Information processing device, information processing method, program

Abstract

Creating an appropriate vehicle operation plan takes time. [Solution] The information processing device of the present disclosure comprises: a construction unit that constructs association information that associates the number of trains at stations and between stations with station information representing stations at each time based on a train timetable; and a creation unit that creates a train operation plan that determines the train formations to be operated between stations in the train timetable so as to satisfy the constraints based on the association information.

Description

Technical Field

[0001] This disclosure relates to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] Patent Document 1 describes creating a vehicle operation plan based on a train schedule. Specifically, in Patent Document 1, each train in the train schedule is regarded as a node, and a network connecting the trains by arcs is represented, and a vehicle operation plan is created by searching for the running route of the trains.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the above-mentioned Patent Document 1, there is a problem that it takes time to search for the running route of the trains and it takes time to create an appropriate vehicle operation plan.

[0005] Therefore, one of the objects of this disclosure is to solve the above-mentioned problem that it takes time to create an appropriate vehicle operation plan.

Means for Solving the Problems

[0006] An information processing apparatus according to one aspect of this disclosure includes a construction unit that constructs association information associating the constraints on the number of vehicles at stations and between stations with station information representing stations for each time based on a train schedule, and a creation unit that creates a vehicle operation plan that determines the formation to be operated at stations and between stations in the train schedule so as to satisfy the constraints based on the association information. The information processing apparatus is provided with This is the structure it takes. Furthermore, the information processing method, which is one form of this disclosure, Based on the train schedule, we construct association information that links station information representing stations at each time point with constraints on the number of trains at each station and between stations. Based on the aforementioned association information, a train operation plan is created that specifies the train formations to be used at stations and between stations in the train timetable in order to satisfy the aforementioned constraints. This is the structure it takes. Furthermore, one form of this disclosure is a program, In an information processing device, Based on the train schedule, we construct association information that links station information representing stations at each time point with constraints on the number of trains at each station and between stations. Based on the aforementioned association information, a train operation plan is created that specifies the train formations to be used at stations and between stations in the train timetable in order to satisfy the aforementioned constraints. To execute the process This is the structure it takes. [Effects of the Invention]

[0007] This disclosure, when structured as described above, can reduce the time required to create an appropriate vehicle operation plan. [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing an example of the configuration of the information processing device related to this disclosure. [Figure 2] This flowchart shows an example of the processing operation of the information processing device related to this disclosure. [Figure 3] This figure shows an example of the processing process of the information processing device related to this disclosure. [Figure 4] This figure shows an example of the processing process of the information processing device related to this disclosure. [Figure 5] This block diagram shows an example of the hardware configuration of the information processing device related to this disclosure. [Figure 6] This is a block diagram showing an example of the configuration of the information processing device related to this disclosure. [Modes for carrying out the invention]

[0009] <First Embodiment> A first embodiment of this disclosure will be described with reference to the drawings. The drawings may be relevant to any embodiment.

[0010] The information processing device 10 of this disclosure is used, as an example, to create a vehicle operation plan based on a train timetable. In particular, in this embodiment, the vehicle operation plan is created to satisfy the constraints on the number of vehicles at stations and between stations. In this embodiment, the vehicle operation plan is further created to minimize the cost of vehicles in accordance with the operator's requests, etc. However, in this disclosure, it is not necessarily limited to considering the cost of vehicles, and it is sufficient to create a vehicle operation plan that satisfies the constraints. In this disclosure, a set of one or more vehicles is referred to as a "train formation," and a train formation that operates between stations is referred to as a "train."

[0011] The configuration and operation of the information processing device 10 in this embodiment will be described below. The information processing device 10 is composed of one or more information processing devices, each equipped with an arithmetic unit and a storage device. As shown in Figure 1, the information processing device 10 includes a graph construction unit 11, a solution unit 12, and an allocation unit 13. The functions of the graph construction unit 11, the solution unit 12, and the allocation unit 13 can be realized by the arithmetic unit executing a program for realizing each function stored in the storage device. The information processing device 10 also includes a graph storage unit 15 formed in the storage device.

[0012] The graph construction unit 11 (construction unit) first accepts a train schedule, constraints, and operation requirements (step S1 in FIG. 2). The train schedule is information of a diagram (schedule diagram) representing the operation plan of trains, and is represented, for example, as shown in the left diagram of FIG. 3. Specifically, the train schedule includes stations and the arrival and departure times (departure time and arrival time) of each train at the stations, and is configured so that the required time between stations for each train and the required time at each station can also be understood. Further, the train schedule may include other information such as the type of vehicle.

[0013] Constraints are information representing constraints on vehicles on stations and tracks between stations. For example, the constraints may be information such as the number of vehicles that can wait at each station and the number of vehicles that can be parked at night, or information such as the number of vehicles that can enter each track. Note that the constraints are not limited to constraints on the number of vehicles at stations and between stations, and may include constraints on the type of vehicle.

[0014] Operation requirements are information representing requirements regarding trains from the operation staff. For example, the operation requirements are information such as the maximum number of vehicles, the desired number of vehicles, and the minimum number of vehicles for each section between stations and for each time period. Note that the operation requirements may be the number of vehicles required for each section between stations regardless of time, and may also include requirements regarding the type of vehicle between stations.

[0015] Then, the graph construction unit 11 constructs a graph using the train schedule, constraints, and operation requirements, with station information representing stations for each time period as nodes, and associating information representing the movement of vehicles between stations as edges with such nodes (step S2 in FIG. 2). It can also be said that an edge represents at least one of a train between stations or a formation waiting (or staying) at a station across time periods (hereinafter referred to as a "waiting formation"). Constraints such as the number of vehicles in the formation that can wait at a station and the number of vehicles in the train between stations may be associated with the edge. As an example, the graph construction unit 11 constructs a graph as shown in the right diagram of FIG. 3 from the train schedule shown in the left diagram of FIG. 3 and the above-described constraints and operation requirements. Here, an example of constructing the graph will be described with reference to FIG. 3.

[0016] First, in the train schedule of the left figure in FIG. 3, the train indicated by the arrow within symbol T0’ represents the train arriving at Station B (hereinafter referred to as the “arriving train”), and the train indicated by the arrow within symbol T0” represents the train departing from Station B (hereinafter referred to as the “departing train”). Also, the group of trains indicated by the arrows within symbol T1’ represents the trains arriving at Station B. In such a case, each station related to “arriving train T0’ at Station B → departing train T0” from Station B” shall be represented as one node at time T0. As a result, as shown in the right figure of FIG. 3, Station A, Station B, and Station C at time T0 are represented as nodes A_0, B_0, and C_0 respectively, and Station B at time T1 is represented as node B_1. In addition, for each node corresponding to each station at each time, edges represented by arrows corresponding to each train in operation are connected. Specifically, when there are trains running between stations at each time, the nodes corresponding to each station at each time are connected by edges represented by arrows corresponding to the trains running. Also, when it is possible for formations to wait at each station at each time, edges represented by dotted arrows corresponding to the waiting of formations at the station are connected to the nodes corresponding to each station at each time.

[0017] Then, the graph construction unit 11 sets, based on the constraints and operation requirements, for the edges connected to the nodes as described above, a capacity representing the constraints on the number of vehicles at stations and between stations, and a cost per vehicle.

[0018] Capacity represents constraints when creating a train schedule. For example, capacity is a value set from constraints, and if an edge represents a train running between stations, it sets the maximum number of trains that can run between those stations. In this case, capacity may also represent the maximum number of trains determined by the number of tracks, etc. For example, if an edge represents a train waiting at a station, capacity sets the maximum number of trains that can wait at that station. In this case, capacity may also represent physical constraints such as the number of platforms for waiting trains at a station. Capacity may also represent constraints due to the operating schedule. In this case, capacity may, for example, represent the maximum number of trains that can operate during a particular time period, based on the departure and arrival times set for that time period or the congestion of the train schedule. Capacity may also represent safety or operational constraints. In this case, capacity may, for example, be a value set based on safety standards to ensure safe train operation on the tracks and at stations. Capacity may also represent constraints on trains that can be parked at a station from the time of the last train of the day to the time of the first train of the following day. In this case, capacity may represent, for example, the number of platforms at a station, as well as the number of vehicles that can be stored in the train depot at the station.

[0019] Cost is set at the edge and represents a numerical value related to the evaluation of vehicle operation. For example, cost represents the cost incurred by a vehicle traveling between stations, or the cost incurred by a vehicle waiting at a station. In this case, the cost is set to a smaller value the more it is desired for a vehicle to be operated at or between stations, according to the operational request. For example, between stations, the cost is set to a small value in sections where it is desired for a vehicle to travel, and in some cases, it may be set to a negative value. Therefore, if a large number of passengers are expected during a given time or between stations, and the number of vehicles requested in the operational request is large, the cost will be set to a small value. Also, when a vehicle is waiting at a station, the cost will be small if it is desired for use by many people afterward, and large if it is not desired for use afterward or if there are few vehicles that can wait.

[0020] Furthermore, the cost may represent the expenses required to operate the train. In this case, the cost represents economic expenses such as electricity, maintenance, and fuel costs associated with operating the train. The cost may also represent expenses based on the demand for the train. In this case, the cost is set according to passenger demand in a particular time period or section. For example, when demand is high, train allocation is prioritized, so the cost is set low, and when demand is low, the cost is set high. The cost may also represent expenses based on the characteristics of the vehicle. In this case, for example, when maintenance is required more frequently in operation, the cost is set high, and when maintenance is required less frequently, the cost is set low. The cost may also be set according to the intention to operate the train. In this case, for example, the cost is set low when there is a sudden increase in demand, such as during an event, and high under normal circumstances.

[0021] As described above, the graph construction unit 11 constructs a graph, as shown in the right-hand diagram of Figure 3, by connecting nodes representing stations for each hour with edges representing the number of train cars waiting at stations, constraints on the number of train cars between stations, and the cost of the cars. At this time, nodes representing virtual start and end points may be set at the beginning and end of the day to construct a group of graphs representing the train schedule for the entire day, or the train schedule may be divided into predetermined time periods, and a group of graphs may be constructed for each time period. The graph construction unit 11 then stores the constructed graphs in the graph storage unit 15.

[0022] The problem-solving unit 12 (creation unit) uses the graph constructed as described above to calculate the number of vehicles to operate so as to satisfy the constraints set for each station and the space between stations. At this time, the problem-solving unit 12 calculates the number of vehicles to operate so as to minimize the cost for the entire group of graphs. In other words, the problem-solving unit 12 solves the minimum cost flow problem in the graph (step S3 in Figure 2).

[0023] Here, Figure 4 shows an example of a graph constructed by the graph construction unit 11 and solved by the solution unit 12. In this graph, node 1 is the starting point and node 5 is the ending point, and each node (1 to 5) represents a station at each time point. Each node is connected to an edge corresponding to the train being operated, and each edge is further assigned the aforementioned "capacity" and "cost". In this case, the "flow rate" shown in Figure 4 represents the number of operational "vehicles". Therefore, in the example in Figure 4, the problem is to minimize the cost across the entire graph and allocate "vehicles = 10" while satisfying the capacity constraint set for each edge. Specifically, the solution unit 12 calculates the allocation of the number of vehicles (shown as "?" in Figure 4) at each edge such that it does not exceed the maximum number of vehicles, which is the "capacity", and the sum of the values ​​obtained by multiplying the "cost" by the number of vehicles is minimized.

[0024] For example, the edge connecting node 1 and node 2 is set to "Capacity: 5" and "Cost: 3". Therefore, at this edge, the number of vehicles, which is the "flow rate," will be 5 or less, and the cost will be calculated as "Number of vehicles × 3 (cost)". Then, at all edges, the calculation of "Number of vehicles × cost" is performed so that the "flow rate" does not exceed the "Capacity" of the number of vehicles, and the allocation of the number of vehicles, which is the "flow rate," at each edge is calculated to minimize the total cost.

[0025] The allocation unit 13 (creation unit) assigns train sets to each train in the train timetable so that the number of trains is the same as the number of trains calculated by the solving unit 12 as described above (step S4 in Figure 2). In other words, the number of trains used in each train in the train timetable is the number of trains calculated. Then, the allocation unit 13 creates and outputs a train operation plan consisting of a series of trains operated by each train set, as a result of assigning train sets to each train as described above.

[0026] Furthermore, the allocation unit 13 may control the configuration of each train according to the number of cars that have been determined. For example, the allocation unit 13 may control the addition and removal of train formations in the station depot and on the tracks according to the number of cars that have been determined by assigning multiple formations to the same train so that the total number of cars is equal to the number of cars that have been determined.

[0027] As described above, according to this embodiment, by creating a graph with stations at each time interval as nodes and vehicle constraints and costs as edges, it is possible to search for a train formation that satisfies the constraints while minimizing costs. This reduces the time required for the search, and as a result, reduces the time required to create an appropriate vehicle operation plan that satisfies the constraints.

[0028] Herein, the graph construction unit 11 is not necessarily limited to constructing a graph. For example, the graph construction unit 11 may construct association information of a data structure that associates the number of vehicles waiting at a station and the number of train vehicles between stations with station information representing stations for each time period, as well as constraints and costs. The solving unit 12 can then calculate the allocation of the number of vehicles in the same manner as described above by solving the association information to satisfy the constraints.

[0029] Furthermore, this disclosure is not necessarily limited to setting costs on the graph (association information). For example, the graph construction unit 11 constructs association information in a data structure that associates the number of vehicles waiting at a station and the number of train vehicles between stations with station information representing stations for each time period, and the solving unit 12 solves the association information to satisfy the constraints on the number of vehicles at stations and between stations, thereby calculating the allocation of the number of vehicles in the same manner as described above.

[0030] <Second Embodiment> Next, a second embodiment of the present disclosure will be described with reference to the drawings. This embodiment shows an outline of the information processing device, etc., described in the above-described embodiment. Note that the drawings may be relevant to any embodiment.

[0031] First, the hardware configuration of the information processing device 100 in this disclosure will be described. The information processing device 100 is composed of a general information processing device, and as an example, it is equipped with the following hardware configuration as shown in Figure 5. ·CPU(Central Processing Unit)101(Arithmetic unit) ROM (Read Only Memory) 102 (Storage Device) • RAM (Random Access Memory) 103 (Storage Device) • Program group 104 loaded into RAM 103 • Storage device 105 for storing the program group 104 • Drive device 106 for reading and writing to external storage medium 110 of the information processing device. • Communication interface 107 connecting to a communication network 111 outside the information processing device. • Input / output interface 108 for data input and output. • Bus 109 connecting each component

[0032] Figure 5 shows an example of the hardware configuration of the information processing device 100, and the hardware configuration of the information processing device is not limited to the case described above. For example, the information processing device may consist of only a part of the configuration described above, such as not having a drive device 106. In addition, the information processing device may use a GPU (Graphic Processing Unit), DSP (Digital Signal Processor), MPU (Micro Processing Unit), FPU (Floating point number Processing Unit), PPU (Physics Processing Unit), TPU (Tensor Processing Unit), quantum processor, microcontroller, or a combination thereof instead of the CPU described above.

[0033] The information processing device 100 can then construct and equip the construction unit 121 and the creation unit 122 shown in Figure 6 by having the CPU 101 acquire the program group 104 and execute it. The program group 104 is, for example, stored in advance in the storage device 105 or ROM 102, and the CPU 101 loads it into the RAM 103 and executes it as needed. The program group 104 may also be supplied to the CPU 101 via the communication network 111, or it may be stored in advance in the storage medium 110, and the drive device 106 reads the program and supplies it to the CPU 101. However, the construction unit 121 and the creation unit 122 described above may be constructed with dedicated electronic circuits to realize these means.

[0034] The above-mentioned construction unit 121 constructs association information that associates the number of train cars waiting at a station and the constraints on the number of train cars between stations with station information representing stations at each time, based on the train timetable. The above-mentioned creation unit 122 creates a train operation plan that determines the train sets to be used at stations and between stations in the train timetable so as to satisfy the constraints, based on the association information.

[0035] As described above, this disclosure enables the creation of association information that links the number of trains to station information for each time period, and enables the creation of a train operation plan that satisfies the number of trains based on this association information. As a result, the time required to create an appropriate train operation plan that satisfies the constraints can be reduced.

[0036] Furthermore, at least one of the functions of the construction unit 121 and the creation unit 122 described above may be executed on an information processing device installed and connected to any location on the network, that is, it may be executed using so-called cloud computing.

[0037] Furthermore, the aforementioned programs 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 memory (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory)). Programs may also be supplied to a computer using various types of transient computer-readable media. Examples of transient computer-readable media include electrical signals, optical signals, and electromagnetic waves. Transitory computer-readable media can be supplied to a computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

[0038] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure are possible, as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, each of the embodiments described above can be combined with other embodiments as appropriate.

[0039] <Note> Some or all of the above embodiments may also be described as follows. The general configuration of the information processing apparatus, information processing method, and program in this disclosure is described below. However, this disclosure is not limited to the configurations described below. Furthermore, some or all of the configurations and functions described in Appendices 2 to 8, which are dependent on Appendice 1 below, may also be dependent on Appendices 9 and 10 in the same way as Appendices 2 to 8. Moreover, not limited to Appendices 1, 9, and 10, some or all of the configurations and functions described as appendices may also be dependent on similar hardware, software, various recording means for recording software, or systems, without departing from the embodiments described above. (Note 1) Based on the train schedule, a construction unit constructs association information that links station information representing stations at each time of day with constraints on the number of trains at each station and between stations. Based on the aforementioned association information, a creation unit creates a vehicle operation plan that determines the train formations to be used at stations and between stations in the train timetable in order to satisfy the aforementioned constraints, Equipped with an information processing device. (Note 2) The information processing device described in Appendix 1, The construction unit creates a graph in which the station information is used as a node and edges representing the constraints are connected to the nodes as the association information. Information processing device. (Note 3) The information processing device described in Appendix 2, The construction unit creates the graph by connecting the constraints of the number of cars in a train set waiting at a station and the number of cars in a train moving between stations as edges to the nodes. Information processing device. (Note 4) The information processing device described in Appendix 1, The creation unit calculates the cost between stations in the train timetable based on the associated information, according to the number of trains used between stations, and creates the train operation plan based on the calculated cost. Information processing device. (Note 5) The information processing device described in Appendix 4, The creation unit calculates the total cost between stations based on the number of trains operating between stations in a group of associated information, and creates the train operation plan so as to minimize the total cost. Information processing device. (Note 6) The information processing device described in Appendix 5, The aforementioned costs are set to a value small enough that it is desirable for trains to be operated at and between stations. Information processing device. (Note 7) The information processing device described in Appendix 4, The construction unit constructs association information that associates the station information with the costs incurred for each vehicle when operating at stations and between stations. Information processing device. (Note 8) The information processing device described in Appendix 7, The construction unit receives requests for vehicle operation between stations and constructs associated information that links the costs corresponding to said operation requests with the station information. Information processing device. (Note 9) Based on the train schedule, we construct association information that links station information representing stations at each time point with constraints on the number of trains at each station and between stations. Based on the aforementioned association information, a train operation plan is created that specifies the train formations to be used at stations and between stations in the train timetable in order to satisfy the aforementioned constraints. Information processing methods. (Note 10) In an information processing device, Based on the train schedule, we construct association information that links station information representing stations at each time point with constraints on the number of trains at each station and between stations. Based on the aforementioned association information, a train operation plan is created that specifies the train formations to be used at stations and between stations in the train timetable in order to satisfy the aforementioned constraints. A program that executes a process. [Explanation of Symbols]

[0040] 10 Information Processing Devices 11 Graph Construction Section 12 Solving section 13. Allocation Section 15 Graph memory unit 100 Information Processing Devices 101 CPU 102 ROM 103 RAM 104 Program Groups 105 Storage device 106 Drive unit 107 Communication Interface 108 Input / Output Interfaces 109 Bus 110 Storage medium 111 Communication Network 121 Construction Department 122 Creation Department

Claims

1. Based on the train schedule, a construction unit constructs association information that links station information representing stations at each time of day with constraints on the number of trains at each station and between stations. Based on the aforementioned association information, a creation unit creates a vehicle operation plan that determines the train formations to be used at stations and between stations in the train timetable in order to satisfy the aforementioned constraints, Equipped with an information processing device.

2. An information processing apparatus according to claim 1, The construction unit creates a graph in which the station information is used as a node and edges representing the constraints are connected to the nodes as the association information. Information processing device.

3. An information processing apparatus according to claim 2, The construction unit creates the graph by connecting the constraints of the number of cars in a train set waiting at a station and the number of cars in a train moving between stations as edges to the nodes. Information processing device.

4. An information processing apparatus according to claim 1, The creation unit calculates the cost between stations in the train timetable based on the associated information, according to the number of trains used between stations, and creates the train operation plan based on the calculated cost. Information processing device.

5. An information processing apparatus according to claim 4, The creation unit calculates the total cost between stations based on the number of trains operating between stations in a group of associated information, and creates the train operation plan so as to minimize the total cost. Information processing device.

6. An information processing device according to claim 5, The aforementioned costs are set to a value small enough that it is desirable for trains to be operated at and between stations. Information processing device.

7. An information processing apparatus according to claim 4, The construction unit constructs association information that associates the station information with the costs incurred for each vehicle when operating at stations and between stations. Information processing device.

8. An information processing apparatus according to claim 7, The construction unit receives requests for vehicle operation between stations and constructs associated information that links the costs corresponding to said operation requests with the station information. Information processing device.

9. Based on the train schedule, we construct association information that links station information representing stations at each time point with constraints on the number of trains at each station and between stations. Based on the aforementioned association information, a train operation plan is created that specifies the train formations to be used at stations and between stations in the train timetable in order to satisfy the aforementioned constraints. Information processing methods.

10. In an information processing device, Based on the train schedule, we construct association information that links station information representing stations at each time point with constraints on the number of trains at each station and between stations. Based on the aforementioned association information, a train operation plan is created that specifies the train formations to be used at stations and between stations in the train timetable in order to satisfy the aforementioned constraints. A program that executes a process.

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