Vehicle management system, vehicle management method, and program

Abstract

To increase arithmetic processing speed.SOLUTION: A vehicle management system includes: information acquisition means for acquiring information on positions of vehicle storage locations where a shared vehicle is stored, a travel cost when driving the shared vehicle between the vehicle storage locations, a departure point and a destination point of a user who uses the shared vehicle, and a travel cost for the user to travel to the vehicle storage location; optimization problem construction means for constructing a first optimization problem based on the information acquired by the information acquisition means, and constructing a second optimization problem obtained by converting inequality constraints in the constructed first optimization problem into equality constraints and by continuously relaxing variables in the equation; and algorithm calculation means for calculating Lagrangian multipliers based on the second optimization problem constructed by the optimization problem construction means, and calculating a solution to the second optimization problem based on the calculated Lagrangian multipliers.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a vehicle management system, a vehicle management method, and a program. [Background technology]

[0002] A system is known that promotes the movement of shared vehicles from stations where there is an excess of shared vehicles to stations where there is a shortage of shared vehicles in order to eliminate uneven distribution of shared vehicles (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-245585 Summary of the Invention [Problem to be solved by the invention]

[0004] In the above system, as the number of users, shared vehicles, and stations increases, the number of combinations becomes enormous, which can cause a problem of a decrease in the speed of the calculation process.

[0005] The present disclosure has been made to solve such problems, and its main purpose is to provide a vehicle management system, a vehicle management method, and a program that can increase the calculation processing speed. [Means for solving the problem]

[0006] In order to achieve the above object, one aspect of the present disclosure is to an information acquisition means for acquiring information on the location of vehicle storage locations where shared vehicles are stored, travel costs when the shared vehicles move between the vehicle storage locations, departure points and destinations of users who use the shared vehicles, and travel costs for users to travel to the vehicle storage locations; an optimization problem constructing means for constructing a first optimization problem based on the information acquired by the information acquiring means, and for constructing a second optimization problem by converting inequality constraints in the constructed first optimization problem into equality constraints and continuously relaxing variables in the equations; an algorithm calculation means for calculating a Lagrangian multiplier based on the second optimization problem constructed by the optimization problem construction means, and for calculating a solution to the second optimization problem based on the calculated Lagrangian multiplier; Equipped with Vehicle Management System is. In this aspect, The algorithm calculation means may repeat updating the Lagrangian multiplier and calculating the solution to the second optimization problem until a constraint of the second optimization problem is satisfied. In order to achieve the above object, one aspect of the present disclosure is to A step of acquiring information regarding the location of a vehicle storage location where a shared vehicle is stored, a travel cost when the shared vehicle moves between the vehicle storage locations, a departure point and a destination of a user who uses the shared vehicle, and a travel cost for the user to travel to the vehicle storage location; constructing a first optimization problem based on the acquired information, and constructing a second optimization problem by converting inequality constraints in the constructed first optimization problem into equality constraints and continuously relaxing variables in the equation; calculating a Lagrangian multiplier based on the constructed second optimization problem, and calculating a solution to the second optimization problem based on the calculated Lagrangian multiplier; Including, Vehicle management method is. In order to achieve the above object, one aspect of the present disclosure is to A process of acquiring information on the location of vehicle storage locations where shared vehicles are stored, the travel costs when the shared vehicles move between the vehicle storage locations, the departure points and destinations of users who use the shared vehicles, and the travel costs for users to travel to the vehicle storage locations; constructing a first optimization problem based on the acquired information, and converting the inequality constraints in the constructed first optimization problem into equality constraints and continuously relaxing the variables in the equation to construct a second optimization problem; calculating a Lagrangian multiplier based on the constructed second optimization problem, and calculating a solution to the second optimization problem based on the calculated Lagrangian multiplier; to the computer, program is. [Effects of the Invention]

[0007] According to the present disclosure, it is possible to provide a vehicle management system, a vehicle management method, and a program that can increase the calculation processing speed. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a schematic hardware configuration of a vehicle management system according to an embodiment of the present invention; [Figure 2] 1 is a block diagram showing a schematic system configuration of a vehicle management system according to an embodiment of the present invention; [Figure 3] FIG. 10 is a diagram for explaining a simulation result of the vehicle management system. [Figure 4] FIG. 10 is a diagram showing simulation results of a vehicle management system. [Figure 5] FIG. 10 is a diagram showing simulation results of a vehicle management system. [Figure 6] 3 is a flowchart showing the flow of a vehicle management method according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] This embodiment will be described below with reference to the drawings. For example, one-way car sharing is known, in which a user returns a shared vehicle to a station different from the station from which the user departed. In this one-way car sharing, when there are many stations, shared vehicles, and users, it is necessary to solve an optimization problem that simultaneously considers vehicle allocation between stations and vehicle allocation to users.

[0010] Such optimization problems involve combinations of stations, shared vehicles, and users. Therefore, as the number of combinations increases and the problem scale grows, the calculation time increases exponentially, which can lead to problems such as a decrease in the processing speed.

[0011] In contrast, the vehicle management system according to this embodiment, as described below, constructs an equivalent optimization problem that is easy to handle and obtains the same optimal solution as the optimization problem while eliminating combinatorial elements from the optimization problem to be solved. Furthermore, the vehicle management system according to this embodiment solves this optimization problem using an algorithm based on the Synchorn algorithm, which is known as a fast algorithm. This increases the processing speed, enabling even large-scale optimization problems to be solved quickly.

[0012] 1 is a block diagram showing a schematic hardware configuration of a vehicle management system according to this embodiment. The vehicle management system 1 according to this embodiment has the hardware configuration of a typical computer, including, for example, a processor 11 such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), an internal memory 12 such as a RAM (Random Access Memory) or a ROM (Read Only Memory), a storage device 13 such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive), an input / output I / F 14 for connecting peripheral devices such as a display, and a communication I / F 15 for communicating with devices external to the device.

[0013] 2 is a block diagram showing a schematic system configuration of a vehicle management system according to this embodiment. The vehicle management system 1 according to this embodiment includes an information acquisition unit 2, an optimization problem formulation unit 3, and an algorithm calculation unit 4.

[0014] In this embodiment, for example, a plurality of stations are set up. Each station is provided with at least one vehicle storage area (parking space) for storing shared vehicles. Users rent and board shared vehicles at each vehicle storage area of ​​each station, or disembark and return the vehicles. The shared vehicles stored at each vehicle storage area of ​​each station are moved between stations by a service provider or the like so as to minimize uneven distribution of shared vehicles among the stations.

[0015] The information acquisition unit 2 is a specific example of information acquisition means. The information acquisition unit 2 acquires information on the locations of vehicle storage locations where shared vehicles are stored, travel costs when a shared vehicle moves between vehicle storage locations, departure points and destinations of users who use the shared vehicle, and travel costs for users to travel to vehicle storage locations. Note that this information may be input into the information acquisition unit 2 by a user, or may be set in advance in the information acquisition unit 2, for example.

[0016] The optimization problem constructing unit 3 is a specific example of an optimization problem constructing means. Based on the information acquired by the information acquiring unit 2, the optimization problem constructing unit 3 constructs a first optimization problem of the following equation (1).

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[0017] However, the variables and coefficients in the above equation (1) are defined as follows:

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[0018] The optimization problem construction unit 3 converts the inequality constraints in the first optimization problem of the above equation (1) into equality constraints, and then constructs the second optimization problem of the following equation (2) by continuously relaxing the variables in the equation. In this way, by constructing an easy-to-handle equivalent second optimization problem that can obtain the same optimal solution as the problem to be solved while eliminating combinatorial elements from the first optimization problem to be solved, it is possible to solve this second optimization problem quickly, as will be described later.

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[0019] The algorithm calculation unit 4 is a specific example of an algorithm calculation means. The algorithm calculation unit 4 can quickly solve the second optimization problem of the above equation (2) by using an algorithm based on the sinkhorn algorithm as follows.

[0020] That is, the algorithm calculation unit 4 calculates and updates the Lagrange multiplier f() using the following equation (3) based on the second optimization problem of the above equation (2) constructed by the optimization problem construction unit 3.

[0021] In the following equation (3), predetermined initial values ​​are set for g and h. Here, in the following equation (3), a hat symbol placed above g is referred to as g, and a hat symbol placed above h is referred to as h, and hereafter, other parameters are expressed in the same manner.

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[0022] Similarly, the algorithm calculation unit 4 calculates and updates the Lagrange multipliers g() and h() using the following equation (4) based on the second optimization problem of the above equation (2) constructed by the optimization problem construction unit 3.

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[0023] Here, the algorithm calculation unit 4 calculates D hat, S hat, and A hat in the above equations (3) and (4) using the following equation (5).

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[0024] The algorithm calculation unit 4 determines whether the calculated solution satisfies the constraints of the second optimization problem of the above equation (2). If the algorithm calculation unit 4 determines that the calculated solution does not satisfy the constraints of the second optimization problem of the above equation (2), it updates the Lagrange multipliers and calculates a solution again.

[0025] The algorithm calculation unit 4 repeats the updating of the Lagrange multipliers f(·), g(·), and h(·) and the calculation of the solution until the constraints of the second optimization problem in the above equation (2) are satisfied.

[0026] If the algorithm calculation unit 4 determines that the calculated solution satisfies the constraints of the second optimization problem of the above equation (2), it outputs the solution and terminates.

[0027] Next, we will explain the results of a simulation using the above-mentioned vehicle management system 1. For example, as shown in Figure 3, assume that there are six stations with only one vehicle storage location, and two users 1 and 2 move from (1) to (1)' and from (2) to (2)', respectively.

[0028] In Fig. 3, squares represent stations. Colored (hatched) squares indicate that there are shared vehicles in the vehicle storage area, while open squares indicate that there are no shared vehicles and that the area is empty.

[0029] Figures 4 and 5 show examples of calculation results of the optimization problem for the above settings. In both Figures 4 and 5, User 1 travels along the route from Departure Point (1) → Station 1 → Station 2 → Destination (1)'. User 2 travels along the route from Departure Point (2) → Station 3 → Station 5 → Destination (2)'.

[0030] 4, it is necessary for user 1 to be able to return the shared vehicle at station 2, and for user 2 to be able to reserve a shared vehicle at station 3. To achieve this, the shared vehicle must be moved between stations 2 and 3, and this movement is indicated by the bold arrow in the figure.

[0031] In Figure 5, a shared vehicle moves from station 2 to station 4 and from station 6 to station 3. Depending on the cost of moving the shared vehicle between stations and the cost of the user traveling to the station, different results may be obtained, as shown in Figures 4 and 5. The final result is a solution that minimizes the sum of the user's travel cost to the station and the service provider's vehicle dispatch cost.

[0032] Next, a description will be given of a vehicle management method performed by the vehicle management system 1 according to the present embodiment. Fig. 6 is a flowchart showing the flow of the vehicle management method according to the present embodiment.

[0033] The information acquisition unit 2 acquires information regarding the location of the vehicle storage location of the shared vehicle, the travel cost when the shared vehicle moves between vehicle storage locations, the departure and destination of the user using the shared vehicle, and the travel cost for the user to travel to the vehicle storage location (step S101).

[0034] The optimization problem constructing unit 3 constructs a first optimization problem of the above equation (1) based on the information acquired by the information acquiring unit 2 (step S102).

[0035] The optimization problem constructing unit 3 converts the inequality constraints in the first optimization problem of the above equation (1) into equality constraints, and further constructs the second optimization problem of the above equation (2) by continuously relaxing the variables of the equation (step S103). The algorithm calculation unit 4 calculates and updates the Lagrange multipliers using the above equations (4) and (3) based on the second optimization problem of the above equation (2) constructed by the optimization problem construction unit 3 (step S104).

[0036] The algorithm calculation unit 4 uses the calculated Lagrange multipliers to calculate a solution to the second optimization problem using the above equation (6) (step S105).

[0037] The algorithm calculation unit 4 determines whether the calculated solution to the second optimization problem satisfies the constraint of the second optimization problem in the above equation (2) (step S106). If the algorithm calculation unit 4 determines that the calculated solution to the second optimization problem does not satisfy the constraint of the second optimization problem in the above equation (2) (NO in step S106), the process returns to the above (step S104).

[0038] On the other hand, if the algorithm calculation unit 4 determines that the calculated solution to the second optimization problem satisfies the constraint of the second optimization problem in the above equation (2) (YES in step S106), it ends this process.

[0039] As described above, according to the vehicle management system 1 of this embodiment, by using an algorithm based on the Synchorn algorithm, which enables high-speed optimization, it is possible to quickly find a solution even when the optimization problem is large in scale, thereby increasing the calculation processing speed.

[0040] In addition, the problem is set up so that the movement of shared vehicles between stations is handled by the service provider, not the user, so there is no need to forcefully stimulate user demand for transportation.

[0041] Furthermore, although the station service provider incurs costs when moving the shared vehicle, it is possible to obtain a plan that minimizes the overall cost by taking into account this cost and the user's travel costs.

[0042] Furthermore, since the calculation is made to minimize the user's travel costs, if there are no shared vehicles in a vehicle storage location close to the user, the calculation result can be obtained such that the service provider moves a shared vehicle from another vehicle storage location to the vehicle storage location close to the user, taking into account the overall cost.

[0043] Although several embodiments of the present disclosure have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the invention and its equivalents as defined in the claims.

[0044] The present disclosure can also be implemented by causing a processor to execute a computer program to perform the processing shown in FIG. 6, for example.

[0045] The program can be stored and supplied to a computer using various types of non-transitory computer readable media. Non-transitory computer readable media include various types of tangible storage media. Examples of non-transitory computer readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory)).

[0046] The program may be provided to the computer by various types of transitory computer-readable media. Examples of transitory computer-readable media include electrical signals, optical signals, and electromagnetic waves. The transitory computer-readable media can provide the program to the computer via a wired communication path such as an electrical wire or optical fiber, or via a wireless communication path.

[0047] Each part constituting the vehicle management system 1 according to the above-described embodiment can be realized not only by a program, but also in part or in whole by dedicated hardware such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array). [Explanation of symbols]

[0048] 1. Vehicle management system, 2. Information acquisition unit, 3. Optimization problem construction unit, 4. Algorithm calculation unit

Claims

1. an information acquisition means for acquiring information on the location of vehicle storage locations where shared vehicles are stored, travel costs when the shared vehicles move between the vehicle storage locations, departure points and destinations of users who use the shared vehicles, and travel costs for users to travel to the vehicle storage locations; an optimization problem constructing means for constructing a first optimization problem based on the information acquired by the information acquiring means, and for constructing a second optimization problem by converting inequality constraints in the constructed first optimization problem into equality constraints and continuously relaxing variables in the equations; an algorithm calculation means for calculating a Lagrangian multiplier based on the second optimization problem constructed by the optimization problem construction means, and for calculating a solution to the second optimization problem based on the calculated Lagrangian multiplier; Equipped with Vehicle management system.

2. The vehicle management system according to claim 1, the algorithm calculation means repeats updating the Lagrange multiplier and calculating the solution to the second optimization problem until the constraints of the second optimization problem are satisfied. Vehicle management system.

3. A step of acquiring information regarding the location of a vehicle storage location where a shared vehicle is stored, a travel cost when the shared vehicle moves between the vehicle storage locations, a departure point and a destination of a user who uses the shared vehicle, and a travel cost for the user to travel to the vehicle storage location; constructing a first optimization problem based on the acquired information, and constructing a second optimization problem by converting inequality constraints in the constructed first optimization problem into equality constraints and continuously relaxing variables in the equation; calculating a Lagrangian multiplier based on the constructed second optimization problem, and calculating a solution to the second optimization problem based on the calculated Lagrangian multiplier; Including, Vehicle management methods.

4. A process of acquiring information on the location of vehicle storage locations where shared vehicles are stored, the travel costs when the shared vehicles move between the vehicle storage locations, the departure points and destinations of users who use the shared vehicles, and the travel costs for users to travel to the vehicle storage locations; constructing a first optimization problem based on the acquired information, and converting the inequality constraints in the constructed first optimization problem into equality constraints and continuously relaxing the variables in the equation to construct a second optimization problem; calculating a Lagrangian multiplier based on the constructed second optimization problem, and calculating a solution to the second optimization problem based on the calculated Lagrangian multiplier; to the computer, program.

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