthermore, the sharing group information can set one or more predetermined boarding locations and / or disembarking locations. The predetermined boarding location is set as the boarding location of the ride reservations made by passengers of the sharing group. Specifically, a ride dispatch plan is provided for a transfer from the predetermined boarding location, such as a rotary designated by the administrator, to the disembarking location (home, etc.) of each passenger included in the ride dispatch reservation. The predetermined disembarking location is set as the disembarking location of the ride dispatch reservation made by passengers of the sharing group. Specifically, a ride dispatch plan is provided for a transfer from the boarding location of each passenger included in multiple ride dispatch reservations to the predetermined disembarking location, such as a rotary designated by the administrator. By setting the predetermined boarding location and / or disembarking location, a ride dispatch plan can be generated according to advance plans, etc., thereby reducing the calculation load.

[0049] An overview of the vehicle dispatch plan will be described with reference to FIG. 4. The vehicle dispatch plan derives the order in which one or more vehicles v will arrive at the respective drop-off locations of multiple passengers from a certain departure point as a drop-off service. In this embodiment, "location" includes the current vehicle location of vehicle v, the passenger boarding location and / or drop-off location, etc. FIG. 4 describes an example of a drop-off service in which the current vehicle location is a boarding location Ps, and all passengers depart from the same boarding location Ps and head to different drop-off locations Pa to Pc. Note that this example is provided for the sake of simplicity, and the present invention can also be applied to cases where the current vehicle location is different from the initial boarding location Ps, cases where passengers depart from different boarding locations, and even pick-up services and mixed services. This specification deals with the simplified example of FIG. 4, but this embodiment is not limited to this example.

[0050] FIG. 4(a) illustrates an example of vehicle allocation for three passengers A to C. The drop-off locations for passengers A to C are indicated as points Pa, Pb, and Pc. The departure location is indicated as point Ps. FIG. 4(a) also shows the cost between each location as a numerical value. Passengers A to C each belong to a shared group. For example, passengers A and C belong to shared group G1, and passenger B belongs to shared group G2. If ride-sharing is not approved between shared groups G1 and G2, passengers A or C cannot ride with passenger B. In this case, a vehicle allocation plan must be created in which a separate vehicle is allocated for passenger B, or one vehicle first transports passengers A and C to the drop-off locations and then returns to the departure location Ps to transport passenger B.

[0051] Figure 4(b) shows a vehicle allocation plan for four passengers A to D. The drop-off locations for passengers A to D are indicated as points Pa, Pb, Pc, and Pd, and the departure location is indicated as point Ps. Figure 4(b) also shows the cost between each point as a numerical value. Also, assume that passengers A and C belong to synergistic group G1, passenger B belongs to synergistic group G2, and passenger D belongs to synergistic group G3. Here, synergistic group G2 is not approved for ride-sharing with synergistic groups G1 and G3, but ride-sharing is approved between synergistic groups G1 and G3. In this case, the vehicle allocation plan can be generated so that passengers A, C, and D ride in one vehicle. The vehicle allocation plan is also generated so that passenger B does not ride-sharing with other passengers.

[0052] FIG. 4(c) shows a list of inter-point costs corresponding to FIG. 4(a). FIG. 4(d) shows a list of inter-point costs corresponding to FIG. 4(b). For example, the distance from point Ps to point Pa is 20, and the distance from point Pa to point Pb is 16. A vehicle allocation plan is generated to minimize the vehicle allocation cost of allocating one or more vehicles to as many points as possible while satisfying the constraints described below. In this embodiment, the vehicle allocation cost is the vehicle's travel distance, and a vehicle allocation plan is generated so that the total travel distance is minimized. Furthermore, the inter-point cost is expressed as the distance between points.

[0053] <1.1. Combination model> In this embodiment, a combinatorial model is used to obtain a combinatorial optimal solution for the arrival order (boarding order or disembarking order) of multiple passengers at their respective destinations (including boarding and disembarking points). The combinatorial model is a model for obtaining a solution to a combinatorial optimization problem. In this embodiment, the combinatorial optimization problem is a type of traveling salesman problem. Note that the type of combinatorial model is not limited as long as it is a model for solving a combinatorial optimization problem such as the above-mentioned arrival order.

[0054] For simplicity's sake, the following details are given using as an example a combination model for determining the order of disembarking from a specific boarding location to disembarking locations included in multiple vehicle reservations. The combination model according to this embodiment is a model for determining the route that minimizes the vehicle dispatch cost when one or multiple vehicles 4 make one trip to each of multiple passengers' boarding locations and / or disembarking locations.

[0055] A combinatorial model is a model that derives the optimal combination from among combinations of variables for each element. In this embodiment, the QUBO formula is used as the combinatorial model. A QUBO matrix is ​​obtained by applying data from a real problem to the variables of the QUBO formula and processing the data. The QUBO matrix is ​​a matrix representation of a QUBO problem (a combinatorial optimization problem using unconstrained binary variable optimization of a quadratic form), and the energy of the solution is calculated based on the elements of this matrix. An objective function is set in the QUBO formula, and the combination that minimizes the energy of the function can be found as the solution to the combinatorial optimization problem. In this embodiment, energy is defined as the vehicle dispatch cost, and a combinatorial optimal solution that minimizes the vehicle dispatch cost is derived.

[0056] In this embodiment, the variable x[v,t,i] of the objective function is defined as vehicle v, arrival order t, and passenger i, and the combination model derives a combination of elements that minimizes the dispatch cost from among combinations of these variables. Passenger i indicates the passenger's boarding and / or disembarking location.

[0057] The objective function has one or more objective terms. The objective terms are set with the objective of minimizing the vehicle dispatch cost. The vehicle dispatch cost can be selected from at least one of the following: travel distance, travel time, passenger fare, vehicle delivery time, and number of vehicles. The service provider or user can arbitrarily select which vehicle dispatch cost to minimize. The objective terms are set with corresponding coefficients and variables depending on the vehicle dispatch cost to be minimized.

[0058] As specific examples, the objective term may be minimizing the sum or average of the distance traveled by one or more vehicles. Alternatively, the objective term may be minimizing the sum or average of the travel time of multiple passengers. Alternatively, the objective term may be minimizing the number of vehicles 4 to be dispatched. Alternatively, the objective term may be minimizing the sum or average of the fares of multiple passengers. The objective function may employ at least one or more objective terms selected from these.

[0059] The constraints of the objective function are set for the purpose of preventing candidates for combinatorial optimal solutions that cannot be met in reality or are inappropriate for adoption from being adopted as the combinatorial optimal solution. The objective function can have one or more constraint terms related to the constraints. Constraints will be described in detail later.

[0060] As shown in equation (1), the objective function H(x) is set with terms H1(x), H2(x), and H3(x) indicating one or more objective terms or constraint terms. At least one objective term is set. There is no limit to the number of constraint terms that can be set, and they may not even be set. The objective function H(x) indicates the sum of the energies of the objective terms and constraint terms. In this embodiment, the solution that minimizes the sum of the energies of the objective functions is the combinatorial optimum solution that minimizes the vehicle dispatch cost.

[0061]

number

[0062] Input data for the combination model includes passenger count information for each boarding location, vehicle capacity information, first location information, and second location information. The location information is information indicating the point-to-point cost between each location. In this embodiment, the first location information indicates the point-to-point cost between the departure location and each passenger's boarding location and / or disembarking location, and the second location information indicates the point-to-point cost between each passenger's boarding location and the boarding location, disembarking location and the disembarking location, or between each passenger's boarding location and the disembarking location.

[0063] In this embodiment, the input data is represented by the following variables in the objective term shown in equation (2): first point information: disS2P, second point information: disP2P, vehicle capacity: capaNums v , Number of reservations: iNum, vehicle v, arrival order t, destination i, j. Number of vehicles: vNum. Note that the number of vehicles vNum is the vehicle capacity capaNums v This objective term is an example of the objective term H1(x) in the objective function of equation (1), and for simplicity, the number of passengers information is omitted assuming that all passengers are one person.

[0064]

number

[0065] The constraints of the combination model will be explained below.

[0066] The combination model according to this embodiment has multiple constraint conditions. The constraint conditions include at least one selected from the following: a condition that the arrival order is numbered consecutively starting from 1; a condition that a passenger has only one arrival order in one or more vehicles; and a condition that the number of passengers in a vehicle does not exceed its capacity. Further constraint conditions may be set, such as a condition that the arrival order at the disembarking location can be set only after the arrival order at the boarding location of a passenger; or a condition that only passengers who approve of the ride-sharing can ride in a single vehicle. The vehicle allocation plan generation unit 23 can obtain an appropriate combination optimal solution by narrowing down the candidates for the combination optimal solution based on the constraint conditions.

[0067] The constraint term outputs the minimum energy (for example, 0) when the constraint condition is satisfied. The constraint term outputs an energy greater than or equal to a predetermined value when the constraint condition is not satisfied. The constraint term is weighted so that the energy output when the constraint condition is not satisfied is greater than or equal to the energy output by the objective term. Therefore, when the constraint condition is not satisfied, the objective function derives a high energy regardless of the energy output by the objective term, and therefore, it is possible to suppress the adoption of the combination as the optimal combinatorial solution.

[0068] The vehicle dispatch plan generation unit 23 generates a vehicle dispatch plan by obtaining a combinatorial optimal solution using the combinatorial model. The vehicle dispatch plan generation unit 23 generates input data to be input to the combinatorial model based on the information acquired by the acquisition unit 21. The vehicle dispatch plan generation unit 23 inputs the input data to the combinatorial model (QUBO formula) and generates output data (QUBO matrix). The vehicle dispatch plan generation unit 23 issues a command to process the QUBO matrix to the combinatorial optimization engine (QUBO solver 6) to execute optimization processing. The vehicle dispatch plan generation unit 23 acquires a return value, which is the combinatorial optimal solution as the execution result, from the combinatorial optimization engine. The return value includes a variable x[v, t, i], and the vehicle dispatch plan generation unit 23 can generate an optimized vehicle dispatch plan indicating which vehicle v should be dispatched to which passenger i in what arrival order t.

[0069] The combination model is the same as in the first and second embodiments described below. Note that a combination model for obtaining a combinational optimal solution for the disembarking order of multiple passengers at their respective disembarking locations, and a combination model for obtaining a combinational optimal solution for the boarding order from the boarding location may be used separately. The vehicle allocation plan generation unit 23 can generate a vehicle allocation plan by obtaining a combinational optimal solution from a combinatorial optimization engine using the output data of the combination model.

[0070] <1.2. Delivery> In a drop-off service, the vehicle dispatch plan generation unit 23 obtains a combinatorial optimal solution that minimizes the dispatch cost of one or more vehicles from among combinations of one or more vehicles, a predetermined boarding location, multiple disembarking locations, and the disembarking order of passengers. In a drop-off service, one or more vehicles start from a common boarding location, and board passengers at the same time at the departure location. The vehicle dispatch plan generation unit 23 obtains a combinatorial optimal solution for the disembarking order of each passenger when traveling from the departure location via each passenger's disembarking location. The vehicle dispatch plan generation unit 23 generates a vehicle dispatch plan including the disembarking order of each passenger using the obtained combinatorial optimal solution for the disembarking order.

[0071] <1.3.Pick-up service> In a pick-up service, the vehicle dispatch plan generation unit 23 obtains a combinatorial optimal solution that minimizes the dispatch cost of one or more vehicles from among combinations of boarding orders based on one or more vehicle current locations, multiple boarding locations, predetermined disembarking locations, and passenger boarding order. In a pick-up service, one or more vehicles have a common disembarking location as their final destination, and the passengers are picked up at their respective boarding locations and then disembarked simultaneously at the final destination. The vehicle dispatch plan generation unit 23 obtains a combinatorial optimal solution for the boarding order of each passenger when traveling from the current vehicle location as a departure point to the final destination via each passenger's boarding location. The vehicle dispatch plan generation unit 23 generates a vehicle dispatch plan including the boarding order of each passenger using the obtained combinatorial optimal solution for the boarding order.

[0072] <1.4. Mixed shipments> In a mixed service, the vehicle allocation plan generation unit 23 obtains a combinatorial optimal solution that minimizes the dispatch cost of one or more vehicles from among combinations of arrival orders based on one or more current vehicle locations, multiple boarding and disembarking locations, and the arrival order at the boarding and disembarking locations. In a mixed service, one or more vehicles board passengers in order at each passenger's boarding location and disembark passengers in order at each passenger's disembarking location. The vehicle allocation plan generation unit 23 obtains a combinatorial optimal solution for the arrival order at the boarding and disembarking locations when vehicles start from the current vehicle location and pass through each passenger's boarding and disembarking locations. The vehicle allocation plan generation unit 23 generates a vehicle allocation plan including the arrival order at each passenger's boarding and disembarking location using the obtained combinatorial optimal solution for the arrival order.

[0073] <1.5. Group Generation> The group generation unit 22 classifies multiple passengers into one or more passenger groups based on the desired boarding time, desired disembarking time, and location coordinates of the boarding and / or disembarking locations included in multiple pieces of ride-hailing reservation information. Figure 5 shows different examples of passenger group classification methods. The points in each graph in Figure 5 are passengers plotted according to the desired boarding time and location coordinates of the ride-hailing reservation information.

[0074] In the classification method of Figure 5(a), multiple passengers are classified into passenger groups G1, G2, and G3 based on the desired boarding times and disembarking times included in the vehicle dispatch reservation information. According to the classification method of Figure 5(a), by grouping passengers with similar desired boarding times for drop-off trips and similar desired disembarking times for pick-up trips, it is possible to board or disembark passengers together at times that suit the passengers' wishes, and the cost of dispatching one or more vehicles 4 can be relatively low. Here, the location coordinates refer to the coordinates of the boarding and / or disembarking locations included in the vehicle dispatch reservation information.

[0075] In the classification method of Figure 5(b), multiple passengers are classified into passenger groups G4, G5, and G6 based on the boarding and / or disembarking locations included in the vehicle dispatch reservation information. The graph in Figure 5(b) has two axes, with the horizontal axis representing location coordinate X (e.g., longitude) and the vertical axis representing location coordinate Y (e.g., latitude). By grouping passengers whose boarding or disembarking locations are close in distance, passengers can be boarded and disembarked in a concentrated manner, and with the efficiency of carpooling, the cost of dispatching one or more vehicles 4 can be relatively low.

[0076] In the classification method of FIG. 5(c), multiple passengers are classified into passenger groups G7, G8, and G9 based on the desired boarding time or desired disembarking time and the boarding and / or disembarking locations included in the vehicle dispatch reservation information. The graph in FIG. 5(c) has three axes: the X axis represents a location coordinate X (e.g., longitude), the Y axis represents a location coordinate Y (e.g., latitude), and the Z axis represents time t (desired boarding time or desired disembarking time). By grouping passengers with similar desired boarding times and boarding locations close in distance, passengers can be concentrated on boarding, which improves the efficiency of carpooling and relatively reduces the cost of dispatching one or more vehicles 4. Furthermore, by grouping passengers with similar disembarking locations close in distance and desired disembarking times, passengers can be concentrated on disembarking, which improves the efficiency of carpooling and relatively reduces the cost of dispatching one or more vehicles 4.

[0077] The group generation unit 22 is arbitrarily set by the vehicle dispatching service provider or the like as to whether to adopt a classification method based on desired boarding time and / or location coordinates (including boarding and disembarking locations).

[0078] In one embodiment, the group generation unit 22 first classifies multiple passengers into passenger groups based on location coordinates included in the vehicle dispatch reservation information. Next, the group generation unit 22 further classifies the previously classified passenger groups into smaller passenger groups based on the desired boarding times included in the vehicle dispatch reservation information. In this way, by further grouping passengers grouped by drop-off or boarding locations based on the desired boarding times, passenger groups can be generated with high accuracy. Note that a procedure may also be adopted in which passengers first grouped by the desired boarding times are further grouped based on drop-off or boarding locations.

[0079] In particular, when multiple passengers belong to the same synergistic group, it is assumed that the boarding location is the same place, such as a company, so classifying passenger groups by their desired boarding time and disembarking location can be an effective classification.

[0080] In this embodiment, the group generation unit 22 classifies a plurality of passengers into passenger groups by cluster analysis. In this embodiment, a known cluster analysis algorithm can be adopted as the algorithm used to classify passenger groups. Examples of cluster analysis algorithms include the k-means method and DBSCAN.

[0081] The group generation unit 22 allocates one or more vehicles 4 to a passenger group based on multiple pieces of vehicle reservation information and one or more pieces of vehicle information. The group generation unit 22 allocates to a passenger group vehicles 4 whose current vehicle location included in the vehicle information is close to the boarding location included in the vehicle reservation information. Furthermore, the group generation unit 22 allocates one or more vehicles 4 so that the sum of the vehicle capacities included in one or more pieces of vehicle information is equal to or greater than the number of passengers included in the passenger group. For example, if the passenger group consists of six people, two or more three-seater vehicles 4 are allocated.

[0082] The group generation unit 22 may classify multiple vehicles into one or multiple vehicle groups based on the available vehicle departure times and / or location coordinates (current vehicle locations) included in the multiple vehicle information. The vehicle group classification method can be the same as the passenger group classification method. The group generation unit 22 assigns vehicle groups to passenger groups based on the desired boarding times, available vehicle departure times, and location coordinates of passengers and vehicles. Specifically, the group generation unit 22 refers to the desired boarding times of the passenger groups and the available vehicle departure times of the vehicle groups, and assigns vehicle groups to passenger groups that are close in time. Furthermore, the group generation unit 22 refers to the location coordinates of the boarding locations of the passenger groups and the location coordinates of the vehicle groups, and assigns vehicle groups to passenger groups that are close in distance. This makes it possible to achieve efficient vehicle allocation that allows passengers to board vehicles in a concentrated manner.

[0083] The group generation unit 22 calculates the vehicle capacity of each allocated vehicle 4 and the sum of the vehicle capacity of all the allocated vehicles 4, and stores the calculated vehicle capacity information in association with the vehicle allocation plan.

[0084] The group generation unit 22 calculates the number of passengers at each boarding location and stores the information on the number of passengers by boarding location in association with the vehicle dispatch plan. The information on the number of passengers is calculated based on the number of passengers included in the vehicle dispatch reservation information. Alternatively, the information on the number of passengers may be calculated as the sum of the number of passengers in different vehicle dispatch reservation information for the same boarding location.

[0085] The group generation unit 22 classifies multiple passengers approved by the synergistic group information included in the passenger information into the same passenger group. The group generation unit 22 may also be controlled to generate passenger groups that include only passengers in the same synergistic group. For example, airport employees belonging to the same airline use a ride-hailing service when returning home late at night. In this case, since the airport employees are from the same boarding point or a relatively nearby boarding point (such as a different terminal), a ride-hailing service with short waiting times can be provided by efficiently dispatching a limited number of vehicles 4. Furthermore, the airline can reduce fees when paying for the ride-hailing service for airport employees.

[0086] <1.6. Vehicle allocation plan generation unit> The vehicle allocation plan generation unit 23 generates a vehicle allocation plan based on the vehicle allocation reservation information of passengers. When passengers are classified into passenger groups by the group generation unit 22, the vehicle allocation plan generation unit 23 can generate a vehicle allocation plan based on the vehicle allocation reservation information of passengers classified into the passenger groups.

[0087] The vehicle allocation plan generating unit 23 is configured to calculate the order of arrival at each destination, including passenger boarding and disembarking locations, for a mixed service. Note that the vehicle allocation plan generating unit 23 can also be configured to calculate the boarding order of each passenger when traveling via each of the passengers' boarding locations and then to a predetermined arrival location, for a pick-up service. Furthermore, the vehicle allocation plan generating unit 23 can also be configured to calculate the disembarking order of each passenger when traveling from a predetermined departure location to each of the passengers' disembarking locations, for a drop-off service.

[0088] The vehicle dispatch plan generation unit 23 can generate a vehicle dispatch plan by referring to the number of passengers included in the vehicle dispatch reservation information and the vehicle capacity included in the vehicle information. The number of passengers indicates that multiple passengers will board from one boarding location, and the vehicle capacity limits the number of passengers boarding a vehicle at the same time so as not to exceed this capacity. These can be calculated by including them in the objective terms and constraint terms.

[0089] <1.7.Map Information> The map information storage unit DB2 stores map information. The map information includes road data and location coordinates, and is used to confirm a vehicle's driving route and destination. In this embodiment, the map information storage unit DB2 stores the results of pre-calculating the cost between two points in association with the map information. The route distance and route time do not indicate the straight-line distance between two points, but rather the distance and time, respectively, when traveling along a realistic route following the road data.

[0090] The vehicle allocation plan generation unit 23 can generate location information for the position coordinates of two locations included in the acquired vehicle allocation reservation information and vehicle information by referring to the route distance or route time associated with the map information. The vehicle allocation plan generation unit 23 generates a vehicle allocation plan using the route distance or route time acquired from the map information storage unit DB2 for the vehicle allocation cost between multiple boarding locations and disembarking locations acquired from the map information storage unit DB2.

[0091] The map information may be dynamically associated with road congestion status in cooperation with a road information system. The road congestion status refers to the congestion status associated with road data due to traffic jams, disasters, etc. By reflecting the road congestion status in the road data of the map information, the travel time when the road is used as a route varies. For example, since the route time of a route on a road where traffic jams occur is set to be long, vehicle dispatch costs can be minimized by acquiring the route time and generating a vehicle dispatch plan that takes the travel time into consideration.

[0092] <1.8. Output section> The output unit 24 provides the dispatch plan generated by the dispatch plan generation unit 23 to the passenger terminal 3 or the vehicle terminal 5. The dispatch plan includes at least one of the boarding order and the disembarking order derived as the combinatorial optimum solution.

[0093] The output unit 24 can also derive and provide a travel route that reflects the boarding order and / or disembarking order in map information. The travel route is information that indicates which roads on the map to travel along. The output unit 24 can also derive and provide the arrival times at each passenger's boarding and disembarking locations. Some of the functions of the output unit 24 may be configured to be executed by the passenger terminal 3 or the vehicle terminal 5.

[0094] FIG. 6 shows an example of a screen display provided by the output unit 24. Note that FIG. 6 is an example of a screen display on the vehicle terminal 5. FIG. 6(a) shows an example of a travel route screen W10 display in which the arrival order at the destination (boarding order or disembarking order) is reflected on a map. FIG. 6(a) illustrates the transportation of passengers A to C by vehicle C1. The current vehicle location of vehicle C1 and the boarding and disembarking locations of passengers A to C are displayed on the map by pins, respectively. Vehicle C1 is indicated by vehicle pin O1. The boarding locations of passengers A to C are indicated by boarding location pins S1 to S3, and the disembarking locations are indicated by disembarking location pins E1 to E3. The travel route of vehicle C1 to each of passengers A to C's boarding and disembarking locations is displayed on the map as travel route display R1.

[0095] FIG. 6(b) shows an example of the display of the vehicle allocation plan screen W20, which is displayed as a pop-up by clicking the menu button on the driving route screen W10. The vehicle allocation plan screen W20 includes a vehicle information area W21, a vehicle allocation reservation information area W22, and a vehicle allocation plan area W23. The vehicle information area W21 displays vehicle information including the current vehicle location and vehicle capacity of one or more vehicles to be allocated, and detailed information about a specific vehicle designated from the vehicle information area W21 can be displayed in the vehicle allocation reservation information area W22 and the vehicle allocation plan area W23. The vehicle allocation reservation information area W22 displays vehicle allocation reservation information including the boarding locations, disembarking locations, and number of passengers for multiple passengers A to C.

[0096] The vehicle dispatch plan area W23 displays a vehicle dispatch plan including the boarding order and disembarking order. In FIG. 6(b), the vehicle dispatch plan area W23 displays the boarding order of passengers A to C and the disembarking order of passengers A to C in a chart. The vehicle dispatch plan area W23 also displays the travel distance and travel time for the vehicle dispatch plan. Although FIG. 6(b) shows an example in which the travel distance and travel time for all travel routes are displayed, a configuration in which the route distance and route time are displayed for each passenger's boarding and disembarking location may also be used.

[0097] The vehicle terminal 5 acquires the vehicle dispatch plan from the vehicle dispatch device 2, generates a display of the vehicle dispatch plan screen W20 based on the vehicle dispatch plan, and displays it on a display unit such as a display. The vehicle terminal 5 generates a display of the driving route screen W10 based on the vehicle information, vehicle dispatch reservation information, and the vehicle dispatch plan, and displays it on a display unit. Note that the vehicle dispatch device 2 may generate the display of the driving route screen W10 and the vehicle dispatch plan screen W20.

[0098] The passenger terminal 3 acquires from the dispatch device 2 a dispatch plan related to at least the passenger, generates a dispatch plan screen display, and displays it on a display unit such as a display. The passenger terminal 3 generates a driving route screen display related to at least the passenger based on the vehicle information, dispatch reservation information, and dispatch plan, and displays it on a display unit. For example, the dispatch plan screen for passenger A displays the arrival time, driving distance, driving time, etc. at passenger A's boarding and disembarking locations. Furthermore, passenger A's driving route screen displays a driving route display R1 from boarding location pin S1 to disembarking location pin E1, which is passenger A's driving route. Note that the dispatch device 2 may generate the driving route screen and dispatch plan screen display for each passenger.

[0099] <2.1. First embodiment> FIG. 7 shows a flowchart relating to the vehicle allocation process. The group registration unit 20 accepts the registration of a synergistic group (S101). First, the group registration unit 20 receives an instruction to register a synergistic group from the manager's terminal device and registers synergistic group information. The group registration unit 20 receives a request to join the synergistic group from the passenger terminal 3 and registers the passenger information in association with the synergistic group information. The participation request may be approved by an approval operation from the manager's terminal device, and the group registration unit 20 may be configured to execute a process of associating the passenger information with the synergistic group information if approved.

[0100] The acquisition unit 21 acquires various information (S102). The acquisition unit 21 acquires vehicle reservation information for a plurality of passengers from a plurality of passenger terminals 3. The acquisition unit 21 also acquires vehicle information for a plurality of vehicles from one or a plurality of vehicle terminals 5. The vehicle terminal 5 can transmit the vehicle information together with an instruction to permit acceptance of the vehicle reservation.

[0101] The vehicle allocation plan generation unit 23 generates a vehicle allocation plan based on each of the boarding locations and disembarking locations included in the plurality of vehicle allocation reservation information so as to minimize the vehicle allocation cost of one or more vehicles (S103). Furthermore, the vehicle allocation plan generation unit 23 generates a vehicle allocation plan based on each of the boarding locations and disembarking locations included in the plurality of vehicle allocation reservation information so as to allow only passengers approved to ride-sharing according to the synergistic group information to ride-sharing. Furthermore, the vehicle allocation plan generation unit 23 preferably generates a vehicle allocation plan so as to minimize the vehicle allocation cost of one or more vehicles and allow only passengers approved to ride-sharing according to the synergistic group information to ride-sharing. The vehicle allocation plan generation unit 23 can generate a vehicle allocation plan including a disembarking order based on the disembarking locations of the plurality of vehicle allocation reservation information and the current vehicle locations of one or more vehicle information. Furthermore, the vehicle allocation plan generation unit 23 can generate a vehicle allocation plan including a boarding order based on the boarding locations of the plurality of vehicle allocation reservation information and the current vehicle locations of one or more vehicle information.

[0102] The vehicle dispatch cost is any cost that is the target of efficiency improvement in the vehicle dispatch service. The vehicle dispatch cost is, for example, a driving distance, and the vehicle dispatch plan generation unit 23 derives a combinatorial optimal solution for determining in what order the vehicles should travel to multiple destinations in order to minimize the driving distance of one or more vehicles 4. An example in which the vehicle dispatch cost is a driving distance will be described below.

[0103] In one aspect, the vehicle dispatch plan generation unit 23 can generate a vehicle dispatch plan based on a predetermined boarding location in the shared group information and a drop-off location included in a plurality of vehicle dispatch reservation information. Also, the vehicle dispatch plan generation unit 23 can generate a vehicle dispatch plan based on a predetermined drop-off location in the shared group information and a boarding location included in a plurality of vehicle dispatch reservation information.

[0104] The output unit 24 provides the generated vehicle allocation plan to the vehicle terminal 5 (S104). The vehicle terminal 5 acquires the vehicle allocation plan and displays the vehicle allocation plan on the display unit.

[0105] In addition, if it is not necessary to generate a vehicle allocation plan so that only passengers approved to share the ride according to the share-taking group information share the ride, the processing of the group registration unit 20 in S101 can be omitted.

[0106] 2.2 Example 1 4(a), the processing of the vehicle allocation plan generation unit 23 when distributing vehicle C1 to passengers A to C will be described using Example 1 as an example. Example 1 illustrates the processing when there is no registered sharing group or when all passengers are in the same sharing group. Also, the vehicle capacity is 3 and the number of vehicles is 1.

[0107] The acquisition unit 21 acquires the boarding locations and / or disembarking locations included in the vehicle dispatch reservation information of passengers A to C. In the first embodiment, the boarding locations (departure points) of passengers A to C are the same point Ps, and the disembarking locations are points Pa to Pc.

[0108] The vehicle allocation plan generation unit 23 generates location information based on the acquired boarding locations and / or disembarking locations. The location information is information indicating all inter-location costs to be optimized. In this embodiment, the vehicle allocation plan generation unit 23 generates first location information (FIG. 8(a)) indicating a first inter-location distance disS2P from the location Ps, which is the departure location, to each of the locations Pa to Pc, which are disembarking locations, and second location information (FIG. 8(b)) indicating a second inter-location distance disP2P between each of the locations Pa to Pc, which are disembarking locations.

[0109] The vehicle dispatch plan generation unit 23 inputs input data including the location information of FIG. 8 into the QUBO formula and generates a QUBO matrix. FIG. 9 shows an example of the QUBO matrix generated in the first embodiment. In FIG. 9, each row and column represents a variable x[v, t, i]. In FIG. 9, the matrix disS2P is generated by the term of the first location information disS2P in equation (2), and the matrix disP2P is generated by the term of the second location information disP2P in equation (2). Each element of the QUBO matrix represents energy. In the matrix disP2P, the rows represent the t-th destination (drop-off location) of the vehicle v under consideration, the columns represent the t+1-th destination (drop-off location) of the vehicle v, and the values ​​represent the dispatch cost between two locations. For example, row x[1,1,B] and column x[1,2,A] indicate that when you first arrive at passenger B's drop-off point Pb and then (secondly) arrive at passenger A's drop-off point Pa, the dispatch cost between those points is 16. Note that if the QUBO matrix is ​​a symmetric matrix, the values ​​on the bottom left of the diagonal can be omitted and input to the QUBO solver. In the QUBO matrix in Figure 9, the values ​​on the bottom left of the diagonal are omitted.

[0110] FIG. 10(a) illustrates the results of the QUBO solver 6 running the QUBO matrix in FIG. 9. In FIG. 10(a), passenger i indicates the drop-off location of the passenger who is the t-1th in the previous drop-off order, and passenger j indicates the drop-off location of the passenger who is the tth in the next drop-off order. For example, in drop-off order t=2, the energy from the drop-off location Pb of the previous passenger B to the drop-off location Pa of the next passenger A is 16. FIG. 10(b) illustrates an overview of the optimized vehicle dispatch plan. According to this, in Example 1, it can be understood that the dispatch cost can be minimized (total energy 35) by having vehicle C1 travel in the order of points Ps, Pb, Pa, and Pc. Note that Example 1 does not assume shared groups, which raises issues such as the risk of trouble between passengers and the unclear location of contractual responsibility for the ride-sharing service between passengers and crew members.

[0111] 2.3 Example 2 4(a), the processing of the vehicle allocation plan generation unit 23 when vehicle C1 is allocated to passengers A to C, passengers A and C belong to a synergistic group G1, and passenger B belongs to a synergistic group G2 will be described as Example 2. It is assumed that ride-sharing has not been approved between synergistic groups G1 and G2.

[0112] In one embodiment, the synergistic group information can be registered using a group function of a social networking service (SNS), etc. Furthermore, passenger information can be registered by joining a group on the SNS, etc.

[0113] The group registration unit 20 receives a designation of a group on an SNS or the like from the administrator's terminal device and accepts a registration instruction to register the group as synergistic group information. The passenger terminal 3 transmits a request to join the group. The administrator's terminal device approves the request to join and notifies the passenger terminal 3 of passenger information including the passenger ID. The passenger terminal 3 can make a vehicle reservation within the group that the passenger has joined by inputting vehicle reservation information using the passenger ID and transmitting it to the vehicle dispatch device 2. Note that the group registration unit 20 may issue passenger IDs to existing participants in the group by registering a group on an SNS or the like as synergistic group information.

[0114] The administrator's terminal device can refer to billing data for fees incurred by passengers in the shared group when using the dispatch service. The billing data is issued by the vehicle terminal 5 or the vehicle management company, etc. The dispatch device 2 can calculate the fees for each passenger related to the billing data and generate passenger-specific billing data. This allows the administrator to collectively pay the fees for the dispatch service in the shared group. The administrator can also bill each passenger separately.

[0115] The acquisition unit 21 acquires ride-sharing reservation information, passenger information, and synergistic group information for passengers A to C. The ride-sharing plan generation unit 23 generates first location information (FIG. 11(a)) and second location information (FIG. 11(b)) based on the boarding location and / or disembarking location included in the ride-sharing reservation information. The ride-sharing plan generation unit 23 also extracts synergistic groups included in the passenger information (FIG. 11(c)). The ride-sharing plan generation unit 23 also extracts ride-sharing approval relationships between the extracted synergistic groups G1 and G2 by referring to the synergistic group information (FIG. 11(d)).

[0116] In the second embodiment, the constraint condition is set as the approval of synergy among the synergy groups. This constraint condition is set as a constraint term in the objective function H(x) of the formula (1). The formula (3) shows the constraint term related to the constraint condition that only passengers who are approved to share by the synergy group information are allowed to ride together. Here, the approval relationship paG2paGDsb iindicates a list of approval relationships for ride-sharing between passengers.

[0117]

number

[0118] The left term in equation (3) is a value indicating whether passenger i boards vehicle v in a certain arrival order (boarding order or disembarking order) t. If this term is 1 or greater, it indicates that passenger i boards vehicle v in the arrival order (boarding order or disembarking order) t, and if it is 0, it indicates that passenger i does not board vehicle v in the arrival order (boarding order or disembarking order) t. Figure 12(a) is a schematic diagram of this term. When at least one of passengers A to C is boarding in a certain arrival order (disembarking order) t, the value of this term is 1 or greater. Note that Example 2 is an example of a drop-off service, so all combinations of passengers A to C boarding at the same boarding location are considered.

[0119] The right-hand term in equation (3) serves to restrict other passengers who do not approve of carpooling from riding in vehicle v in which passenger i is riding. If this term is 1 or greater, it does not satisfy the constraint, i.e., passengers who do not approve of carpooling will ride together. If it is 0, it satisfies the constraint, and passengers who approve of carpooling will ride together. Figure 12(b) shows passenger-to-passenger non-sharing information related to this constraint. In Example 2, passenger B belongs to the sharing group G1 of passengers A and C and the sharing group G2 that does not approve of carpooling, and is not approved to ride with passengers A and C. The vehicle allocation plan generation unit 23 generates the passenger-to-passenger non-sharing information shown in Figure 12(b) using the information shown in Figures 11(c) and 11(d).

[0120] The dispatch plan generation unit 23 inputs input data including the location information of FIG. 11 and the ride-sharing prohibition information of FIG. 12 into the QUBO formula to generate a QUBO matrix. FIG. 13 shows an example of a QUBO matrix related to the constraint term of equation (3). For simplicity of explanation, FIG. 13 omits the QUBO matrix related to the objective term and other constraint terms. According to FIG. 13, the energy of the element indicating the trip between passenger B and passengers A and C is 2, and the energy of the element indicating the trip between passenger A and passenger C is 0. When this QUBO matrix is ​​optimized by the QUBO solver 6, the combination with the smallest energy is derived as the optimal solution, and therefore the combination of passenger B and passengers A and C, which are not allowed to ride-sharing, sharing rides, is excluded from the optimal solution.

[0121] FIG. 14(a) illustrates the execution result of the QUBO solver 6 on a QUBO matrix including the matrix related to the objective term in FIG. 9 and the matrix related to the constraint term in FIG. 13. FIG. 14(b) shows a schematic diagram of a vehicle dispatch plan optimized to allow only passengers who agree to ride-sharing to share a ride. According to these figures, in Example 2, vehicle C1 travels to points Ps, Pc, and Pa in this order, minimizing the dispatch cost (total energy 23) and satisfying the condition that only passengers who agree to ride-sharing share a ride. Passenger B can be picked up and dropped off by vehicle C2, which is separate from vehicle C1, or vehicle C1 can pick up and drop off passengers A and C after or before picking them up and dropping off passengers. In Example 2, the vehicle dispatch plan generation unit 23 preferably adopts a solution that transports the largest number of passengers as the combinatorial optimal solution, and constraint terms for this solution may be set. Thus, Example 2 assumes a sharing group, resulting in a different vehicle dispatch plan from Example 1.

[0122] 2.4. Example 3 4(b), the processing of the vehicle allocation plan generation unit 23 when vehicles C1 and C2 are allocated to passengers A to D, and passengers A and C belong to synergistic group G1, passenger B belongs to synergistic group G2, and passenger D belongs to synergistic group G3 will be described as Example 3. Note that carpooling is not permitted between synergistic groups G1 and G3 and synergistic group G2, but is permitted between synergistic groups G1 and G3.

[0123] The acquisition unit 21 acquires the ride-sharing reservation information, passenger information, and sharing group information of passengers A to D. The ride-sharing plan generation unit 23 generates first location information (FIG. 15(a)) and second location information (FIG. 15(b)) based on the boarding location and / or disembarking location included in the ride-sharing reservation information. The ride-sharing plan generation unit 23 also extracts the sharing groups included in the passenger information (FIG. 15(c)). The ride-sharing plan generation unit 23 also extracts the ride-sharing approval relationships between the extracted sharing groups G1, G2, and G3 by referring to the sharing group information (FIG. 15(d)). The ride-sharing plan generation unit 23 also generates ride-sharing prohibition information between passengers based on the information in FIGS. 15(c) and 15(d) (FIG. 15(e)). According to this, passenger D belongs to a different synergistic group G3 from passengers A and C's synergistic group G1, but passenger D is approved to ride with passengers A and C according to the approval relationship of the synergistic group information (Figure 15(d)). On the other hand, passenger B is not approved to ride with passengers A, C, and D.

[0124] In the third embodiment, a QUBO formula including the constraint term shown in equation (3) is adopted. The vehicle dispatch plan generation unit 23 inputs the location information of FIG. 15 and input data including the non-shared information into the QUBO formula to generate a QUBO matrix. FIG. 16 shows an example of a QUBO matrix related to the objective term of equation (2). FIG. 17 shows an example of a QUBO matrix related to the constraint term of equation (3). The elements in the dotted line area in FIGS. 16 and 17 indicate the energy by vehicle C1 (variable x[1, t, i]), and the elements in the dashed line area indicate the energy by vehicle C2 (variable x[2, t, i]).

[0125] Figure 18(a) illustrates the results of running the QUBO solver 6 on a QUBO matrix including the matrices in Figures 16 and 17. Figure 18(b) shows an overview of a vehicle dispatch plan optimized for vehicles C1 and C2 so that only passengers who approve of carpooling can ride together. The solid line in Figure 18(b) indicates the route of vehicle C1, and the dashed line indicates the route of vehicle C2.

[0126] According to these, in Example 3, vehicle C1 travels to points Ps, Pc, Pa, and Pd in ​​this order, and vehicle C2 travels to points Ps and Pb in this order, thereby minimizing the dispatch cost (total energy 53) and satisfying the condition that only passengers who approve of carpooling can ride together. Here, minimizing the dispatch cost means minimizing the total energy of the dispatch cost of vehicle C1 and the dispatch cost of vehicle C2. Even if the number of vehicles is further increased, an efficient dispatch plan can be generated by similarly minimizing the total energy of the dispatch costs of all vehicles. In this way, in Example 3, an efficient dispatch plan can be generated even if the number of vehicles increases or if carpooling is approved between sharing groups.

[0127] <2.5. Modifications> A modified example will be described in which a vehicle allocation plan for a shared ride group is generated without using the constraint terms of equation (3). The vehicle allocation plan generation unit 23 generates input data for the combination model using the boarding locations and / or disembarking locations included in the vehicle allocation reservation information of multiple passengers who are approved to share a ride according to the shared ride group information. As a result, the variable x[v,t,i] is defined by one or more vehicles v, the arrival order t, and multiple passengers i who are approved to share a ride. The vehicle allocation plan generation unit 23 applies this variable x[v,t,i] to an objective function defined to minimize the allocation cost of one or more vehicles, thereby obtaining a combination optimal solution in which only passengers who are approved to share a ride according to the shared ride group information share a ride and the allocation cost is minimized. The vehicle allocation plan generation unit 23 generates a vehicle allocation plan using this combination optimal solution. The modified example has been described above.

[0128] According to the first embodiment, an optimal vehicle dispatch plan can be generated that satisfies the condition that only passengers who are approved to share a ride can share a ride. In the first to third embodiments using formula (3), an optimal vehicle dispatch plan can be generated that includes multiple passengers who belong to different sharing groups, which cannot be calculated in the modified example. In the modified example, passengers who are approved to share a ride can be extracted in advance, thereby reducing the calculation load on the combination model and the combinatorial optimization engine.

[0129] <3.1. Second Embodiment> Fig. 19 shows a flowchart of the vehicle dispatch process according to the second embodiment. In the second embodiment, when there is a large amount of vehicle dispatch reservation information for multiple passengers, a configuration is adopted in which passenger groups are generated in advance and a combinatorial optimal solution is obtained for each passenger group. This reduces the computational load associated with the combinatorial optimization problem.

[0130] The group registration unit 20 accepts the registration of a synergistic group (S201). First, the group registration unit 20 receives an instruction to register a synergistic group from the manager's terminal device and registers synergistic group information. The group registration unit 20 receives a request to join the synergistic group from the passenger terminal 3 and registers the passenger information in association with the synergistic group information. The participation request may be approved by an approval operation from the manager's terminal device, and the group registration unit 20 may be configured to execute a process of associating the passenger information with the synergistic group information if approved.

[0131] The acquisition unit 21 acquires various information (S202). The acquisition unit 21 acquires vehicle reservation information for a plurality of passengers from a plurality of passenger terminals 3. The acquisition unit 21 also acquires vehicle information for a plurality of vehicles from one or a plurality of vehicle terminals 5.

[0132] The group generation unit 22 classifies the passengers into one or more passenger groups based on the plurality of vehicle reservation information (S203). Here, the group generation unit 22 classifies the passengers into the passenger groups based on the desired boarding time and / or disembarking location included in the vehicle reservation information. The group generation unit 22 assigns one or more vehicles to each passenger group based on the plurality of vehicle reservation information and one or more vehicle information.

[0133] The vehicle allocation plan generation unit 23 generates a vehicle allocation plan for each passenger group so as to minimize the vehicle allocation cost of one or more vehicles (S204). The vehicle allocation plan generation unit 23 generates a vehicle allocation plan including a drop-off order based on the drop-off locations of multiple vehicle allocation reservation information included in the passenger group and the current vehicle locations of one or more vehicle information. The vehicle allocation plan generation unit 23 also generates a vehicle allocation plan including a boarding order based on the boarding locations of multiple vehicle allocation reservation information included in the passenger group and the current vehicle locations of one or more vehicle information. The vehicle allocation plan generation unit 23 obtains a combinatorial optimal solution that minimizes the vehicle allocation cost by calculation using the QUBO solver 6 or mathematical calculation. In the second embodiment, the size of the combinatorial problem is reduced by determining the passenger groups, so the method is not limited to deriving a combinatorial optimal solution by calculation using the QUBO solver 6.

[0134] The output unit 24 provides the generated vehicle allocation plan to the vehicle terminal 5 (S205). The vehicle terminal 5 acquires the vehicle allocation plan and displays the vehicle allocation plan on the display unit.

[0135] As described above, in the second embodiment, by generating passenger groups, it is possible to reduce the calculation load on the combinatorial optimization engine and shorten the calculation time, thereby providing an efficient vehicle dispatch plan. For example, even when quantum annealing or simulated annealing (including pseudo-quantum annealing) shown in Table 1 is adopted as a solver, it is possible to deal with situations such as when the scale of the problem is extremely large. Furthermore, when an exact solution is required for a small to medium-sized problem, a typical solution method or a general-purpose solution method can be adopted as a solver. [Explanation of symbols]

[0136] 1. Vehicle dispatch system 2. Dispatch device 20 Group Registration Department 21 Acquisition Department 22 Group Generation Section 23 Vehicle allocation plan generation unit 24 Output section 3 Passenger terminals 4 vehicles 5 Vehicle terminal 6. QUBO Solver DB storage unit DB1 Vehicle dispatch information storage unit DB2 map information storage section NW communication network

Claims

1. A vehicle dispatch system that provides a vehicle dispatch plan for vehicles shared by multiple passengers, a group registration unit that registers sharing group information that defines the relationship between a plurality of passengers who approve sharing; an acquisition unit that acquires ride reservation information of a plurality of passengers, including boarding locations and / or disembarking locations; A vehicle dispatch system comprising: a vehicle dispatch plan generation unit that generates a vehicle dispatch plan based on the boarding locations and / or disembarking locations included in the plurality of vehicle dispatch reservation information so that the dispatch cost of one or more vehicles is minimized and only passengers approved to share in the shared group information share in the shared vehicle.

2. the acquisition unit acquires vehicle information of one or more vehicles, The vehicle dispatch system of claim 1, wherein the vehicle dispatch plan generation unit obtains a combination optimal solution that minimizes the dispatch cost of one or more vehicles from among combinations of arrival orders of one or more vehicles, the boarding and / or disembarking locations of multiple passengers approved for sharing based on the synergistic group information, and the order of arrival at the boarding and / or disembarking locations.

3. the acquisition unit acquires vehicle information of one or more vehicles, The vehicle dispatch system of claim 1, wherein the vehicle dispatch plan generation unit obtains an optimal combination solution for a combination of arrival orders consisting of one or more vehicles, multiple passenger boarding and / or disembarking locations, and the order of arrival at the boarding and / or disembarking locations, such that only passengers approved to share according to the synergistic group information can share, and the dispatch cost of one or more vehicles is minimized.

4. the acquisition unit acquires vehicle information of one or more vehicles, including a vehicle capacity and a vehicle current location; The vehicle dispatch system according to claim 1 , wherein the vehicle dispatch plan generation unit generates the vehicle dispatch plan based on boarding locations and / or disembarking locations of a plurality of the vehicle dispatch reservation information and current vehicle locations of one or a plurality of the vehicle information.

5. 2. The vehicle dispatch system of claim 1, wherein the vehicle dispatch plan generation unit obtains a combined optimal solution that satisfies at least one constraint selected from the following: a condition that arrival orders are consecutively numbered starting from 1; a condition that a passenger has only one arrival order in one or more vehicles; and a condition that the number of passengers in the vehicles does not exceed the vehicle capacity.

6. 2. The vehicle dispatch system according to claim 1, wherein the vehicle dispatch plan generation unit obtains a combination optimal solution that minimizes the dispatch cost of one or more vehicles from among combinations of one or more vehicles, predetermined boarding locations, multiple disembarking locations, and passenger disembarkation orders.

7. 2. The vehicle dispatch system according to claim 1, wherein the vehicle dispatch plan generation unit obtains a combination optimal solution that minimizes the dispatch cost of one or more vehicles from among combinations of one or more vehicles, multiple boarding locations, predetermined disembarking locations, and passenger boarding order.

8. The acquisition unit acquires vehicle reservation information of a plurality of passengers, including desired boarding times or desired disembarking times, a group generation unit that classifies a plurality of passengers into one or a plurality of passenger groups based on at least one of a desired boarding time, a desired disembarking time, a boarding location, and a disembarking location included in the plurality of pieces of vehicle dispatch reservation information; The vehicle dispatch system according to claim 1 , wherein the vehicle dispatch plan generation unit generates a vehicle dispatch plan for each of the passenger groups so as to minimize a dispatch cost of one or more vehicles.

9. the acquisition unit acquires vehicle information of one or more vehicles, including a vehicle capacity and a vehicle current location; The vehicle dispatch system according to claim 8 , wherein the group generation unit assigns one or more of the vehicles to the passenger group based on a plurality of pieces of vehicle dispatch reservation information and one or more pieces of vehicle information.

10. The vehicle dispatch system according to claim 9 , wherein the group generation unit allocates the vehicles so that the sum of the vehicle capacities included in one or more pieces of vehicle information is equal to or greater than the number of passengers included in the passenger group.

11. The vehicle dispatch system according to claim 8 , wherein the group generation unit classifies a plurality of passengers who are in a relationship of approving synergy based on the synergistic group information into the passenger group.

12. a map information storage unit that stores a result of previously calculating a route distance or a route time between two points in association with map information; The vehicle dispatch system according to claim 1, wherein the vehicle dispatch plan generation unit generates the vehicle dispatch plan using the route distance or the route time acquired from the map information storage unit for the vehicle dispatch cost between the acquired multiple boarding locations and / or disembarking locations.

13. The vehicle dispatch system according to any one of claims 1 to 12, wherein the vehicle dispatch plan generation unit issues a processing request for a combinatorial optimization problem in which variables of each element related to the combination of arrival orders are defined to a combinatorial optimization engine, and obtains a combinatorial optimal solution from the combinatorial optimization engine.

14. A vehicle dispatch system that provides a vehicle dispatch plan for vehicles shared by multiple passengers, an acquisition unit that acquires vehicle reservation information of a plurality of passengers, including boarding locations and / or disembarking locations, and vehicle information of one or more vehicles, including vehicle current locations; a dispatch plan generation unit that issues a processing request to a combinatorial optimization engine for a combination model that defines variables including one or more vehicles, multiple boarding locations and / or disembarking locations included in multiple pieces of dispatch reservation information, and the order of arrival at the boarding locations and / or disembarking locations, obtains from the combinatorial optimization engine a combinatorial optimal solution that minimizes the dispatch cost of one or more vehicles, and generates a dispatch plan based on the combinatorial optimal solution.

15. A vehicle dispatching method for providing a vehicle dispatch plan for vehicles sharing a plurality of passengers, comprising: Registering shared ride group information that defines the relationship between multiple passengers who approve shared rides; Acquires ride reservation information for multiple passengers, including boarding and disembarking locations, A vehicle dispatch method in which a computer executes a process to generate a vehicle dispatch plan based on the boarding and disembarking locations included in the plurality of vehicle dispatch reservation information so that the dispatch cost of one or more vehicles is minimized and only passengers approved for sharing according to the sharing group information share.

16. A vehicle dispatch program that provides a vehicle dispatch plan for vehicles shared by multiple passengers, a group registration unit that registers sharing group information that defines the relationship between a plurality of passengers who approve sharing; an acquisition unit that acquires ride reservation information of a plurality of passengers, including boarding locations and disembarking locations; A vehicle dispatch program that causes a computer to function as a vehicle dispatch plan generation unit that generates a vehicle dispatch plan based on the boarding and disembarking locations included in the plurality of vehicle dispatch reservation information so that the dispatch cost of one or more vehicles is minimized and only passengers approved to share the vehicle according to the shared group information share the vehicle.

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