Dispatch system, dispatch method, dispatch 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 allocation system, a vehicle allocation method, and a vehicle allocation program for generating a shared vehicle plan.

Background Art

[0002] Conventionally, in public transportation such as buses, shared rides by multiple passengers have been introduced. In such shared rides, they are operated on fixed routes like regular buses, and operations such as changing the route according to the demands of each passenger were not possible.

[0003] The Ministry of Land, Infrastructure, Transport and Tourism decided to introduce a taxi sharing service system on October 29, 2021. In the new sharing service system, passengers share rides in buses, taxis, etc., and operations are possible such as flexibly changing the route according to the demands of each passenger.

[0004] Patent Document 1 discloses a technique aimed at suitably performing dynamic generation of an operation plan. In Patent Document 1, a plurality of operation plans are obtained based on passenger information including boarding or alighting points where a plurality of passengers board or alight from a vehicle sharing rides and boarding or alighting times, and a list of the plurality of obtained operation plans is displayed on terminal devices of respective multiple transportation operators. It is described that a selection input for selecting, from the list, the operation plan for accepting an order is received from a terminal device of any one of the transportation operators. Also, in Patent Document 1, it is described that operation plans are generated by clustering passengers and allocating one bus to each cluster.

[0005] Patent Document 1 discloses a technique related to a sharing service characterized by generating a plurality of operation plans based on passenger information including boarding or alighting points and boarding or alighting times, and selecting an operation plan for accepting an order from a list of those plurality of operation plans.

[0006] Patent Document 2 discloses a demand-responsive operation management system applicable to public transportation services such as buses. Patent Document 2 describes a control method for a demand-responsive operation management system comprising a vehicle that operates according to an operation plan, a first user terminal, a second user terminal, and an operation management device that is communicably connected to the vehicle, the first user terminal, and the second user terminal, wherein after the vehicle has started operating according to a first operation plan, the operation management device receives a first usage request from the first user terminal including a first boarding / alighting point, and the operation management device receives a second usage request from the second user terminal including a second boarding / alighting point, the operation management device notifies the vehicle of a second operation plan with a stopping position between the first boarding / alighting point and the second boarding / alighting point, and the vehicle, upon receiving notification of the second operation plan, starts operating according to the second operation plan.

[0007] Patent Document 2 discloses a technology for a demand-responsive service, characterized in that, after commencing operation according to a first operation plan, the service receives usage requests from a first user terminal and a second user terminal, and then generates a second operation plan with a stopping position between the two boarding / alighting points. [Prior art documents] [Patent Documents]

[0008] [Patent Document 1] International Publication No. 2020 / 262673 [Patent Document 2] Patent No. 6273656 [Overview of the project] [Problems that the invention aims to solve]

[0009] The demand for ride-sharing services is increasing to address driver shortages for taxis and buses, and to reduce the financial burden on individual passengers. However, ride-sharing among strangers has presented challenges, such as the risk of disputes between passengers and the ambiguity of contractual responsibilities between drivers and passengers.

[0010] Furthermore, implementing a new ride-sharing service system would be difficult because it would require complex calculations to determine the most suitable route based on the pick-up and drop-off locations of multiple passengers.

[0011] In view of the above-mentioned problems, the present invention aims to solve the problem of providing a vehicle dispatch plan for multiple passengers sharing a vehicle. More specifically, the present invention aims to solve the problem of providing an optimal dispatch plan in a ride-sharing service, including the relationships between passengers who approve of ride-sharing. [Means for solving the problem]

[0012] [1] A dispatch system that provides a dispatch plan for vehicles carrying multiple passengers, A group registration unit that registers synergy group information defining the relationships between multiple passengers who approve synergy, An acquisition unit that acquires dispatch reservation information for multiple passengers, including the boarding location and / or alighting location, A dispatch system comprising: a dispatch plan generation unit that generates a dispatch plan based on the pick-up and / or drop-off locations included in a plurality of the aforementioned dispatch reservation information, such that the dispatch cost of one or more vehicles is minimized and only passengers whose carpooling is approved by the carpooling group information are allowed to carpool. [2] The acquisition unit acquires vehicle information of one or more vehicles, including the current location of the vehicle. The dispatch system according to [1], wherein the dispatch plan generation unit obtains a combination of arrival order combinations that minimize the dispatch cost of one or more of the vehicles, from among the combinations of one or more vehicles, the boarding locations and / or alighting locations of multiple passengers whose ride-sharing is approved by the ride-sharing group information, and the order in which they arrive at the boarding locations and / or alighting locations. [3] The acquisition unit acquires vehicle information of one or more vehicles, including the current location of the vehicle. The dispatch system according to [1] or [2], wherein the dispatch plan generation unit obtains an optimal combination of arrival order, which is a combination of one or more vehicles, the boarding locations and / or alighting locations of multiple passengers, and the order of arrival at the boarding locations and / or alighting locations, such that the condition is met that only passengers approved for carpooling by the carpooling group information carpool together, and the dispatch cost of one or more vehicles is minimized. [4] The acquisition unit acquires vehicle information for one or more vehicles, including the number of passengers and the current location of the vehicle. The dispatch system according to any one of [1] to [3], wherein the dispatch plan generation unit generates the dispatch plan based on the pick-up and / or drop-off locations of a plurality of dispatch reservation information and the current location of one or more vehicle information. [5] The dispatch system according to any one of [1] to [4], wherein the dispatch plan generation unit obtains a combinationally optimal solution that satisfies at least one constraint selected from the following: the condition that the arrival order is numbered sequentially starting from 1; the condition that a single passenger has only one arrival order in one or more vehicles; and the condition that the number of vehicles does not exceed the vehicle capacity. [6] The dispatch system according to any one of [1] to [5], wherein the dispatch plan generation unit obtains an optimal combination from among the combinations of disembarking order, which consists of one or more vehicles, a predetermined boarding location, a plurality of disembarking locations, and the order in which passengers disembark, the dispatch system that minimizes the dispatch cost of one or more of the vehicles. [7] The dispatch system according to any one of [1] to [6], wherein the dispatch plan generation unit obtains the optimal combination that minimizes the dispatch cost of one or more of the vehicles from among the combinations of boarding order consisting of one or more vehicles, multiple boarding locations, predetermined disembarking locations, and the boarding order of passengers. [8] The acquisition unit acquires dispatch reservation information for multiple passengers, including the desired boarding time or desired alighting time. The system includes a group generation unit that classifies multiple passengers into one or more passenger groups based on at least one of the following: desired pick-up time, desired drop-off time, pick-up location, and drop-off location included in multiple ride-hailing reservation information. The dispatch system according to any one of [1] to [7], wherein the dispatch plan generation unit generates a dispatch plan for each of the passenger groups so as to minimize the dispatch cost of one or more vehicles. [9] The acquisition unit acquires vehicle information for one or more vehicles, including the number of passengers and the current location of the vehicles. The dispatch system according to [8], wherein the group generation unit assigns one or more vehicles to the passenger group based on a plurality of dispatch reservation information and one or more of the vehicle information.

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

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

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

[12] A map information storage unit is provided which stores the result of pre-calculating the route distance or route time between two points in association with map information, The dispatch system according to any one of [1] to

[11] , wherein the dispatch plan generation unit generates the dispatch plan using the route distance or route time obtained from the map information storage unit for the dispatch cost between a plurality of the obtained pick-up locations and / or drop-off locations.

[13] The dispatch system according to any one of [1] to

[12] , wherein the dispatch plan generation unit makes a request to a combinatorial optimization engine to process a combinatorial optimization problem that defines the variables of each element relating to the combination of arrival order, and obtains a combinatorial optimal solution from the combinatorial optimization engine.

[14] A dispatch system that provides a dispatch plan for vehicles carrying multiple passengers, An acquisition unit that acquires multiple passenger dispatch reservation information, including boarding and / or alighting locations, and vehicle information for one or more vehicles, including the vehicle's current location. A dispatch system comprising: a dispatch plan generation unit that requests a processing request to a combinatorial optimization engine for a combinatorial model that defines variables including one or more vehicles, multiple pick-up locations and / or drop-off locations included in multiple dispatch reservation information, and the order of arrival at the pick-up locations and / or drop-off locations; obtains a combinatorial optimal solution from the combinatorial optimization engine that minimizes the dispatch cost of one or more vehicles; and generates a dispatch plan based on the combinatorial optimal solution.

[0013] [1] According to the invention, by registering a carpool group and generating a carpool plan only by passengers whose carpooling is approved, a carpool service that solves various problems associated with carpooling can be provided. [2] According to the invention, by using the pick-up location and / or drop-off location of passengers whose carpooling is approved, an optimal carpool plan can be generated based on the optimal combination of passengers whose carpooling is approved. [3] According to the invention, by processing passengers including those whose carpooling is approved and those whose carpooling is not approved, an optimal carpool plan can be generated based on the optimal combination of passengers whose carpooling is approved. [4] According to the invention, a carpool plan can be generated considering the current location of the vehicle. [5] According to the invention, it is possible to prevent an inappropriate combination from being adopted as the optimal solution. [6] According to the invention, a carpool plan can be generated by delivery service. [7] According to the invention, a carpool plan can be generated by pick-up service. [8] According to the invention, by targeting passenger groups, the processing load for generating the carpool plan can be reduced. [9],

[10] According to the invention, by appropriately allocating vehicles to passenger groups and generating a carpool plan, the processing load can be reduced.

[11] According to the invention, by classifying passengers based on the carpool group, while reducing the processing load for generating the carpool plan, an optimal carpool plan can be generated in which only passengers whose carpooling is approved carpool together.

[12] According to the invention, by deriving distance and time in advance, it contributes to shortening the processing time and reducing the processing burden.

[13] According to the invention, the combinatorial optimization process can be executed in real time.

[14] According to the invention, in a new carpool service system, a process of determining an appropriate route according to the requests such as the pick-up locations and drop-off locations of multiple passengers can be executed in real time.

Effect of the Invention

[0014] According to the present invention, it is possible to provide a vehicle dispatch plan for multiple passengers sharing a vehicle. In particular, it is possible to provide an efficient vehicle dispatch plan for group ride-sharing. [Brief explanation of the drawing]

[0015] [Figure 1] A block diagram of the system according to this embodiment. [Figure 2] Hardware configuration diagram of this embodiment. [Figure 3] Data configuration diagram of this embodiment. [Figure 4] A schematic diagram illustrating the vehicle dispatch plan of this embodiment. [Figure 5] An example of passenger group classification. [Figure 6] An example of the screen display of the terminal device of this embodiment. [Figure 7] Flowchart of the vehicle dispatch process in Embodiment 1. [Figure 8] Example data structure used in Example 1. [Figure 9] An example of the QUBO matrix from Example 1. [Figure 10] An example of the execution result of the combinatorial optimization process in Example 1. [Figure 11] Example data structure used in Example 2. [Figure 12] A schematic diagram illustrating the constraints used in Example 2. [Figure 13] An example of the QUBO matrix in Example 2. [Figure 14] An example of the execution result of the combinatorial optimization process in Example 2. [Figure 15] Example data structure used in Example 3. [Figure 16] An example of the QUBO matrix from Example 3. [Figure 17] An example of the QUBO matrix from Example 3. [Figure 18] An example of the execution result of the combinatorial optimization process in Example 3. [Figure 19] Flowchart of the vehicle dispatch process in Embodiment 2. [Modes for carrying out the invention]

[0016] The following describes a vehicle dispatch system and vehicle dispatch method according to embodiments of the present invention with reference to the drawings. Note that the embodiments shown below are examples of the present invention, and the present invention is not limited to these embodiments; various configurations can be adopted.

[0017] In this embodiment, the configuration and operation of the dispatch system and dispatch device will be described, but a dispatch method, computer program, and program recording medium on which the program is stored with a similar configuration will also produce similar effects. Using a program recording medium, for example, the program can be installed on a computer. The series of processes according to this embodiment, which will be described below, are provided as a program executable on a computer and can be provided via a non-transient computer-readable recording medium such as a CD-ROM or flexible disk, or via a communication line.

[0018] The dispatch system is comprised of a computer system. The computer system includes a processing unit such as a CPU (Central Processing Unit) and a memory device. The computer system can function as a dispatch device by executing a dispatch program stored in the memory device using its processing unit. The dispatch method is implemented through processing by the computer system, including the dispatch device.

[0019] In this explanation, ride-sharing refers to a service where multiple passengers ride together in a vehicle such as a bus or taxi, and the route can be flexibly changed according to the requests of each passenger regarding their boarding and alighting locations. Group ride-sharing refers to a service where multiple passengers who have agreed to ride-sharing are treated as a group, and a ride-sharing service is provided to them.

[0020] A dispatch plan is a sequence of operations using one or more vehicles to transport multiple passengers to and from their pick-up and / or drop-off locations. Multiple combinations exist for how each point is served within the dispatch plan. By selecting the combination that offers the shortest route and travel time, an efficient ride-hailing service can be achieved.

[0021] In this embodiment, the dispatch plan includes three types: drop-off, pick-up, and mixed-passenger. A drop-off service refers to a dispatch plan in which a vehicle picks up multiple passengers simultaneously from a predetermined pick-up location and transports them to their respective different drop-off locations. A pick-up service refers to a dispatch plan in which a vehicle goes to different pick-up locations for multiple passengers, picks them up individually, and transports them simultaneously to a predetermined drop-off location. A mixed-passenger service refers to a dispatch plan in which a vehicle goes to different pick-up locations for multiple passengers, picks them up individually, and transports them to their respective different drop-off locations.

[0022] In this specification, the destination refers to the pick-up or drop-off point of passengers being transported by the vehicle. The departure point refers to the starting point in the dispatch plan. For outbound services, the departure point may be a predetermined pick-up point or the vehicle's current location, while for pick-up services and mixed services, the vehicle's current location may be used.

[0023] In this specification, arrival order refers to the order in which a vehicle arrives at multiple destinations (boarding and alighting points). Boarding order refers to the order in which a vehicle arrives at the boarding points of multiple passengers. Alighting order refers to the order in which a vehicle arrives at the alighting points of multiple passengers.

[0024] A combinatorial optimization problem is a problem that seeks to find the optimal combination from among multiple combinations as described above. An efficient vehicle dispatch plan can be derived by solving a type of traveling salesman problem. In the calculation of combinatorial optimization problems, a combinatorial explosion occurs where the number of candidate solutions increases rapidly with the size of the problem. In the combinatorial optimization problem in 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 for n=5, 720 for n=7, and 8.8e+30 for n=30, and processing all combinations by brute force becomes impractical in real time.

[0025] Combinatorial optimization problems can be formalized, and their exact or approximate solutions can be derived using a solver, which is a combinatorial optimization engine. Furthermore, combinatorial optimization problems can be formalized as QUBO equations and represented as QUBO matrices incorporating actual data. This QUBO matrix can then be used to derive an exact or approximate solution using a QUBO solver, which is a combinatorial optimization engine. QUBO solvers are implemented using quantum annealing-type quantum computers or classical computers using simulated annealing algorithms. In the future, QUBO solvers may also be implemented using gate-type quantum computers. QUBO solvers can solve combinatorial optimization problems in a relatively short time, even when the number of combinations is large. However, the scale of the problems they can handle (number of combinations) and the time it takes 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 time. In this embodiment, an efficient vehicle dispatch plan can be generated using a combinatorial optimization engine capable of processing combinatorial optimization problems. In this embodiment, the combinatorial optimization engine is specifically described using an implementation example based on the QUBO solver, but this is not limited to this, and solvers including mathematical programming can be used. Also, in this embodiment, the solution derived as a result of combinatorial optimization is referred to as the optimal solution, but its accuracy depends on how the solver is implemented and used, and it is sufficient if it has a practical accuracy as an exact solution or an approximate solution. The exact solution method includes typical solution methods that are applied to specific problems and general solution methods that are applied to general problems.

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

[0027] [Table 1]

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

[0029] The dispatch device 2 includes, as functional components, a group registration unit 20 for registering a group of passengers who approve of sharing a ride, an acquisition unit 21 for acquiring various information, a group generation unit 22 for classifying multiple passengers into passenger groups, a dispatch plan generation unit 23 for generating a dispatch plan for vehicles in which multiple passengers will share a ride, and an output unit 24 for outputting the dispatch plan to an external device. Note that the group generation unit 22 may not be included in the dispatch device 2 according to Embodiment 1.

[0030] The passenger terminal 3 is a terminal device operated by passengers requesting a ride from vehicle 4. The passenger terminal 3 receives ride reservation information from each passenger and transmits the ride request to the ride dispatch device 2, thereby enabling the ride dispatch service to be provided by the ride dispatch system 1.

[0031] Vehicle 4 is a vehicle that carries multiple passengers and is a taxi or bus dispatched to passengers. These vehicles 4 are equipped with vehicle terminals 5, such as a driver's personal terminal or car navigation system, in either a fixed or portable form, without any restrictions. Vehicle 4 may be an autonomous vehicle and may or may not have a driver.

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

[0033] The storage unit DB is configured as a database comprising a dispatch information storage unit DB1 for storing dispatch information and a map information storage unit DB2 for storing map information.

[0034] The dispatch device 2 is connected to the QUBO solver 6 for data communication. 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 an execution result. The dispatch device 2 can generate an efficient dispatch plan using the obtained combinatorial optimization 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] Figure 2(a) shows the hardware configuration diagram of the dispatch system 2. The dispatch system 2 comprises a control device 201, a storage device 202, and a communication device 203 as its hardware configuration, with each component connected by a bus interface. In this embodiment, the dispatch system 2 can use computer devices such as a server or a personal computer. The dispatch system 2 is composed of multiple computer devices, and as long as the overall system can realize the above-mentioned functional components (20-24), it is not limited to the configuration shown in Figure 2.

[0036] The control device 201 consists of one or more processors such as a CPU and controls the overall processing in the dispatch device 2 by executing the dispatch program, OS (Operating System), and other applications. The storage device 202 is an HDD (Hard Disk Drive), SSD (Solid State Drive), flash memory, RAM (Random Access Memory), etc., and stores the dispatch program and various data. The communication device 203 is a communication interface such as wired communication or wireless communication and controls data communication with external devices. Furthermore, the communication device 203 can perform data communication with external devices by controlling communication with the communication network NW.

[0037] Figure 2(b) shows a modified example of the hardware configuration diagram of the dispatching system 2. According to Figure 2(b), the dispatching system 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 Figure 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 will operate according to control instructions from the classical computer. If the QUBO solver 6 is implemented using simulated annealing, it will be configured as a classical computer.

[0038] Figure 2(c) shows a hardware configuration diagram of terminal devices 9, including passenger terminal 3 and vehicle terminal 5. Terminal device 9 comprises a control device 901, a storage device 902, a communication device 903, an input device 904, and an output device 905 as its hardware configuration. Terminal device 9 may also be equipped with a GPS communication device. In this embodiment, terminal device 9 can be a smartphone, a personal computer, a tablet terminal, etc. Vehicle terminal 5 may be a car navigation system.

[0039] The control device 901 consists 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, and other applications. 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 dispatch device 2. The input device 904 is an input interface that accepts input operations from the user and consists of a microphone, touch panel, mouse, keyboard, etc. The output device 905 consists of a display for display output. The GPS communication device can acquire the position coordinates of the terminal device 9 by GPS communication.

[0040] Figure 3 shows an example of the data structure for various types of information. The dispatch information includes dispatch reservation information and vehicle information. Figure 3 illustrates one configuration of a drop-off service where each passenger is picked up from the same pick-up location Ps and dropped off at their respective destinations. In a drop-off service, since each passenger boards from the same pick-up location Ps, the boarding order is always 1 (simultaneous boarding). The current location of each vehicle can also be the pick-up location Ps. It is also possible to pick up and drop off each passenger from different pick-up locations, and the configuration is not limited to this example.

[0041] The ride-hailing reservation information is entered by the passenger via the passenger terminal 3 as a ride-hailing reservation and stored in the ride-hailing information storage unit DB1. As shown in Figure 3(a), the ride-hailing reservation information includes a ride-hailing reservation ID, a passenger ID, a pick-up location, a drop-off location, the number of passengers, the desired pick-up time, and the desired drop-off time. The pick-up location and a drop-off location are location coordinates in terms of latitude and longitude. The pick-up location and a drop-off location can be determined by a configuration known as geocoding or address matching, where the corresponding location coordinates are obtained by inputting landmarks or other information that are pre-associated with addresses or location coordinates. The ride-hailing reservation information allows identification of the passenger who made the reservation by the passenger ID, and the passenger information corresponding to the passenger ID can be referenced.

[0042] Vehicle information is transmitted from the vehicle terminal 5 and stored in the dispatch information storage unit DB1. As shown in Figure 3(b), the vehicle information includes a vehicle ID, the vehicle's current location, the vehicle's passenger capacity, and the vehicle's departure time. The vehicle's current location is the position coordinates obtained by GPS communication or the like. The vehicle information is transmitted from the vehicle terminal 5 at predetermined intervals or when the dispatch plan begins.

[0043] Passenger information is stored in the dispatch information storage unit DB1 upon prior registration request by the passenger. As shown in Figure 3(c), the passenger information includes a passenger ID, name, gender, age, and identification information of the ride-sharing group to which the passenger belongs (ride-sharing group ID). A ride-sharing group is a group formed by multiple passengers who mutually approve ride-sharing. Ride-sharing groups can be organizations such as companies, schools, government offices, and various institutions, or groups formed among acquaintances. Furthermore, if ride-sharing is approved between one ride-sharing group and another, it is also possible for passengers belonging to different approved ride-sharing groups to ride together. For example, ride-sharing is more likely to be accepted between passengers belonging to the same organization or related organizations. In one embodiment, the present invention provides a ride-sharing service that is particularly suited to passengers whose ride-sharing is approved by a ride-sharing group that is considered to greatly benefit from the ride-sharing service.

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

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

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

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

[0048] Furthermore, the ride-sharing group information allows for the setting of one or more predetermined pick-up and / or drop-off locations. The predetermined pick-up location is set as the pick-up location for ride-sharing group passengers' reservations. Specifically, a ride-sharing plan is provided for the drop-off service from the predetermined pick-up location, such as a rotary designated by the administrator, to each passenger's drop-off location (such as their home) included in the ride-sharing reservation. The predetermined drop-off location is set as the drop-off location for ride-sharing group passengers' reservations. Specifically, a ride-sharing plan is provided for the pick-up service from each passenger's pick-up location, such as a rotary designated by the administrator, to each passenger's drop-off location included in multiple ride-sharing reservations. By setting predetermined pick-up and / or drop-off locations, the ride-sharing plan can be generated according to prior schedules, thus reducing the computational load.

[0049] The outline of the dispatch plan will be explained with reference to Figure 4. The dispatch plan derives the sequence in which one or more vehicles v arrive at the respective drop-off locations of multiple passengers from a certain departure point as a return trip. In this embodiment, "location" includes the current location of vehicle v, the boarding locations and / or drop-off locations of passengers, etc. Figure 4 illustrates an example of a return trip where the vehicle's current location is the boarding location Ps, and all passengers depart from the same boarding location Ps and head to different drop-off locations Pa~Pc. Note that this example is for the sake of simplicity, and the present invention is also applicable when the vehicle's current location is different from the initial boarding location Ps, when passengers depart from different boarding locations, and even for pick-up trips and mixed trips. This specification deals with the simplified embodiment shown in Figure 4, but this embodiment is not limited to these embodiments.

[0050] Figure 4(a) illustrates the dispatch of three passengers A, B, and C. The respective drop-off locations for passengers A, B, and C are shown as points Pa, Pb, and Pc. The departure point is shown as point Ps. Figure 4(a) also shows the cost between each point numerically. Passengers A, B, and C each belong to a shared ride group. For example, passengers A and C belong to shared ride group G1, and passenger B belongs to shared ride group G2. If ride-sharing is not approved between shared ride groups G1 and G2, passenger A or C cannot ride with passenger B. In this case, it is necessary to generate a dispatch plan, for example, by dispatching a separate vehicle to passenger B, or by having one vehicle first drop off passengers A and C at their drop-off locations, then returning to departure point Ps to pick up passenger B.

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

[0052] Figure 4(c) shows a table of inter-point costs corresponding to Figure 4(a). Figure 4(d) shows a table of inter-point costs corresponding to Figure 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. The dispatch plan is generated to minimize the dispatch cost by dispatching one or more vehicles to as many points as possible while satisfying the constraints described later. In this embodiment, the dispatch cost is the vehicle's mileage, and the dispatch plan is generated so that the sum of the mileages is minimized. Inter-point cost is also expressed as the distance between points.

[0053] <1.1. Combinatorial Models> In this embodiment, a combinatorial model is used to obtain the optimal combination of arrival order (boarding order or alighting order) for multiple passengers to their respective destinations (including boarding and alighting locations). 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 the aforementioned combinatorial optimization problem such as arrival order.

[0054] To simplify the explanation, the following details will be described using a combination model of the order of drop-offs at multiple drop-off locations included in multiple ride reservations as an example. The combination model according to this embodiment is a model that finds the route that minimizes the ride-hailing cost when one or more vehicles 4 make one round trip to the pick-up and / or drop-off locations of multiple passengers.

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

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

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

[0058] As a specific example, the objective is to minimize the sum or average of the distances traveled by one or more vehicles. Another objective is to minimize the sum or average of the travel times of multiple passengers. Yet another objective is to minimize the number of vehicles to be dispatched. Finally, another objective is to minimize the sum or average of the fares of multiple passengers. The objective function can employ at least one of these objectives.

[0059] The constraints on the objective function are set to prevent the selection of combinatorially optimal solutions that are not realistically possible or unsuitable for adoption. The objective function may have one or more constraint terms related to the constraints. The constraints will be described in detail later.

[0060] The objective function H(x) is defined as shown in equation (1), with terms H1(x), H2(x), and H3(x) representing one or more objective or constraint terms. At least one objective term is set. There is no limit to the number of constraint terms, and some terms may not be set. The objective function H(x) represents the sum of the energy of the objective and constraint terms. In this embodiment, the solution that minimizes the sum of the energy of the objective function is the combinatorially optimal solution that minimizes the vehicle dispatch cost.

[0061]

number

[0062] The 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 indicates the inter-point costs between each location. In this embodiment, the first location information indicates the inter-point costs between the departure point and each passenger's boarding and / or alighting location, and the second location information indicates the inter-point costs between each passenger's boarding locations, alighting locations, or boarding locations.

[0063] In this embodiment, the input data is represented by the following variables in the objective term shown in equation (2): First location information: disS2P, Second location information: disP2P, Vehicle capacity: capaNums v Number of ride reservations: iNum, Vehicle v, Arrival order t, Destination i, j. Number of vehicles: vNum. Note that the number of vehicles vNum is equal to the number of passengers capaNums. v This represents the length of the objective term. This objective term is an example of the objective term H1(x) in the objective function of equation (1), and for simplicity, passenger number information is omitted as it is assumed to be 1 person in all cases.

[0064]

number

[0065] The constraints on the combinatorial model are described below.

[0066] The combination model according to this embodiment has several constraints. The constraints include at least one selected from the following: a condition that the arrival order be sequential starting from 1; a condition that a single passenger has only one arrival order in one or more vehicles; and a condition that the number of vehicles does not exceed the vehicle capacity. Further constraints may include a condition that the arrival order of the disembarking destination can only be set after the arrival order of a single passenger's boarding destination, or a condition that only passengers who have approved carpooling can carpool in the same vehicle. The dispatch plan generation unit 23 can obtain an appropriate optimal combination solution by narrowing down the candidates for the optimal combination solution based on the constraints.

[0067] The constraint term outputs the minimum energy (e.g., 0) when the constraint condition is satisfied. When the constraint condition is not satisfied, the constraint term outputs an energy above a predetermined value. The constraint term is weighted such that the energy output when the constraint condition is not satisfied is greater than or equal to the energy output of the objective term. Therefore, when the constraint condition is not satisfied, the objective function derives a high energy regardless of the energy output of the objective term, thus discouraging the adoption of that combination as the combinatorially optimal solution.

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

[0069] The combination model is the same in Embodiment 1 and Embodiment 2 described later. Note that a combination model for obtaining the optimal combination of disembarking order for multiple passengers at their respective disembarking locations, and a combination model for obtaining the optimal combination of boarding order from the boarding location may also be used. The dispatch plan generation unit 23 can generate a dispatch plan by obtaining the optimal combination from a combination optimization engine using the output data of the combination model.

[0070] <1.2. Shipping> In outbound services, the dispatch plan generation unit 23 obtains the optimal combination of one or more vehicles that minimizes the dispatch cost of one or more vehicles from a combination of one or more vehicles, a predetermined boarding location, multiple disembarking locations, and the order in which passengers disembark. In outbound services, one or more vehicles depart from a common boarding location, where they simultaneously board passengers. The dispatch plan generation unit 23 obtains the optimal combination of the order in which each passenger disembarks, passing through each passenger's disembarking location from the departing location. Using the obtained optimal combination of disembarking order, the dispatch plan generation unit 23 generates a dispatch plan that includes the order in which each passenger disembarks.

[0071] <1.3. Pick-up service> In the pick-up service, the dispatch plan generation unit 23 obtains the optimal combination of combinations of boarding order, consisting of one or more vehicle current locations, multiple boarding locations, predetermined disembarking locations, and the boarding order of passengers, which minimizes the dispatch cost for one or more vehicles. In the pick-up service, one or more vehicles have a common disembarking location as their final destination, and board each passenger at their respective boarding locations before simultaneously disembarking them at the final destination. The dispatch plan generation unit 23 obtains the optimal combination of boarding order for each passenger when traveling from the vehicle's current location as the starting point, via each passenger's boarding location, to the final destination. Using the obtained optimal combination of boarding order, the dispatch plan generation unit 23 generates a dispatch plan that includes the boarding order for each passenger.

[0072] <1.4. Mixed-use flights> In mixed-use routes, the dispatch plan generation unit 23 obtains the optimal combination of arrival sequences from a combination of the current location of one or more vehicles, multiple boarding and alighting locations, and the order of arrival at the boarding and alighting locations, which minimizes the dispatch cost of one or more vehicles. In mixed-use routes, one or more vehicles board passengers in order at each passenger's boarding location and alight passengers in order at each passenger's alighting location. The dispatch plan generation unit 23 obtains the optimal combination of arrival sequences for each passenger's boarding and alighting location when the vehicle departs from its current location and passes through each passenger's boarding and alighting location. Using the obtained optimal combination of arrival sequences, the dispatch plan generation unit 23 generates a dispatch plan that includes the order of arrival at each passenger's boarding and alighting location.

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

[0074] In the classification method shown in Figure 5(a), passenger groups are divided into passenger groups G1, G2, and G3 based on the desired pick-up and drop-off times included in the ride-hailing reservation information. According to the classification method in Figure 5(a), by grouping passengers with similar desired pick-up times for outbound services and similar desired drop-off times for pick-up services, it is possible to pick up or drop off a group of passengers at times that align with their preferences, thereby relatively reducing the dispatch cost for one or more vehicles 4. Here, the location coordinates indicate the coordinates of the pick-up and / or drop-off locations included in the ride-hailing reservation information.

[0075] In the classification method shown in Figure 5(b), passenger groups are divided into passenger groups G4, G5, and G6 based on the pick-up and / or drop-off locations included in the ride-hailing reservation information. The graph in Figure 5(b) has two axes: the horizontal axis represents the position coordinate X (longitude, etc.), and the vertical axis represents the position coordinate Y (latitude, etc.). By grouping passengers whose pick-up and drop-off locations are geographically close, passengers can be picked up and dropped off in a concentrated manner, and along with the efficiency of ride-sharing, the dispatch cost for one or more vehicles 4 can be made relatively small.

[0076] In the classification method shown in Figure 5(c), passenger groups are divided into passenger groups G7, G8, and G9 based on the desired pick-up or drop-off time and pick-up and / or drop-off location included in the ride-hailing reservation information. The graph in Figure 5(c) has three axes: the X axis represents the position coordinate X (longitude, etc.), the Y axis represents the position coordinate Y (latitude, etc.), and the Z axis represents time t (desired pick-up or drop-off time). By grouping passengers with similar desired pick-up times and nearby pick-up locations, passengers can be picked up intensively, improving the efficiency of ride-sharing and relatively reducing the dispatch cost of one or more vehicles 4. Similarly, by grouping passengers with nearby drop-off locations and similar desired drop-off times, passengers can be dropped off intensively, improving the efficiency of ride-sharing and relatively reducing the dispatch cost of one or more vehicles 4.

[0077] The group generation unit 22 is configured at the discretion of the ride-hailing service provider, etc., regarding whether to adopt a classification method for desired ride times and / or location coordinates (including pick-up and drop-off locations).

[0078] In one embodiment, the group generation unit 22 first classifies multiple passengers into passenger groups based on the location coordinates included in the ride reservation information. Next, the group generation unit 22 further classifies the previously classified passenger groups into more detailed passenger groups based on the desired boarding time included in the ride reservation information. By grouping passengers by disembarking or boarding location and then further grouping them by desired boarding time, accurate passenger groups can be generated. Alternatively, a procedure may be adopted in which passengers are initially grouped by desired boarding time and then further grouped based on disembarking or boarding location.

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

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

[0081] The group generation unit 22 assigns one or more vehicles 4 to a passenger group based on multiple ride reservation information and one or more vehicle information. The group generation unit 22 assigns a vehicle 4 to the passenger group that is the closest in distance to the pick-up location included in the ride reservation information, based on the current location of the vehicle included in the vehicle information. The group generation unit 22 also assigns one or more vehicles 4 such that the sum of the vehicle capacities included in one or more vehicle information is equal to or greater than the number of passengers in the passenger group. For example, if the passenger group has 6 people, two or more vehicles 4 with a capacity of 3 people each will be assigned.

[0082] The group generation unit 22 may classify multiple vehicles into one or more vehicle groups based on the vehicle departure times and / or location coordinates (current vehicle location) included in the vehicle information of multiple vehicles. The method for classifying vehicle groups can be the same as the method for classifying passenger groups. The group generation unit 22 assigns vehicle groups to passenger groups based on the desired boarding time, the vehicle departure time, and the location coordinates of the passengers and vehicles. Specifically, the group generation unit 22 refers to the desired boarding time of the passenger groups and the vehicle departure time of the vehicle groups and assigns vehicle groups to passenger groups that are close in time. In addition, 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 concentrates passengers on the vehicles.

[0083] The group generation unit 22 calculates the passenger capacity of each assigned vehicle 4 and the sum of the passenger capacities of all those vehicles 4, and stores this passenger capacity information linked to the dispatch plan.

[0084] The group generation unit 22 calculates the number of passengers at each boarding location and stores this information as passenger count information for each boarding location, linked to the dispatch plan. The passenger count information is calculated based on the number of passengers included in the dispatch reservation information. Alternatively, the passenger count information may be calculated by summing the number of passengers from different 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 from 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 at the same or relatively close pick-up location (e.g., a different terminal), they can receive a ride-hailing service with short waiting times by efficiently allocating a limited number of vehicles 4. In addition, if the airline pays for the ride-hailing service for airport employees, the cost can be reduced.

[0086] <1.6. Dispatch Plan Generation Unit> The dispatch plan generation unit 23 generates a dispatch plan based on the passenger's dispatch reservation information. If the passengers have been classified into passenger groups by the group generation unit 22, the dispatch plan generation unit 23 can generate a dispatch plan based on the dispatch reservation information of the passengers classified into those passenger groups.

[0087] The dispatch plan generation unit 23 employs a configuration that calculates the order of arrival at each destination, including the passengers' boarding and alighting locations, for mixed-use services. The dispatch plan generation unit 23 can also employ a configuration that calculates the boarding order of each passenger when traveling to a predetermined destination point, passing through each passenger's respective boarding locations, for pick-up services. Furthermore, the dispatch plan generation unit 23 can also employ a configuration that calculates the alighting order of each passenger when traveling from a predetermined departure point to each passenger's respective alighting location, for drop-off services.

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

[0089] <1.7. Map Information> The map information storage unit DB2 stores map information. This map information includes road data and location coordinates and is used to confirm vehicle routes and destinations. In this embodiment, the map information storage unit DB2 stores the pre-calculated cost between two points, associating it with the map information. The route distance and route time represent not the straight-line distance between the two points, but rather the distance and time taken when traveling along a realistic route following the road data.

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

[0091] Map information may be dynamically linked to road congestion status in conjunction with a road information system. Road congestion status refers to congestion caused by events such as traffic jams and disasters, which is associated with road data. By reflecting road congestion status in the road data of map information, the travel time when using that road as a route will change. For example, on roads where congestion occurs, the travel time for that route will be set to be longer, so by obtaining the travel time and generating a dispatch plan that takes travel time into account, dispatch costs can be minimized.

[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 alighting order derived as a combinatorially optimal solution.

[0093] Furthermore, the output unit 24 can derive and provide a travel route that reflects the boarding order and / or alighting order in the map information. The travel route is information indicating which roads on the map the vehicle will travel on. The output unit 24 can also derive and provide the arrival time for each passenger at their boarding and alighting locations. Some of these functions of the output unit 24 may be performed by the passenger terminal 3 or the vehicle terminal 5.

[0094] Figure 6 shows an example of the screen display provided by the output unit 24. Note that Figure 6 is an example of the screen display on the vehicle terminal 5. Figure 6(a) shows an example of the display of the travel route screen W10, which reflects the order of arrival at the destination (boarding order or alighting order) on the map. Figure 6(a) illustrates the pick-up and drop-off of passengers A to C by vehicle C1. The current location of vehicle C1 and the boarding and alighting locations of passengers A to C are displayed on the map by pins. 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 alighting locations are indicated by alighting location pins E1 to E3. The travel route by vehicle C1 to each of the boarding and alighting locations of passengers A to C is displayed on the map as the travel route display R1.

[0095] Figure 6(b) shows an example of the display of the dispatch plan screen W20, which is displayed as a pop-up by the menu button on the route screen W10. The dispatch plan screen W20 comprises a vehicle information area W21, a dispatch reservation information area W22, and a dispatch plan area W23. The vehicle information area W21 displays vehicle information, including the current location and passenger capacity of one or more vehicles to be dispatched, and detailed information can be displayed for a specific vehicle selected from among them in the dispatch reservation information area W22 and the dispatch plan area W23. The dispatch reservation information area W22 displays dispatch reservation information, including the boarding locations, alighting locations, and number of passengers for multiple passengers A to C.

[0096] The dispatch planning area W23 displays the dispatch plan, including the boarding and alighting order. In Figure 6(b), the dispatch planning area W23 displays the boarding order and alighting order of passengers A to C in a chart. The dispatch planning area W23 also displays the travel distance and travel time for that dispatch plan. Figure 6(b) shows an example where the travel distance and travel time for all routes are displayed, but the system may also be configured to display the route distance and route time for each passenger's boarding and alighting location.

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

[0098] The passenger terminal 3 obtains a dispatch plan related to at least the passenger from the dispatch device 2, generates a display of the dispatch plan screen, and displays it on a display unit such as a monitor. Based on the vehicle information, dispatch reservation information, and dispatch plan, the passenger terminal 3 generates a display of a route screen related to at least the passenger, and displays it on a display unit. For example, the dispatch plan screen for passenger A displays the arrival time, distance traveled, and travel time for passenger A's boarding and alighting locations, respectively. The route screen for passenger A displays the route R1 from boarding location pin S1 to alighting location pin E1, which is passenger A's route. The dispatch device 2 may generate the route screens and dispatch plan screens for each passenger.

[0099] <2.1. Embodiment 1> Figure 7 shows a flowchart related to the vehicle dispatch process. The group registration unit 20 accepts registration of a synergistic group (S101). First, the group registration unit 20 receives a registration instruction for a synergistic group from the administrator's terminal device and registers the 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 administrator's terminal device, and the group registration unit 20 may be configured to execute a process to associate the passenger information with the synergistic group information if approved.

[0100] The acquisition unit 21 acquires various types of information (S102). The acquisition unit 21 acquires dispatch reservation information for multiple passengers from multiple passenger terminals 3. The acquisition unit 21 also acquires vehicle information for multiple vehicles from one or more vehicle terminals 5. The vehicle terminal 5 can transmit vehicle information along with a command to authorize acceptance of the dispatch reservation.

[0101] The dispatch plan generation unit 23 generates a dispatch plan (S103) based on the pick-up and drop-off locations included in the multiple pick-up reservation information, such that the dispatch cost for one or more vehicles is minimized. The dispatch plan generation unit 23 also generates a dispatch plan (S103) based on the pick-up and drop-off locations included in the multiple pick-up reservation information, such that only passengers approved for ride-sharing by the ride-sharing group information are able to ride together. It is preferable that the dispatch plan generation unit 23 generates a dispatch plan (S103) such that the dispatch cost for one or more vehicles is minimized, and only passengers approved for ride-sharing by the ride-sharing group information are able to ride together. The dispatch plan generation unit 23 can generate a dispatch plan (S103) including the drop-off order based on the drop-off locations in the multiple pick-up reservation information and the current vehicle locations in the one or more vehicle information. The dispatch plan generation unit 23 can also generate a dispatch plan (S103) including the boarding order based on the pick-up locations in the multiple pick-up reservation information and the current vehicle locations in the one or more vehicle information.

[0102] Dispatch costs are any costs that can be made more efficient in the ride-hailing service. Dispatch costs are, for example, distance traveled, and the dispatch plan generation unit 23 derives the optimal combination of the order in which vehicles should travel to multiple destinations in order to minimize the distance traveled by one or more vehicles 4. The following describes an example where the dispatch cost is distance traveled.

[0103] In one embodiment, the dispatch plan generation unit 23 can generate a dispatch plan based on a predetermined pick-up location in the ride-sharing group information and a drop-off locations included in multiple dispatch reservation information.

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

[0105] Furthermore, if it is not necessary to generate a dispatch plan so that only passengers approved for ride-sharing based on ride-sharing group information are able to ride together, the processing in the group registration unit 20 of S101 can be omitted.

[0106] <2.2. Example 1> In Figure 4(a), the processing of the dispatch plan generation unit 23 when dispatching vehicle C1 to passengers A to C will be explained using Example 1 as an example. Example 1 illustrates the processing when there is no registered group of passengers, or when all passengers belong to the same group of passengers. The vehicle capacity is 3, and the number of vehicles is 1.

[0107] The acquisition unit 21 acquires the boarding location and / or alighting location included in the vehicle reservation information for passengers A to C. In Example 1, the boarding location (departure point) for passengers A to C is the same location Ps, and their alighting locations are locations Pa to Pc.

[0108] The dispatch plan generation unit 23 generates location information based on the acquired pick-up and / or drop-off locations. The location information is information that shows the cost between all locations that are subject to optimization. In this embodiment, the dispatch plan generation unit 23 generates first location information (Figure 8(a)) that shows the first distance between locations disS2P from the departure location Ps to each drop-off location Pa to Pc, and second location information (Figure 8(b)) that shows the second distance between locations disP2P between each drop-off location Pa to Pc.

[0109] The dispatch plan generation unit 23 inputs the input data, including the location information shown in Figure 8, into the QUBO formula and generates a QUBO matrix. Figure 9 shows an example of the QUBO matrix generated in Example 1. In Figure 9, each row and column represents the variable x[v,t,i]. In Figure 9, the matrix disS2P is generated by the first location information disS2P term in formula (2), and the matrix disP2P is generated by the second location information disP2P term in formula (2). Each element of the QUBO matrix represents energy. In the matrix disP2P, the row is the t-th destination (drop-off point) of the vehicle v under consideration, and the column is the t+1-th destination (drop-off point) of the vehicle v, and its value represents the dispatch cost between the two points. For example, row x[1,1,B] and column x[1,2,A] show that when the vehicle arrives at passenger B's disembarkation point Pb first, and then passenger A's disembarkation point Pa next (second), the dispatch cost between those points is 16. Note that if the QUBO matrix is ​​a symmetric matrix, the value in the lower left of the diagonal can be omitted when inputting into the QUBO solver. In the QUBO matrix in Figure 9, the value in the lower left of the diagonal has been omitted.

[0110] Figure 10(a) illustrates the result of running the QUBO matrix from Figure 9 using the QUBO solver 6. In Figure 10(a), passenger i indicates the disembarkation point of the (t-1)th passenger in the previous disembarkation order, and passenger j indicates the disembarkation point of the (t)th passenger in the next disembarkation order. For example, in disembarkation order t=2, it is shown that the energy from the disembarkation point Pb of the previous passenger B to the disembarkation point Pa of the next passenger A is 16. Figure 10(b) shows an overview of the optimized dispatch plan. Based on these, it is understood that in Example 1, dispatch costs can be minimized (total energy 35) by having vehicle C1 travel in the order of points Ps, Pb, Pa, Pc. However, since Example 1 does not assume a carpooling group, there are challenges such as the risk of trouble between passengers and the unclear location of contractual responsibility regarding carpooling services between passengers and crew.

[0111] <2.3. Example 2> In Figure 4(a), the processing of the dispatch plan generation unit 23 when vehicle C1 is dispatched to passengers A and C, and passengers A and C belong to syndicate group G1, and passenger B belongs to syndicate group G2 will be explained as Example 2. It is assumed that no ride-sharing approval has been granted between syndicate groups G1 and G2.

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

[0113] The group registration unit 20 receives a designation of a group, such as an SNS, from the administrator's terminal device and accepts a registration instruction to register the group as synergistic group information. The passenger terminal 3 sends a request to join the group. The administrator's terminal device approves the request and notifies the passenger terminal 3 of passenger information, including the passenger ID. The passenger terminal 3 can make a ride reservation within the joined group by entering the ride reservation information using the passenger ID and sending it to the ride reservation device 2. The group registration unit 20 may also issue passenger IDs to existing participants of a group, such as an SNS, by registering the group as synergistic group information.

[0114] The administrator's terminal device can access billing data for fares incurred by passengers in the carpooling group using the ride-hailing service. This billing data is issued by the vehicle terminal 5 or the vehicle management company. The dispatch device 2 can calculate the individual fares for each passenger based on the billing data and generate individual passenger billing data. This allows the administrator to consolidate and pay for ride-hailing services within the carpooling group. Furthermore, the administrator can bill individual passengers.

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

[0116] In Example 2, the constraint is set that synergy must be approved between the synergy groups. This constraint is set as a constraint term in the objective function H(x) in equation (1). Equation (3) shows the constraint term relating to the constraint that only passengers who are approved to synergy based on synergy group information can ride together. Here, the approval relationship is paG2paGDsb iThis shows a list of passengers who have agreed to share a ride with each other.

[0117]

number

[0118] The left-hand term in equation (3) is a value that indicates whether or not passenger i boards vehicle v at a given arrival order (boarding order or alighting order) t. If this term is 1 or greater, it indicates that passenger i will board vehicle v at arrival order (boarding order or alighting order) t, and if it is 0, it indicates that passenger i will not board vehicle v at arrival order (boarding order or alighting order) t. Figure 12(a) is an overview diagram of this term. The value of this term is 1 or greater when at least one of passengers A to C is on board at a given arrival order (alighting order) t. Note that Example 2 is an example of a delivery service, so all combinations of passengers A to C boarding from 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 boarding the vehicle v on which passenger i is riding. If this term is 1 or greater, it indicates that the constraint is not met, i.e., passengers who do not approve of carpooling will carpool with each other. If it is 0, it indicates that the constraint is met, i.e., passengers who approve of carpooling will carpool with each other. Figure 12(b) shows the information on which passengers cannot carpool with each other under this constraint. In Example 2, passenger B belongs to carpooling group G1, which includes passengers A and C, and carpooling group G2, which does not approve of carpooling, and therefore carpooling with passengers A and C is not approved. The dispatch plan generation unit 23 generates the information on which passengers cannot carpool with each other shown in Figure 12(b) using the information shown in Figures 11(c) and (d).

[0120] The dispatch plan generation unit 23 inputs the location information from Figure 11 and the non-synergistic information from Figure 12 into the QUBO equation and generates a QUBO matrix. Figure 13 shows an example of a QUBO matrix relating to the constraint term in equation (3). For the sake of simplicity, the QUBO matrices relating to the objective term and other constraint terms are omitted in Figure 13. According to Figure 13, the element representing the rotation between passenger B and passengers A and C has an energy of 2, and the element representing the rotation between passenger A and passenger C has an energy of 0. When this QUBO matrix is ​​optimized by the QUBO solver 6, the combination with the minimum energy is derived as the optimal solution, thus excluding the combination in which passenger B and passengers A and C, who cannot be synergistically combined, ride together from the optimal solution.

[0121] Figure 14(a) illustrates the execution result by the QUBO solver 6 of the QUBO matrix, which includes the matrix related to the objective term in Figure 9 and the matrix related to the constraint term in Figure 13. Figure 14(b) shows an overview of the dispatch plan optimized so that only passengers who approve of carpooling travel together. According to these, in Example 2, the dispatch cost is minimized (total energy 23) and the condition that only passengers who approve of carpooling travel together is met by having vehicle C1 travel in the order of points Ps, Pc, and Pa. Passenger B can be picked up or dropped off by vehicle C2, or by vehicle C1 before or after picking up passengers A and C. In Example 2, it is preferable for the dispatch plan generation unit 23 to adopt the solution that picks up the most passengers as the combinatorially optimal solution, and constraint terms may be set for this. Thus, in Example 2, a carpooling group is assumed, so the dispatch plan is different from that of Example 1.

[0122] <2.4. Example 3> In Figure 4(b), the processing of the dispatch plan generation unit 23 when vehicles C1 and C2 are dispatched to passengers A to D, and passengers A and C belong to synergy group G1, passenger B belongs to synergy group G2, and passenger D belongs to synergy group G3 will be explained as Example 3. It is assumed that ride-sharing is not approved between synergy groups G1 and G3 and between synergy group G2, but ride-sharing is approved between synergy groups G1 and G3.

[0123] The acquisition unit 21 acquires ride reservation information, passenger information, and ride-sharing group information for passengers A to D. The ride-sharing plan generation unit 23 generates first location information (Figure 15(a)) and second location information (Figure 15(b)) based on the pick-up and / or drop-off locations included in the ride reservation information. The ride-sharing plan generation unit 23 also extracts ride-sharing groups included in the passenger information (Figure 15(c)). The ride-sharing plan generation unit 23 also extracts the ride-sharing approval relationships between the extracted ride-sharing groups G1, G2, and G3 by referring to the ride-sharing group information (Figure 15(d)). The ride-sharing plan generation unit 23 also generates ride-sharing non-existence information between passengers based on the information in Figures 15(c) and (d) (Figure 15(e)). According to this, although passenger D belongs to a different synergy group G3 than the synergy group G1 of passengers A and C, ride-sharing with passengers A and C is approved according to the approval relationship of the synergy group information (Figure 15(d)). On the other hand, ride-sharing with passengers A, C, and D is not approved for passenger B.

[0124] In Example 3, the QUBO formula, which includes the constraint term shown in equation (3), is adopted. The vehicle dispatch planning generation unit 23 inputs the location information from Figure 15 and input data including synergistic non-complicating information into the QUBO formula and generates a QUBO matrix. Figure 16 shows an example of a QUBO matrix relating to the objective term of equation (2). Figure 17 shows an example of a QUBO matrix relating to the constraint term of equation (3). In Figures 16 and 17, the elements in the dotted line region represent the energy due to vehicle C1 (variable x[1,t,i]), and the elements in the dashed-dotted line region represent the energy due to vehicle C2 (variable x[2,t,i]).

[0125] Figure 18(a) illustrates the result of running the QUBO matrix, which includes the matrices in Figures 16 and 17, using the QUBO solver 6. Figure 18(b) shows an overview of a dispatch plan optimized so that only passengers who approve of ride-sharing can ride together, using vehicles C1 and C2. In Figure 18(b), the solid line shows the route of vehicle C1, and the dashed line shows the route of vehicle C2.

[0126] According to these findings, in Example 3, vehicle C1 travels to points Ps, Pc, Pa, and Pd in ​​that order, and vehicle C2 travels to points Ps and Pb in that order, thereby minimizing dispatch costs (total energy 53) and satisfying the condition that only passengers who have approved carpooling can carpool. Here, minimizing dispatch costs means minimizing the total energy of the dispatch costs for vehicle C1 and vehicle C2. Similarly, even if the number of vehicles increases further, an efficient dispatch plan can be generated by minimizing the total energy of the dispatch costs for all vehicles. Thus, in Example 3, an efficient dispatch plan can be generated even when the number of vehicles increases or when carpooling is approved among carpooling groups.

[0127] <2.5. Variant Example> A modified example of generating a ride-hailing plan for a synergistic group without using the constraint term in equation (3) will be described. The ride-hailing plan generation unit 23 generates input data for a combinatorial model using the pick-up and / or drop-off locations included in the ride reservation information of multiple passengers whose synergy is approved by the synergistic 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 whose synergy is approved. The ride-hailing plan generation unit 23 applies this variable x[v,t,i] to an objective function defined so as to minimize the ride-hailing cost of one or more vehicles, thereby obtaining a combinatorially optimal solution in which only passengers whose synergy is approved by the synergistic group information synergize, and the ride-hailing cost is minimized. The ride-hailing plan generation unit 23 generates a ride-hailing plan using this combinatorially optimal solution. The modified example has now been described.

[0128] According to Embodiment 1, it is possible to generate an optimal ride-sharing plan that satisfies the condition that only passengers who have been approved to ride together can ride together. Embodiments 1 to 3 using equation (3) can generate an optimal ride-sharing plan that includes multiple passengers belonging to different ride-sharing groups, which cannot be calculated in the modified example. In the modified example, the computational load on the combinatorial model and combinatorial optimization engine can be reduced by extracting passengers who have been approved to ride together in advance.

[0129] <3.1. Embodiment 2> Figure 19 shows a flowchart relating to the dispatch process according to Embodiment 2. In Embodiment 2, when there is a large amount of dispatch reservation information from multiple passengers, a configuration is adopted in which passenger groups are generated in advance, and then a combinatorially optimal solution is obtained for each of these passenger groups. This reduces the computational load related to the combinatorial optimization problem.

[0130] The group registration unit 20 accepts registration of a synergistic group (S201). First, the group registration unit 20 receives a registration instruction for a synergistic group from the administrator's terminal device and registers the 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 is approved by an approval operation from the administrator's terminal device, and the group registration unit 20 may be configured to execute a process to associate the passenger information with the synergistic group information if approved.

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

[0132] The group generation unit 22 classifies multiple passengers into one or more passenger groups based on multiple ride reservation information (S203). Here, the group generation unit 22 classifies passengers into passenger groups based on the desired pick-up time and / or drop-off location included in the ride reservation information. The group generation unit 22 assigns one or more vehicles to each passenger group based on the multiple ride reservation information and one or more vehicle information.

[0133] The dispatch plan generation unit 23 generates a dispatch plan for each passenger group so as to minimize the dispatch cost of one or more vehicles (S204). The dispatch plan generation unit 23 generates a dispatch plan including the order of disembarkation based on the disembarkation locations of multiple dispatch reservation information included in the passenger group and the current location of one or more vehicle information. The dispatch plan generation unit 23 also generates a dispatch plan including the order of boarding based on the boarding locations of multiple dispatch reservation information included in the passenger group and the current location of one or more vehicle information. The dispatch plan generation unit 23 obtains the combinatorially optimal solution that minimizes the dispatch cost by calculation using the QUBO solver 6 or by mathematical calculation. In Embodiment 2, since the size of the combinatorial problem is reduced by determining the passenger groups, the method is not limited to deriving the combinatorially optimal solution by calculation using the QUBO solver 6.

[0134] The output unit 24 provides the generated dispatch plan to the vehicle terminal 5 (S205). The vehicle terminal 5 receives the dispatch plan and displays it on the display unit based on the dispatch plan.

[0135] As described above, in Embodiment 2, by generating passenger groups, the computational load on the combinatorial optimization engine can be reduced and computation time can be shortened, enabling the efficient provision of vehicle dispatch plans. For example, even when quantum annealing or simulated annealing (including pseudo-quantum annealing) shown in Table 1 is adopted as the solver, it is possible to deal with situations such as the problem being very large in scale. In addition, when an exact solution is required for small to medium-sized problems, a typical solution method or a general-purpose solution method can be adopted as the solver. [Explanation of Symbols]

[0136] 1. Dispatch System 2. Dispatch system 20 Group Registration Department 21 Acquisition Department 22 Group Generation Unit 23. Vehicle Dispatch Planning Department 24 Output section 3. Passenger terminals 4 vehicles 5. Vehicle terminals 6 QUBO solver DB storage DB1 Vehicle dispatch information storage unit DB2 Map Information Storage Unit NW (Network Communication Network)

Claims

1. A dispatch system that provides a vehicle dispatch plan for multiple passengers sharing a vehicle, A group registration unit that registers synergy group information defining the relationships between multiple passengers who approve synergy, An acquisition unit that acquires multiple passenger dispatch reservation information, including boarding and / or alighting locations, and vehicle information for one or more vehicles. The system includes a dispatch plan generation unit that uses a combination model to derive a combinatorially optimal solution based on the pick-up and / or drop-off locations included in multiple dispatch reservation information, such that the dispatch cost for one or more vehicles is minimized and only passengers approved for synchronizing according to the synchronizing group information are able to synchronize, and generates a dispatch plan based on the combinatorially optimal solution, The aforementioned combinatorial model includes an objective function consisting of constraints and objectives, wherein the constraints include at least the condition that a single passenger arrives in only one vehicle out of one or more vehicles, and the condition that the number of vehicles does not exceed the vehicle capacity, and the objective is to minimize the dispatch cost, which includes at least one selected from distance traveled, travel time, passenger fare, vehicle return time, and number of vehicles, and defines variables including one or more vehicles, multiple pick-up and / or drop-off locations included in multiple pick-up reservation information, and the order of arrival at said pick-up and / or drop-off locations. A dispatch system in which the dispatch plan generation unit generates the dispatch plan based on the combinatorially optimal solution that satisfies the constraint conditions imposed by the constraint term of the objective function and minimizes the dispatch cost derived from the objective term of the objective function.

2. The dispatch system according to claim 1, wherein the dispatch plan generation unit obtains an optimal combination of arrival order from among combinations of one or more vehicles, the boarding locations and / or alighting locations of multiple passengers whose ride-sharing is approved by the ride-sharing group information, and the order in which they arrive at the boarding locations and / or alighting locations, such that the dispatch cost of one or more of the vehicles is minimized.

3. The combination model is defined as a constraint term which further includes a constraint condition that only passengers approved for synergy by the synergy group information can synergize, The dispatch system according to claim 1, wherein the dispatch plan generation unit obtains an optimal combination of arrival order, which is a combination of one or more vehicles, the boarding locations and / or alighting locations of multiple passengers, and the order of arrival at the boarding locations and / or alighting locations, such that the condition is met that only passengers approved for carpooling by the carpooling group information carpool together, and the dispatch cost of one or more vehicles is minimized.

4. The acquisition unit acquires vehicle information for one or more vehicles, including the number of passengers and the current location of the vehicle. The dispatch system according to claim 1, wherein the dispatch plan generation unit generates the dispatch plan based on the pick-up and / or drop-off locations of a plurality of dispatch reservation information and the current location of one or more vehicle information.

5. The combination model is defined as the constraint term, which further includes the condition that the arrival order is sequential starting from 1, The dispatch system according to claim 1, wherein the dispatch plan generation unit obtains a combination optimal solution that satisfies the constraints shown in the constraint clause, which includes at least the condition that the arrival order be sequential starting from 1, the condition that a single passenger has an arrival order for only one vehicle out of one or more vehicles, and the condition that the number of vehicles does not exceed the vehicle capacity.

6. The dispatch system according to claim 1, wherein the dispatch plan generation unit obtains an optimal combination from among combinations of disembarking order, consisting of one or more vehicles, predetermined boarding locations, multiple disembarking locations, and the order in which passengers disembark, the combination that minimizes the dispatch cost of one or more of the vehicles.

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

8. The acquisition unit acquires vehicle reservation information for multiple passengers, including their desired boarding or alighting times. The system includes a group generation unit that classifies multiple passengers into one or more passenger groups based on at least one of the following: desired pick-up time, desired drop-off time, pick-up location, and drop-off location included in multiple ride-hailing reservation information. The dispatch system according to claim 1, wherein the dispatch plan generation unit generates a dispatch plan for each of the passenger groups so as to minimize the dispatch cost of one or more vehicles.

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

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

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

12. It includes a map information storage unit that stores the result of pre-calculating the route distance or route time between two points in association with map information, The dispatch system according to claim 1, wherein the dispatch plan generation unit generates the dispatch plan using the route distance or route time obtained from the map information storage unit for the dispatch cost between a plurality of acquired pick-up locations and / or drop-off locations.

13. The dispatch system according to any one of claims 1 to 12, wherein the dispatch plan generation unit makes a request to a combinatorial optimization engine to process a combinatorial optimization problem that defines the variables of each element relating to the combination of arrival order, and obtains a combinatorial optimal solution from the combinatorial optimization engine.

14. A dispatch system that provides a vehicle dispatch plan for multiple passengers sharing a vehicle, An acquisition unit that acquires multiple passenger dispatch reservation information, including boarding and / or alighting locations, and vehicle information for one or more vehicles, including the vehicle's current location. The system comprises: a system that makes a processing request to a combinatorial optimization engine for a combinatorial model that defines variables including one or more vehicles, multiple pick-up and / or drop-off locations included in multiple pick-up reservation information, and the order of arrival at the pick-up and / or drop-off locations; a system that obtains a combinatorial optimal solution from the combinatorial optimization engine that minimizes the pick-up cost of one or more vehicles; and a system that generates a pick-up plan based on the combinatorial optimal solution. The aforementioned combinatorial model includes an objective function consisting of constraint terms and objective terms, wherein the constraint terms include at least the condition that a single passenger arrives in only one vehicle out of one or more vehicles, and the condition that the number of vehicles does not exceed the vehicle capacity, and the objective term is to minimize the dispatch cost which includes at least one of the following: distance traveled, travel time, passenger fare, vehicle return time, and number of vehicles. A dispatch system in which the dispatch plan generation unit generates a dispatch plan based on the combinatorially optimal solution that satisfies the constraint conditions imposed by the constraint term of the objective function and minimizes the dispatch cost derived from the objective term of the objective function.

15. A dispatch method that provides a dispatch plan for vehicles carrying multiple passengers, Register synergy group information that defines the relationships between multiple passengers who approve synergy, The system obtains ride reservation information for multiple passengers, including their boarding and alighting locations, and vehicle information for one or more vehicles. Based on the pick-up and drop-off locations included in multiple ride-hailing reservation information, the computer derives a combinatorially optimal solution using a combinatorial model so that the dispatch cost for one or more vehicles is minimized and only passengers approved for synchronizing according to the synchronizing group information are included in the synchronizing group. The computer then executes a process to generate a ride-hailing plan based on this combinatorially optimal solution. The aforementioned combinatorial model includes an objective function consisting of constraints and objectives, wherein the constraints include at least the condition that a single passenger arrives in only one vehicle out of one or more vehicles, and the condition that the number of vehicles does not exceed the vehicle capacity, and the objective is to minimize the dispatch cost, which includes at least one selected from distance traveled, travel time, passenger fare, vehicle return time, and number of vehicles, and defines variables including one or more vehicles, multiple pick-up and / or drop-off locations included in multiple pick-up reservation information, and the order of arrival at said pick-up and / or drop-off locations. A vehicle dispatch method for generating a vehicle dispatch plan based on the combinatorially optimal solution that satisfies the constraint conditions imposed by the constraint term of the objective function and minimizes the vehicle dispatch cost derived from the objective term of the objective function.

16. A ride-hailing program that provides a ride-hailing plan for vehicles shared by multiple passengers, A group registration unit that registers synergy group information defining the relationships between multiple passengers who approve synergy, An acquisition unit that acquires dispatch reservation information for multiple passengers, including boarding and alighting locations, and vehicle information for one or more vehicles. A computer functions as a dispatch plan generation unit, which derives a combinatorially optimal solution using a combinatorial model based on the pick-up and drop-off locations included in multiple dispatch reservation information, such that the dispatch cost for one or more vehicles is minimized and only passengers approved for synchronizing according to the synchronizing group information are included in the synchronizing, and generates a dispatch plan based on that combinatorially optimal solution. The aforementioned combinatorial model includes an objective function consisting of constraints and objectives, wherein the constraints include at least the condition that a single passenger arrives in only one vehicle out of one or more vehicles, and the condition that the number of vehicles does not exceed the vehicle capacity, and the objective is to minimize the dispatch cost, which includes at least one selected from distance traveled, travel time, passenger fare, vehicle return time, and number of vehicles, and defines variables including one or more vehicles, multiple pick-up and / or drop-off locations included in multiple pick-up reservation information, and the order of arrival at said pick-up and / or drop-off locations. The dispatch plan generation unit generates the dispatch plan based on the combinatorially optimal solution that satisfies the constraints imposed by the constraint term of the objective function and minimizes the dispatch cost derived from the objective term of the objective function.

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