Operation control support device, operation control support system, operation control support method, and operation control support program

Abstract

To provide an operation control support device that can support train operation control not only when a delay occurs but also when a delay is predicted to occur with high probability.SOLUTION: The operation control support device includes a storage unit 22, a data acquisition unit 21, a rule analysis unit 23, and an operation control determination unit 24. The storage unit 22 stores train operation diagram information indicating a train operation plan of a train 51 and operation control history information including content of operation control performed in the past. The data acquisition unit 21 acquires user usage information about a user who uses the train 51 or a station 52 and train operation information about the train 51. The rule analysis unit 23 extracts an operation control rule of the train 51 based on the train operation information, the train operation diagram information, and the operation control history information. The operation control determination unit 24 generates operation control rule candidate information to be used for instructing operation control of the train 51 based on the operation control rule, the train operation information, and the user usage information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a train timetable rescheduling support device, a train timetable rescheduling support system, a train timetable rescheduling support method, and a train timetable rescheduling support program that support train timetable rescheduling. [Background technology]

[0002] Patent Document 1 discloses a train replanning support device that supports train replanning work to restore a schedule disrupted by train delays caused by weather, earthquakes, accidents, etc. to a normal state. The train replanning support device described in Patent Document 1 stores train replanning history data in a train replanning history storage unit, which associates each past train delay data with each train replanning plan implemented for each train delay data. The train replanning support device described in Patent Document 1 then searches the train replanning history data based on train delay information, which includes actual train delay information, which is actual train delays, and predicted train delay information for the entire schedule predicted from the actual train delay information, and presents a train replanning plan associated with the searched train delay data. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2011-111058 Summary of the Invention [Problem to be solved by the invention]

[0004] However, with the above-mentioned conventional technology, since the proposed timetable rescheduling plan is considered based on the delays that have actually occurred, there is a problem that the plan is only taken after the delays have become visible, i.e., after the delays have increased. In other words, with the above-mentioned conventional technology, the trigger for presenting the timetable rescheduling plan is the operation delay, so there is a problem that it is not possible to propose timetable rescheduling that is more extensive than the operation delay.

[0005] The present disclosure has been made in consideration of the above, and aims to provide a train rescheduling support device that can provide support for train rescheduling not only when a delay has occurred, but also when a delay is predicted to occur with a high probability in the future. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the objectives, the timetable replanning support device according to the present disclosure includes a memory unit, a data acquisition unit, a rule analysis unit, and a timetable replanning determination unit. The memory unit stores train schedule information indicating train operation plans and timetable replanning history information including details of timetable replanning implemented in the past. The data acquisition unit acquires user usage information of users who use trains or stations and train operation information. The rule analysis unit extracts train timetable replanning rules based on the operation information, timetable information, and timetable replanning history information. The timetable replanning determination unit generates timetable replanning rule candidate information to be used in issuing train timetable replanning instructions based on the timetable rules, operation information, and user usage information. [Effects of the Invention]

[0007] The train timetable rescheduling support device according to the present disclosure has the advantage of being able to provide train timetable rescheduling support not only when a delay has occurred, but also when a delay is predicted to occur with a high probability in the future. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a traffic management device including a traffic replanning support device according to a first embodiment. [Figure 2] A diagram showing an example of operation information [Figure 3] A diagram showing an example of people flow information [Figure 4] FIG. 10 is a diagram showing an example of train schedule information [Figure 5] FIG. 10 is a diagram showing an example of train schedule history information; [Figure 6] FIG. 1 is a diagram showing an overview of a rule extraction process performed by a rule analysis unit in the traffic management device according to the first embodiment. [Figure 7] An example of a rule extraction database. [Figure 8] FIG. 10 is a diagram showing an example of a database for extracting rules contained in train schedule rescheduling information. [Figure 9] FIG. 10 is a diagram showing an example of train schedule rule information [Figure 10] FIG. 10 is a diagram showing an example of a screen showing candidate information for traffic rescheduling rules presented to a dispatcher. [Figure 11] A flowchart showing an example of the procedure of a timetable replanning support method according to the first embodiment. [Figure 12] A flowchart showing an example of the procedure for extracting train schedule rescheduling rules. [Figure 13] A flowchart showing an example of a processing procedure of a timetable rescheduling rule information generation method. [Figure 14] Flowchart showing an example of the procedure of a traffic rescheduling determination method [Figure 15] Flowchart showing an example of the procedure of a traffic rescheduling determination method [Figure 16] FIG. 10 is a diagram illustrating an example of the configuration of a timetable replanning support system according to a second embodiment. [Figure 17] FIG. 10 is a diagram illustrating an example of the configuration of a timetable replanning support system according to a third embodiment. [Figure 18] A diagram showing an example of operation information [Figure 19] FIG. 10 is a diagram illustrating an example of the configuration of a traffic management device equipped with a traffic replanning support device according to a fourth embodiment. [Figure 20] FIG. 10 is a diagram illustrating an example of the configuration of a traffic management device equipped with a traffic replanning support device according to a fifth embodiment. [Figure 21] FIG. 1 is a diagram showing an example of a hardware configuration for realizing a traffic management device and a traffic rescheduling support device according to first to fifth embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, a timetable replanning assistance device, a timetable replanning assistance system, a timetable replanning assistance method, and a timetable replanning assistance program according to embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

[0010] Embodiment 1 FIG. 1 is a diagram schematically illustrating an example of the configuration of a traffic management device including a traffic replanning support device according to the first embodiment. The traffic management device 1A manages the operation of multiple trains 51 on a railway. The traffic management device 1A also supports traffic replanning work to restore a schedule to a normal state when a delay of a train 51 occurs due to weather, an earthquake, an accident, or the like, or when a schedule disruption occurs due to a delay of a train 51 caused by the degree of congestion on the train 51 or the user usage status of a station 52. The traffic replanning work may be performed to suppress a schedule disruption that may occur due to a delay of a train 51 caused by the degree of congestion on the train 51 or the user usage status of a station 52, that is, to prevent a schedule disruption from occurring in advance. FIG. 1 also illustrates one of the multiple trains 51 and one of the multiple stations 52.

[0011] The traffic control device 1A is connected via a network to each of the multiple trains 51, each of the multiple stations 52 at which the trains 51 depart and arrive, and an information processing terminal 53 operated by a train dispatcher who performs traffic control. Information is transmitted and received via the network between the traffic control device 1A, each of the multiple trains 51, each of the multiple stations 52, and the information processing terminal 53. The network is, for example, a wide area network (WAN) such as the Internet, but may also be a local area network (LAN). The traffic control device 1A is also connected to a display device 54.

[0012] Each of the multiple trains 51 transmits running performance data indicating the running performance of the train 51 to the traffic management device 1A via a communication device (not shown). The running performance data includes a train number, type, running direction, station departure and arrival times, and congestion level. The train number is identification information that uniquely identifies the train 51. The type is information indicating the type of operation mode of the train 51. Types include "local" trains that stop at every station 52 and "express" trains that stop at designated stations 52. The running direction is information indicating "upbound" or "downbound." In the case of a loop line, the running direction may be "outer loop" or "inner loop." The station arrival and departure times are information indicating the times at which the train 51 arrives at and departs from the target station 52. The congestion level is information indicating the degree of congestion of the train 51. Examples of congestion levels are the number of passengers and the occupancy rate. The number of passengers is the number of passengers on the train 51. The occupancy rate is information indicating the ratio of the number of passengers to the train's passenger capacity.

[0013] Each of the multiple stations 52 transmits station facility data indicating the usage status of station facilities to the traffic management device 1A via a communication device (not shown). The station facility data is data that can acquire or estimate people flow, which is the flow of people at the station 52. The station facility data includes ticket gate data, which is data recording entrance and exit at ticket gates, video data from surveillance cameras installed on platforms and other areas within the station 52, and other data indicating people flow. The ticket gate data is data indicating the number of people entering and exiting the station 52, but it may also be origin / destination (OD) data, which indicates boarding data for each passenger from the entrance station, which is the departure point, to the exit station, which is the destination. Other data indicating people flow can also be movement history data acquired using the global positioning system (GPS) function of a portable information terminal carried by a passenger, payment data including an entry record at the entry station and an exit record at the exit station, recorded on an integrated circuit (IC) card.

[0014] The information processing terminal 53 is an information processing device operated by a dispatcher who reschedules trains 51 on a railway. Information about the rescheduling implemented by the dispatcher is input to the information processing terminal 53. The information processing terminal 53 also displays the timetable rescheduling rule candidate information presented by the traffic management device 1A. Examples of such an information processing terminal 53 are a personal computer, a tablet terminal, or a smartphone having an input unit, a display unit, a communication unit, and a processing unit. The information processing terminal 53 displays the timetable rescheduling rule candidate information transmitted from the traffic management device 1A on a display device such as a liquid crystal display device or an organic EL (ElectroLuminescence) display device. The dispatcher issues a timetable rescheduling instruction to the traffic management device 1A via the information processing terminal 53 in accordance with one of the timetable rescheduling rules included in the timetable rescheduling rule candidate information presented by the traffic management device 1A. As a result, the traffic management device 1A performs traffic management in accordance with the timetable rescheduling instruction.

[0015] The traffic management device 1A includes a traffic management unit 11, a data acquisition unit 21, a memory unit 22, a rule analysis unit 23, a timetable replanning determination unit 24, and an output processing unit 25. The memory unit 22 stores five databases: a traffic information database 221, a people flow information database 222, a bus schedule database 223, a timetable replanning history database 224, and a timetable replanning rule information database 225. In FIG. 1, the databases are represented as DBs (Data Bases). This also applies to FIG. 2 and subsequent figures. In FIG. 1, five databases are stored in one memory unit 22, but the traffic management device 1A may be provided with a memory unit for each database.

[0016] Fig. 1 shows a traffic management device 1A equipped with a traffic replanning support device. In Fig. 1, the components excluding the traffic management unit 11, namely, the data acquisition unit 21, the storage unit 22, the rule analysis unit 23, the traffic replanning determination unit 24, and the output processing unit 25, can be considered to correspond to the traffic replanning support device.

[0017] The traffic management unit 11 generates train schedule data, which is an operation plan for a plurality of trains 51, and performs a traffic management process for managing the operation of the plurality of trains 51 based on the train schedule data. A known technique can be used for the traffic management process.

[0018] The data acquisition unit 21 acquires data used for analyzing and determining rules for timetable rescheduling in relation to the decision on timetable rescheduling. The data acquisition unit 21 acquires running history data indicating the running history of trains 51 operating on a railway as operation information. The running history data is input to the data acquisition unit 21 from communication devices (not shown) of each of the multiple trains 51. The data acquisition unit 21 converts the acquired running history data into operation information on a station-to-station basis and transmits it to the operation information database 221 in the storage unit 22. The operation information includes running history information, which is information regarding the operation of the train 51, and congestion degree information, which is information regarding the congestion degree of the train 51.

[0019] The data acquisition unit 21 acquires station facility data indicating the usage status by users of station facilities installed in stations 52 managed by the railway operator. The station facility data is input to the data acquisition unit 21 from communication devices (not shown) of each of the multiple stations 52. If the station facility data is ticket gate data, the ticket gate data indicating the number of people entering and exiting the station 52 during a specified period is input to the data acquisition unit 21 from the communication devices. If the station facility data is video data captured by a camera installed in the station 52, the video data is input to the data acquisition unit 21 from the communication devices. The data acquisition unit 21 acquires the video data as station facility data, estimates people flow information from the video data, and stores the information in the people flow information database 222 of the storage unit 22. Here, the people flow information is generated by estimating the number of people passing through each section of the premises of the station 52 from the acquired video data. Alternatively, if the station facility data is people flow data obtained by estimating the number of people passing through each section of the station 52 from video data from cameras installed within the station 52, the station facility data is input from the communication device to the data acquisition unit 21. That is, the data acquisition unit 21 acquires the people flow data as station facility data. The data acquisition unit 21 stores the station facility data as people flow information in the people flow information database 222 of the storage unit 22.

[0020] As described above, the data acquisition unit 21 acquires data from the train 51 and, if necessary, the station 52, and performs processing to generate user usage information including at least one of the station facility data, which are operation performance information, congestion level information, and people flow information.

[0021] The data acquisition unit 21 acquires train schedule data, which is an operation plan for trains 51 operated by railways. In one example, the train schedule data is generated by the operation management unit 11, and the train schedule data is input to the data acquisition unit 21 from the operation management unit 11. The data acquisition unit 21 converts the acquired train schedule data into train schedule information on a station-to-station basis and stores it in the train schedule database 223 of the storage unit 22. In other words, the data acquisition unit 21 acquires the train schedule data as train schedule information.

[0022] When a train replanning operation is performed due to a delay or the like of the train 51, the data acquisition unit 21 acquires timetable replanning data indicating the details of the timetable replanning operation. In one example, timetable replanning data indicating the details of the timetable replanning operation performed by a skilled dispatcher is input from the information processing terminal 53. The data acquisition unit 21 stores the acquired timetable replanning data in the timetable replanning history database 224 of the storage unit 22 as timetable replanning history information. In the first embodiment, the rule analysis unit 23 described later extracts timetable replanning rules using the history of timetable replanning data performed by a skilled dispatcher. Therefore, when a timetable replanning rule is not stored in the timetable replanning rule information database 225, the data acquisition unit 21 acquires timetable replanning data performed by a skilled dispatcher. After a timetable replanning rule is generated by the rule analysis unit 23, the data acquisition unit 21 also acquires timetable replanning data performed in accordance with the timetable replanning rule from the information processing terminal 53.

[0023] The operation information database 221 stores operation information. As described above, the operation information includes actual operation information of the train 51 obtained from the running history data and congestion information, which is information related to the congestion level of the train 51. FIG. 2 is a diagram showing an example of operation information. The operation information shown in FIG. 2 includes information in the following fields: date, train number, operation type, operation direction, departure station, departure time, arrival station, arrival time, and occupancy rate. The date field indicates the day on which the train 51 is operating. The train number field indicates the train number, which is an identifier for the train 51. The operation type field indicates the operation type, which is the type of train 51. Types include a "local" that stops at every station 52, an "express" that stops at designated stations 52, and the like. The operation direction field indicates the direction of the train 51 on the route on which the train 51 operates. The operation direction can be "upbound" or "downbound," and in the case of a loop line, can be "outer loop" or "inner loop." The departure station field indicates the name of station 52 from which train 51 departs. The departure time field indicates the time at which train 51 departs from the departure station. The arrival station field indicates the name of station 52 at which train 51 arrives. The arrival time field indicates the time at which train 51 arrives at the arrival station. The occupancy rate field indicates the occupancy rate, which is the ratio of the number of passengers on train 51 to the capacity of train 51. The occupancy rate field may be the occupancy rate for the entire train 51 indicated by the train number, or may be the occupancy rate for each car of train 51. In the former case, running history data including the overall occupancy rate of train 51 is acquired by data acquisition unit 21, and in the latter case, running history data including the occupancy rate for each car of train 51 is acquired by data acquisition unit 21.

[0024] The operation information includes, for each train 51, information about all the inter-station routes that the train 51 has traveled. Each row in the table shown in FIG. 2 represents information about each inter-station route for each train 51. In one example, the top row of the table shown in FIG. 2 shows information about the route between stations A and B for train 51, whose train number is "0001M" on "2022 / 10 / 1," whose operation type is "local," and whose operation method is "upbound." The row also shows that the departure time from station A for the train 51 is 8:00, the arrival time at station B is 8:05, and the occupancy rate is 78.2%. The operation information may also include items such as a route ID (identifier) ​​that identifies the route on which the train 51 operates, and a type priority that indicates the priority of the type of train 51. In the example of Figure 2, the date, train number, operation type, operation direction, departure station, departure time, arrival station, and arrival time correspond to operation performance information, and the date, train number, operation type, operation direction, departure station, arrival station, and occupancy rate correspond to congestion level information.

[0025] Returning to FIG. 1 , the people flow information database 222 stores people flow information. The people flow information is information indicating the flow of people at a station 52. FIG. 3 is a diagram illustrating an example of people flow information. In FIG. 3 , ticket gate data indicating the entry and exit history of users at each station 52 is shown as the people flow information. The ticket gate data is information indicating the number of users entering and exiting at a specific time. In the example of FIG. 3 , the horizontal axis of the ticket gate data indicates the specific time, and the vertical axis indicates the number of people. In FIG. 3 , the specific time on the horizontal axis is set to one hour, and the total number of users entering and exiting is shown as a bar graph. In the bar graph, the number of users entering is shown as a solid bar, and the number of users exiting is shown as a hollow bar. Note that FIG. 3 is an example, and the ticket gate data indicating the entry and exit history does not have to be a graph, and may be other types of data, such as table data. Furthermore, the specific time may be one minute, five minutes, ten minutes, or any other time.

[0026] Returning to FIG. 1, the train schedule database 223 stores train schedule information. The train schedule information is information that indicates the operation plan of train 51 on a railway. Here, the train schedule information indicates the operation plan of train 51 on a station-to-station basis. FIG. 4 is a diagram showing an example of train schedule information. The train schedule information shown in FIG. 4 includes information on the following items: operation day, train number, operation direction, departure station, departure time, arrival station, arrival time, and type. The operation day item indicates the day on which train 51 operates. Types of operation days include holidays including Saturdays, Sundays, and public holidays, weekdays other than holidays, all days including holidays and weekdays, and days on a specified date. The train number, operation direction, departure station, departure time, arrival station, and type items are the same as those described in FIG. 2.

[0027] The train schedule information includes, for each train 51, information about all the inter-station routes that the train 51 runs between. Each row in the table shown in FIG. 4 represents information about each inter-station route for each train 51. In one example, the top row in the table shown in FIG. 4 shows information about the train 51 with train number "0001M" running between stations A and B. The row also shows that the train 51 operates all day, its direction of travel is up, its departure time from station A is 8:00, its arrival time at station B is 8:05, and its train type is local. The train schedule information may also include items such as a route ID, which is information identifying the route on which the train 51 runs, and a type priority, which indicates the priority of the type of train 51.

[0028] Returning to Figure 1, the traffic replanning history database 224 stores traffic replanning history information. Traffic replanning history information is information indicating the details of traffic replanning operations carried out for trains 51 on a railway, and is information that accumulates traffic replanning data. In other words, traffic replanning history information is information that includes the details of traffic replanning operations that have been carried out in the past. Figure 5 is a diagram showing an example of traffic replanning history information. The traffic replanning history information shown in Figure 5 includes information on the following items: date, operation time, train number, implementation location, and implementation details. The date item indicates the day on which the traffic replanning operation was carried out. The operation time item indicates the time when the traffic replanning operation was carried out. The implementation location item indicates the location where the traffic replanning operation was carried out. The implementation details item indicates the details of the traffic replanning operation that was carried out. The train number item is the same as that described in Figure 2.

[0029] The traffic rescheduling history information includes information on each traffic rescheduling operation. Each row in the table shown in FIG. 5 represents information on a unit of traffic rescheduling operation. In one example, the first row from the top of the table shown in FIG. 5 shows information on the traffic rescheduling operation performed on train 51 with train number "0013M." The row also shows that, for the traffic rescheduling operation, a change in the operating order with the following train was made at Station D at 8:25 on October 1, 2022.

[0030] Returning to FIG. 1 , the rule analysis unit 23 performs processing to extract a train rescheduling rule for the train 51 based on operation performance information indicating the operation performance of the train 51, congestion level information or station facility data indicating the degree of congestion of the train 51, train schedule information indicating the train 51's operation plan, and train schedule history information including the details of past train schedule rescheduling. The processing of the rule analysis unit 23 is described in detail below. The rule analysis unit 23 extracts a train schedule rescheduling rule including the preconditions for the train schedule rescheduling and the details of the train schedule rescheduling to be implemented when the preconditions are met from the train schedule history information including the details of past train schedule rescheduling, the train 51's operation performance information at that time, user usage information indicating the user's usage of the train 51 and station 52, and the train schedule information for the train 51, and generates train schedule rescheduling rule information including the train schedule rescheduling rule. A data mining technique is used to extract the train schedule rescheduling rule. The user usage information is information including at least one of congestion level information and pedestrian flow information contained in the train schedule information. In the example of Figure 1, the rule analysis unit 23 uses a data mining technique to extract timetable rescheduling rules that indicate correlation rules regarding timetable rescheduling operations between operation information, pedestrian flow information, and bus schedule information, and timetable rescheduling history information, and stores timetable rescheduling rule information including the extracted timetable rescheduling rules in the timetable rescheduling rule information database 225. The process of generating timetable rescheduling rule information by the rule analysis unit 23 is performed in the background, and in one example, the rule analysis unit 23 generates timetable rescheduling rule information outside of commercial operating hours, such as after commercial operations have ended. One example of the analysis method used in the data mining technique is association analysis.

[0031] A timetable rescheduling rule includes preconditions, including one or more conditions or situations for implementing timetable rescheduling, extracted from operation information, pedestrian flow information, and bus schedule information, and timetable rescheduling details, which are details of timetable rescheduling that are implemented when the preconditions are met. In other words, the rule analysis unit 23 analyzes the correlation between the preconditions extracted from operation information, pedestrian flow information, and bus schedule information and the timetable rescheduling details, and extracts, as timetable rescheduling rules, combinations of preconditions and timetable rescheduling details that have a correlation greater than or equal to a predetermined value. The timetable rescheduling rule information may further include information that allows a dispatcher to determine whether to implement a timetable rescheduling detail, such as the number of occurrences, which indicates the number of times the preconditions occurred, and the implementation rate, which indicates the percentage of timetable rescheduling details implemented when the preconditions were met. The number of occurrences and implementation rate may be for a predetermined period, for example, the past year.

[0032] Here, the process of generating timetable replanning rule information will be explained. Fig. 6 is a diagram showing an overview of the rule extraction process in the rule analysis unit in the traffic management device according to embodiment 1. The rule analysis unit 23 has a rule extraction database generation unit 231 and a timetable replanning rule extraction unit 232.

[0033] The rule extraction database generation unit 231 generates the rule extraction database 236 from actual operation information, user usage information, bus schedule information, and train rescheduling history information. The rule extraction database generation unit 231 generates the rule extraction database 236 according to item definition information, which defines predetermined items whose values ​​are true or false and a method for calculating values ​​corresponding to these items. In the example of FIG. 6 , actual operation information is obtained from the train operation information database 221, user usage information is obtained from at least one of the train operation information database 221 and the people flow information database 222, train schedule information is obtained from the train schedule database 223, and train rescheduling history information is obtained from the train rescheduling history database 224. In one example, the rule extraction database 236 may be generated by dividing it into multiple databases classified by implementation station. Dividing and storing the databases enables faster subsequent processing.

[0034] In the first embodiment, if the relationship between the conclusion that a timetable reordering was implemented and the conditions or circumstances at the time of the timetable reordering were the prerequisites, and the conclusion being implemented if the prerequisites are met, can be established with a probability equal to or greater than a predetermined value, this relationship is extracted as a timetable reordering rule. Hereinafter, the extracted conditions or circumstances at the time of the timetable reordering, among the items in the rule extraction database 236, are referred to as the antecedent, and the details of the timetable reordering implemented when the prerequisites indicated in the antecedent are met are referred to as the conclusion. The antecedent does not have to be a single item among the items in the rule extraction database 236, but may be a combination of multiple items. Furthermore, the conclusion may also be a single item or multiple items. Therefore, the item definition information includes an item that serves as the antecedent and an item that serves as the conclusion.

[0035] Furthermore, when extracting a traffic rescheduling rule, the relationship between the target train, which is the train 51 to be targeted, and the trains 51 before and after the target train is taken into consideration. For this reason, the item definition information, more specifically, the items that form the antecedent part, include not only items related to the target train, but also items related to the trains 51 running before and after the target train.

[0036] In one example, the rule extraction database 236 is a database having antecedent items including items selected from the items of operation record information, user usage information, and bus schedule information, and items obtained by combining multiple items, and conclusion items including items generated from timetable rescheduling history information and constituting the details of timetable rescheduling. Furthermore, items other than the number identifying the record corresponding to one row in which a value for each item in the rule extraction database 236 has been entered are selected so that their values ​​are represented as true or false, i.e., "1" or "0."

[0037] Fig. 7 is a diagram showing an example of a rule extraction database. The rule extraction database 236 shown in Fig. 7 includes information on each item, such as number, type_local, type_express, direction_up, direction_down, departure station_A, departure station_B, train in question_delay 1 station before_60 seconds or more, train in question_delay 2 stations before_60 seconds or more, occupancy rate_120% or more, traffic rescheduling operation_1, traffic rescheduling operation_2, implementation station_1, implementation station_2, etc.

[0038] In Figure 7, the items Type_Local, Type_Express, Direction_Up, Direction_Down, Departure Station_A, Departure Station_B, Train_1 Delay before Station_60s or More, Train_2 Delay before Station_60s or More, and Occupancy Rate_120% or More correspond to the antecedent items. The items Operation_1, Operation_2, Implementation Station_1, and Implementation Station_2 correspond to the conclusion items.

[0039] The number field is an identifier that uniquely identifies a record corresponding to one row in the rule extraction database 236. In Figure 7, numbers are represented as No. The same applies to Figure 8 and subsequent figures. The type_local field indicates whether the type of train 51 is local or not. The type_express field indicates whether the type of train 51 is express or not. The direction_up field indicates whether the direction of travel of train 51 is up or not. The direction_down field indicates whether the direction of travel of train 51 is down or not. The departure station_A field indicates whether the departure station of train 51 is station A or not. The departure station_B field indicates whether the departure station of train 51 is station B or not. The train_delay one station before_60s or more field indicates whether the delay time one station before the train 51 targeted by the record indicated by the number field is 60s or more. The Train_Delay 2 Stations Ahead_60s or More field indicates whether the delay time of the train 51 two stations before the target train in the record indicated by the Number field is 60s or more. The Occupancy Rate_120% or More field indicates whether the occupancy rate of the train 51 stored in the record indicated by the Item field is 120% or more.

[0040] The item "Train rescheduling operation_1" indicates whether or not a train rescheduling operation_1 has been performed. The item "Train rescheduling operation_2" indicates whether or not a train rescheduling operation_2 has been performed. The item "Implementation station_1" indicates whether or not a train rescheduling operation has been performed at implementation station_1. The item "Implementation station_2" indicates whether or not a train rescheduling operation has been performed at implementation station_2. Each item of "Train rescheduling operation_1" and "Train rescheduling operation_2" corresponds to a specific rescheduling content. Each item of "Implementation station_1" and "Implementation station_2" corresponds to a specific station name.

[0041] The items in the rule extraction database 236 shown in FIG. 7 are merely examples, and items that are thought to be relevant to the content of train rescheduling can be arbitrarily generated from the items in the operation performance information and user usage information. In addition to these items, the rule extraction database 236 may also include an item indicating whether the delay time one station before or two stations before the train 51 targeted by the record indicated by the number item is 120 seconds or more, 180 seconds or more, ..., etc. In this case, the items may be set so that the delay time one station before or two stations before the train 51 overlaps, such as 60 seconds or more, 120 seconds or more, 180 seconds or more, ..., n seconds or more. The rule extraction database 236 may also include items such as an item indicating the degree of delay at the departure station of the train 51 targeted by the record indicated by the number item, an item indicating the degree of platform congestion obtained from people flow information at the departure station, and an item indicating the net number of passengers entering the departure station.

[0042] As described above, in the rule extraction database 236, information such as delay information and type is input for the target train, which is the train 51 that serves as the reference for the record, and for the trains 51 before and after the target train. The items that make up the premise part of the rule extraction database 236 include the type, running direction, delay information, etc. of the target train, as well as the type, running direction, delay information, etc. of the train 51 running before the target train, and the type, running direction, delay information, etc. of the train 51 running after the target train. In order to distinguish the item for the train 51 running before the target train from the item for the target train, the item for the train 51 running after the target train is written as "preceding train_(item)" in one example, and in order to distinguish it from the item for the target train, the item for the train 51 running after the target train is written as "following train_(item)" in one example. In this way, by generating items of information such as delay information and type of train for the target train and the trains 51 running before and after the target train, it is possible to extract the prerequisites for implementing the train schedule changes by combining not only events occurring on the target train but also events occurring on the trains 51 running before and after the target train.

[0043] Among the items in the rule extraction database 236 shown in FIG. 7, the values ​​of the items type_local, type_express, direction_up, direction_down, departure station_A, and departure station_B are acquired from the operation information in the operation information database 221 or the train schedule information in the train schedule database 223. In addition, the value of the item "Delay of train_one station before_60 seconds or more" can be calculated using the operation information in the operation information database 221 and the train schedule information in the train schedule database 223. Specifically, by calculating the difference between the departure time of the train one station before departure station_A in the operation information and the departure time in the train schedule information, it is possible to determine whether the delay of train_one station before_60 seconds or more is 60 seconds or more. The value of the item "Delay of train_two stations before_60 seconds or more" can be calculated in a similar manner. The value of the item "Occupancy rate_120% or more" can be acquired from the operation information in the operation information database 221.

[0044] Normally, train traffic rescheduling occurs very infrequently. On the other hand, the rule extraction database 236 contains data on all trains 51 that have operated, regardless of whether or not they have been rescheduled, and therefore the amount of data is enormous. Although a rule extraction method such as association analysis could be applied to such a huge amount of data in the rule extraction database 236, in this case, a brute force search is performed on all data, resulting in a huge amount of calculation. For this reason, it is desirable to use a method suitable for extracting rules for items that occur infrequently.

[0045] Therefore, in the first embodiment, the rule extraction database generation unit 231 generates the timetable replanning content rule extraction database 237, which is a database that extracts only records in which one or more of the multiple items that make up the conclusion part have a value of true, i.e., "1", from the rule extraction database 236. In other words, the timetable replanning content rule extraction database 237 extracts only records in which the value of an item related to timetable replanning, i.e., an item corresponding to timetable replanning history information, has a value of true. For this reason, the timetable replanning content rule extraction database 237 does not include records in which timetable replanning has not occurred.

[0046] Fig. 8 is a diagram showing an example of a database for extracting rules containing timetable replanning contents. The database 237 for extracting rules containing timetable replanning contents shown in Fig. 8 is obtained by extracting records containing "1" in the conclusion part from the rule extraction database 236 which contains all the data in Fig. 7.

[0047] The database for rule extraction 236 and the database for timetable replanning content rule extraction 237 are temporarily stored in the storage unit 22, for example.

[0048] Returning to Figure 6, the timetable replanning rule extraction unit 232 extracts timetable replanning rules using a data mining technique, using a rule extraction database 236 containing all data and a timetable replanning content inclusion rule extraction database 237 containing only items related to timetable replanning. The data mining technique extracts conditions for the occurrence of an event in the conclusion from the antecedent part, using the X⇒Y relationship, which states that when condition X is satisfied, condition Y is also frequently satisfied. Note that when extracting timetable replanning rules, data under special circumstances, such as changes in operation due to equipment failure or construction, may be excluded from the rule extraction database 236 and the timetable replanning content inclusion rule extraction database 237, as necessary.

[0049] The timetable rescheduling rule extraction unit 232 first uses a data mining technique to extract timetable rescheduling rules, which are combinations of one or more related items in the premise section and one or more related items in the conclusion section, using the timetable rescheduling content rule extraction database 237. More specifically, the timetable rescheduling rule extraction unit 232 uses the timetable rescheduling content rule extraction database 237 to extract timetable rescheduling rules, which are combinations of one or more related items in the premise section, corresponding to the actual operation data, user usage data, and schedule data, and one or more related items in the schedule rescheduling history data, for which the relatedness indicator is equal to or greater than a predetermined reference value. Taking FIG. 8 as an example, if a relationship is found between the premise section, "Delay of the train one station before the departure station" at "Departure Station B," and the conclusion section, "Schedule rescheduling operation 2" at "Implementation Station 2," the combination of the premise section and the conclusion section is extracted as a timetable rescheduling rule. The premise section may contain one or more items, as long as the relatedness indicator is equal to or greater than a reference value. The extracted antecedent items include those indicating delay information for the target train, those indicating delay information for trains 51 running before and after the target train, those indicating the usage status of passengers, and combinations of these. Hereinafter, the antecedent items of the extracted timetable rescheduling rules will also be referred to as prerequisites, and the conclusion items of the extracted timetable rescheduling rules will also be referred to as timetable rescheduling details. Such extraction of timetable rescheduling rules can be performed using known data mining techniques.

[0050] The timetable replanning rule extraction unit 232 extracts the number of past occurrences of the prerequisites of the extracted timetable replanning rule from the rule extraction database 236. Specifically, the timetable replanning rule extraction unit 232 calculates the number of records in which the antecedent item or combination of items of the extracted timetable replanning rule is "1" from the rule extraction database 236 containing all data as the occurrence number. This makes it possible to determine the number of past occurrences of the prerequisites, including the antecedent item or combination of items for which timetable replanning has been implemented and the antecedent item or combination of items for which timetable replanning has not been implemented. The timetable replanning rule extraction unit 232 may calculate the number of past occurrences of the prerequisites for a specified period, such as up to one year prior to the date on which the timetable replanning rule extraction process is performed. By calculating the number of past occurrences of the prerequisites for a specified period, the calculation processing in the timetable replanning rule extraction unit 232 can be reduced.

[0051] Furthermore, the timetable replanning rule extraction unit 232 extracts the number of implementations, which is the number of times the extracted timetable replanning rule has been implemented, from the timetable replanning content inclusion rule extraction database 237. Specifically, the timetable replanning rule extraction unit 232 calculates, as the number of implementations, the number of records in which the item or combination of items that forms the antecedent part of the extracted timetable replanning rule and the item or combination of items that forms the conclusion part are "1" from the timetable replanning content inclusion rule extraction database 237. When the timetable replanning rule extraction unit 232 is calculating the number of past occurrences of the antecedent part for a specified period, it also calculates the number of implementations for the specified period.

[0052] The timetable replanning rule extraction unit 232 calculates the implementation rate as the proportion of timetable replanning actions taken when the preconditions of the extracted timetable replanning rule are met. Specifically, the timetable replanning rule extraction unit 232 calculates the implementation rate for the extracted timetable replanning rule, which is the proportion of the number of times the extracted timetable replanning rule has been implemented to the number of times the preconditions have occurred in the past. The timetable replanning rule extraction unit 232 then generates timetable replanning rule information including the preconditions and timetable replanning actions of the extracted timetable replanning rule, the number of times the preconditions have occurred in the past, and the implementation rate of the timetable replanning actions, and stores this in the timetable replanning rule information database 225.

[0053] FIG. 9 is a diagram showing an example of timetable replanning rule information. The timetable replanning rule information shown in FIG. 9 includes information in the following fields: rule number, precondition, timetable replanning content, number of occurrences, and implementation rate. The rule number field represents identification information that uniquely identifies the timetable replanning rule information. The precondition field represents the precondition of the timetable replanning rule. The precondition of the timetable replanning rule is an item or combination of items that form the antecedent part of the rule extraction database 236 or the timetable replanning content-containing rule extraction database 237. The timetable replanning content field represents the timetable replanning content of the timetable replanning rule. The timetable replanning content is an item or combination of items that form the conclusion part of the rule extraction database 236 or the timetable replanning content-containing rule extraction database 237. The number of occurrences field represents the number of times the content specified in the precondition has occurred. Here, this is the number of occurrences within the past year. The implementation rate field represents the number of times the timetable replanning content has been implemented when the content specified in the precondition has occurred. Note that in this example, the number of occurrences and implementation rate fields are used as examples, but other indicators may also be used. In this way, the timetable rescheduling rule information is defined using the timetable rescheduling rule and indicators such as the number of occurrences and implementation rate of the timetable rescheduling rule, so that the necessity of each timetable rescheduling rule can be presented to the dispatcher.

[0054] Returning to Figure 1, the timetable replanning rule information database 225 stores timetable replanning rule information. As described above, the timetable replanning rule information includes timetable replanning rules that include preconditions and timetable replanning details that can be implemented when the preconditions are met, as well as the number of times the preconditions have occurred in the past and the implementation rate of the timetable replanning details. An example of timetable replanning rule information is shown in Figure 9.

[0055] The timetable replanning determination unit 24 generates timetable replanning rule candidate information to be used in issuing a timetable replanning instruction for the train 51 based on the timetable replanning rule, actual operation information, and congestion level information or station facility data. The process performed by the timetable replanning determination unit 24 is described in detail below. The timetable replanning determination unit 24 determines whether a relevant timetable replanning rule exists based on current operation history information, user usage information, and train schedule information. Specifically, the timetable replanning determination unit 24 uses operation information, pedestrian flow information, and train schedule information to determine whether the operation history information and user usage information at the time of data acquisition—in this example, the operation information and pedestrian flow information—conform to the prerequisites of the timetable replanning rule stored in the timetable replanning rule information database 225. Because the operation information and pedestrian flow information for each train 51 are acquired by the data acquisition unit 21, the timetable replanning determination unit 24 can determine whether a timetable replanning rule applies in real time. In other words, in order to resolve a timetable disruption, the timetable replanning determination unit 24 determines whether a timetable replanning rule applies and generates timetable replanning rule candidate information during commercial operation hours. If a corresponding timetable replanning rule exists, the timetable replanning determination unit 24 generates timetable replanning rule information including the corresponding timetable replanning rule as timetable replanning rule candidate information, and outputs the timetable replanning rule candidate information to the output processing unit 25. The timetable replanning rule candidate information includes a timetable replanning rule including preconditions and timetable replanning details that can be implemented when the preconditions are met, the number of times the preconditions have occurred in the past, and the implementation rate of the timetable replanning details.

[0056] When extracting timetable replanning rule information, the timetable replanning determination unit 24 may filter the extracted timetable replanning rule information to generate timetable replanning rule candidate information. In one example, the timetable replanning determination unit 24 may generate timetable replanning rule candidate information to include, from the extracted timetable replanning rule information, timetable replanning rule information whose implementation rate is equal to or greater than a first threshold, which is a predetermined threshold, and output the generated information to the output processing unit 25. Here, if the implementation rate of all the extracted timetable replanning rule information is below the threshold, there is no timetable replanning rule information to present, and so the timetable replanning determination unit 24 does not generate timetable replanning rule candidate information or output the timetable replanning rule candidate information to the output processing unit 25.

[0057] The output processing unit 25 outputs the timetable replanning rule candidate information input from the timetable replanning determination unit 24 to a predetermined output destination. In the example of FIG. 1, the output processing unit 25 outputs the timetable replanning rule candidate information to the information processing terminal 53 operated by the dispatcher, and the timetable replanning rule candidate information is displayed on the display unit of the information processing terminal 53. In other words, the timetable replanning rule candidate information is presented to the dispatcher. In this case, the output processing unit 25 transmits the timetable replanning rule candidate information to the information processing terminal 53 via a network (not shown). As a result, the dispatcher implements a timetable replanning content that is deemed appropriate for the current operation situation from the presented timetable replanning rule candidate information. In other words, the dispatcher instructs the traffic management device 1A to implement the timetable replanning content via the information processing terminal 53. When the timetable replanning content is implemented, timetable replanning data including the implemented timetable replanning content is transmitted from the information processing terminal 53 to the traffic management device 1A. Furthermore, when the dispatcher is operating the traffic management device 1A, the output processing unit 25 outputs the timetable replanning rule candidate information to the display device 54 connected to the traffic management device 1A. In this case, the dispatcher instructs the traffic management device 1A to implement the traffic replanning content that is deemed appropriate for the current operational situation from the traffic replanning rule candidate information presented via an input unit (not shown) of the traffic management device 1A. The dispatcher also inputs traffic replanning data including the implemented traffic replanning content into the traffic management device 1A.

[0058] The display unit of the information processing terminal 53 may display the extracted schedule replanning rule candidate information as is, or may display schedule replanning rule information deemed important among the schedule replanning rule candidate information in a different manner from the other schedule replanning rule candidate information. For example, schedule replanning rule information whose implementation rate is equal to or exceeds a predetermined second threshold may be highlighted. Highlighting may be achieved by changing the background color, blinking the background, changing the text color, making the text bold, blinking the text, or other methods to make the information more noticeable than other parts. In this case, the schedule replanning determination unit 24 generates schedule replanning rule candidate information instructing the display of schedule replanning rule information whose implementation rate is equal to or exceeds the second threshold in a different manner from the other parts, and the output processing unit 25 outputs this schedule replanning rule candidate information. For example, the second threshold is an implementation rate determined by a user, such as the operator of the traffic management device 1A, as important based on past schedule replanning content. The second threshold may be the same as or different from the first threshold.

[0059] FIG. 10 is a diagram showing an example of a timetable replanning rule candidate information screen presented to a dispatcher. The timetable replanning rule candidate information screen shown in FIG. 10 shows an example in which extracted timetable replanning rule candidate information is displayed regardless of the implementation rate value. The timetable replanning rule candidate information screen shown in FIG. 10 includes timetable replanning rule candidate information. The timetable replanning rule candidate information includes information on each of the following items: candidate number, prerequisite, timetable replanning content, number of occurrences, and implementation rate. The candidate number item is identification information that uniquely identifies the timetable replanning rule information in the generated timetable replanning rule candidate information. The other items are the same as the items in the timetable replanning rule information in FIG. 9. The timetable replanning rule candidate information screen shown in FIG. 10 shows an example in which timetable replanning rules with an implementation rate of 80% or more are highlighted.

[0060] The first row of the table showing the candidate train rescheduling rule information shown in Figure 10 shows an example in which, when the precondition is "3 minutes delay when departing from Station A, and the following train departs Station C on schedule," a train rescheduling rule that implements "Station D: change of operating order with the following train" has occurred "18 times" in the past year, and the implementation rate is "88.8%."

[0061] Referring to FIG. 10, some candidate numbers, such as "1" and "2," include a delay at the departure station as a precondition, while others, such as "3," include only user usage information as a precondition without including a delay at the departure station. In Patent Document 1, no traffic rescheduling rule is proposed unless a train 51 is delayed. However, in the first embodiment, in addition to delay information, user usage information, i.e., congestion information such as the number of passengers on train 51 and the occupancy rate, or people flow information indicating the number of passengers at station 52, is also used to extract traffic rescheduling rules. Therefore, a traffic rescheduling rule that includes only user usage information as a precondition can be generated. Even if the congestion level of train 51 or station 52 obtained from such user usage information is predicted to exceed a reference value, the need for traffic rescheduling can be presented to the dispatcher. For this reason, in Patent Document 1, even if the congestion level of train 51 or station 52 exceeds a reference value, no timetable rescheduling rules are presented unless a delay occurs to train 51. However, in Embodiment 1, it is possible to present timetable rescheduling rules to the dispatcher even when the congestion level of train 51 or station 52 exceeds a reference value. As a result, before the congestion level of train 51 or station 52 becomes serious and a significant delay occurs to train 51, timetable rescheduling rule information based on current user usage information can be provided, and timetable rescheduling can be implemented based on this timetable rescheduling rule information. As a result, it is possible to prevent delays of train 51 based on user usage information.

[0062] Returning to FIG. 1, the display device 54 connected to the traffic management device 1A is a device that displays information. Examples of the display device 54 include a liquid crystal display device, an organic EL display device, etc. In this example, the display device 54 displays the candidate traffic replanning rule information output by the output processing unit 25. This makes it possible to provide a dispatcher who is managing traffic using the traffic management device 1A with traffic replanning rules that can currently be implemented. Note that while the example in FIG. 1 shows an example in which the display device 54 is connected to the outside of the traffic management device 1A, the traffic management device 1A may also be configured to have the display device 54 built in. The same applies to the following embodiments.

[0063] In the example shown in FIG. 1, the traffic management device 1A is connected to a display device 54, and a dispatcher uses the traffic management device 1A to perform traffic management and traffic rescheduling of trains 51. In this case, the traffic management device 1A is a single information processing device equipped with the display device 54 and an input unit (not shown). In this case, the dispatcher is located in the same place as the traffic management device 1A. On the other hand, the dispatcher may be located in a different place from the traffic management device 1A. In other words, as shown in FIG. 1, the traffic management device 1A and an information processing terminal 53 operated by the dispatcher may be connected via a network. In this case, the traffic management device 1A is configured, for example, by one or more cloud servers or on-premise servers. A cloud server is a server built in a cloud environment that includes computer resources provided by a cloud service platform.

[0064] Next, a method for supporting timetable replanning in the traffic management device 1A will be described. FIG. 11 is a flowchart showing an example of the steps of the method for supporting timetable replanning according to the first embodiment. The data acquisition unit 21 determines whether the current time is within commercial operating hours (step S11). If the current time is outside commercial operating hours (No in step S11), the system switches to timetable replanning rule extraction mode, and the timetable replanning rule extraction process is executed (step S12). That is, the mode in which the timetable replanning rule extraction process is executed becomes the timetable replanning rule extraction mode. The process then ends. On the other hand, if the current time is within commercial operating hours (Yes in step S11), the system switches to timetable replanning determination mode, and the timetable replanning determination process is executed (step S13). That is, the mode in which the timetable replanning determination process is executed becomes the timetable replanning determination mode. The process then ends.

[0065] In this way, the timetable rescheduling rule extraction process is executed in the background outside of commercial operating hours, and the timetable rescheduling determination process is executed during commercial operating hours. This prevents computational and other processes that require a heavy load from being performed during commercial operating hours, thereby reducing the load on the traffic management device 1A during commercial operations.

[0066] Next, details of the timetable rescheduling rule extraction method for performing the timetable rescheduling rule extraction process in step S12 of Fig. 11 will be described. Fig. 12 is a flowchart showing an example of the steps of the timetable rescheduling rule extraction method. First, the data acquisition unit 21 acquires running history data from the train 51 (step S31), converts the running history data into operation information on a station-to-station basis, and stores the information in the operation information database 221 (step S32). The operation information includes running history information and congestion degree information of the train 51.

[0067] The data acquiring unit 21 acquires station facility data from the station 52 (step S33), extracts people flow information from the station facility data, and stores the information in the people flow information database 222 (step S34). If the station facility data is ticket gate data, the data acquiring unit 21 extracts the number of people entering and exiting the station 52 during a predetermined period from the ticket gate data and stores the information in the people flow information database 222 as people flow information. If the station facility data is video data from a camera installed in the station 52, the data acquiring unit 21 estimates the number of people passing through each section within the station 52 from the video data and stores the estimated number of people passing through each section within the station 52 as people flow information in the people flow information database 222. If the station facility data is data estimating the number of people passing through each section within the station 52 from the video data, the data acquiring unit 21 stores the station facility data in the people flow information database 222 as people flow information.

[0068] The data acquisition unit 21 acquires the bus schedule data from the operation control unit 11 (step S35), converts the bus schedule data into bus schedule information for each station, and stores the information in the bus schedule database 223 (step S36).

[0069] When a timetable rescheduling is implemented, the data acquisition unit 21 acquires timetable rescheduling data from the information processing terminal 53 (step S37), and stores the acquired timetable rescheduling data in the timetable rescheduling history database 224 (step S38).

[0070] The order in which the processing of steps S31 and S32, the processing of steps S33 and S34, the processing of steps S35 and S36, and the processing of steps S37 and S38 are performed does not have to be the order shown in Fig. 12, and the orders may be reversed, or the processing may be performed simultaneously in parallel. The processes from steps S31 to S34 correspond to steps of acquiring data from trains 51 and, if necessary, stations 52, and generating operation performance information and congestion level information or station facility data.

[0071] Next, the rule analysis unit 23 executes a process of generating timetable rescheduling rule information (step S39) to generate timetable rescheduling rule information using the operation information stored in the operation information database 221, the pedestrian flow information stored in the pedestrian flow information database 222, the timetable information stored in the timetable database 223, and the timetable rescheduling history information stored in the timetable history database 224. The process of step S39 corresponds to a step of extracting a timetable rescheduling rule for the train 51 based on the operation performance information indicating the operation performance of the train 51, the congestion degree information or station facility data indicating the degree of congestion of the train 51, the timetable information which is information indicating the operation plan of the train 51, and the timetable rescheduling history information including the details of timetable rescheduling implemented in the past.

[0072] Here, the details of the timetable replanning rule information generation process will be described. Fig. 13 is a flowchart showing an example of the processing steps of the timetable replanning rule information generation method. The rule extraction database generation unit 231 of the rule analysis unit 23 generates a rule extraction database 236 using the operation information stored in the operation information database 221, the pedestrian flow information stored in the pedestrian flow information database 222, the bus schedule information stored in the bus schedule database 223, and the timetable replanning history information stored in the bus schedule history database 224 (step S51). The rule extraction database 236 has an antecedent part including multiple items indicating prerequisites, as described above, and a conclusion part including multiple items indicating a conclusion. The rule extraction database 236 is a database configured to have predetermined items whose values ​​are true or false, i.e., "1" or "0," according to item definition information.

[0073] The rule extraction database generation unit 231 extracts records from the rule extraction database 236 in which any of the items constituting the conclusion part is "1", and sets the extracted records as the timetable rescheduling content rule extraction database 237 (step S52).

[0074] Next, the timetable rescheduling rule extraction unit 232 uses the timetable rescheduling content rule extraction database 237 to extract timetable rescheduling rules that are combinations of one or more related items in the premise part and one or more items in the conclusion part using a data mining technique (step S53).

[0075] Thereafter, the timetable replanning rule extraction unit 232 extracts the number of times the prerequisites of the extracted timetable replanning rules have occurred in the past from the rule extraction database 236 (step S54). In addition, the timetable replanning rule extraction unit 232 extracts the number of times the extracted timetable replanning rules have been implemented from the timetable replanning content-containing rule extraction database 237 (step S55).

[0076] Next, the timetable replanning rule extraction unit 232 calculates the implementation rate of the timetable replanning details for the extracted timetable replanning rule from the number of times the prerequisites occur and the number of times the timetable replanning rule is implemented (step S56).The timetable replanning rule extraction unit 232 then generates timetable replanning rule information including the prerequisites, the timetable replanning details, the number of times the prerequisites occur, and the implementation rate of the timetable replanning details (step S57).This completes the timetable replanning rule information generation method, and the process returns to FIG.

[0077] Returning to FIG. 12, the rule analysis unit 23 stores the timetable replanning rule information in the timetable replanning rule information database 225 (step S40), and the timetable replanning rule extraction method ends.

[0078] 12 and 13 are merely examples, and the method for extracting timetable rules is not limited thereto. In one example, if station 52 is unable to transmit station facility data to traffic control device 1A, the processes of steps S33 and S34 are omitted. In this case, the running performance data must include the congestion degree. Furthermore, although the method for extracting timetable rules is performed outside of commercial operating hours, in practice, the processes of steps S31 to S38 may be performed during commercial operating hours, and the processes from step S39 onward may be performed outside of commercial operating hours.

[0079] Next, the details of the timetable rescheduling determination method for performing the timetable rescheduling determination process in step S13 of Fig. 11 will be described. Fig. 14 and Fig. 15 are flowcharts showing an example of the procedure of the timetable rescheduling determination method. First, the data acquisition unit 21 acquires running performance data from the train 51 (step S71) and converts the running performance data into operation information for each station (step S72). The operation information includes running performance information and congestion degree information.

[0080] The data acquiring unit 21 acquires station facility data from the station 52 (step S73) and extracts people flow information from the station facility data (step S74). If the station facility data is ticket gate data, the data acquiring unit 21 extracts the number of people entering and exiting the station 52 during a predetermined period from the ticket gate data. If the station facility data is video data from a camera installed at the station 52, the data acquiring unit 21 uses the video data to estimate the number of people passing through each section within the station 52, as the people flow information. If the station facility data is data obtained by estimating the number of people passing through each section within the station 52 from the video data, the data acquiring unit 21 uses the station facility data as the people flow information.

[0081] The data acquisition unit 21 acquires bus schedule information from the bus schedule database 223 (step S75).

[0082] Next, the timetable replanning determination unit 24 sets one train 51 as the target train, and by referring to the train schedule information, links the train 51 running in front of the target train and the train 51 running behind it on the train schedule (step S76). The timetable replanning determination unit 24 searches the timetable replanning rule information database 225 for a timetable replanning rule that corresponds to the operation status, congestion information, and pedestrian flow information of the target train and the linked train 51 (step S77). In one example, the timetable replanning determination unit 24 searches whether there is a condition obtained from the operation status, congestion information, and pedestrian flow information of the target train and the linked train 51 that corresponds to the prerequisite of the timetable replanning rule. Then, the timetable replanning determination unit 24 repeatedly executes the procedures from step S76 to step S77 for all trains 51 acquired by the data acquisition unit 21.

[0083] Thereafter, the timetable replanning determination unit 24 determines whether a corresponding timetable replanning rule exists (step S78). If a corresponding timetable replanning rule exists (Yes in step S78), the timetable replanning determination unit 24 generates timetable replanning rule candidate information including the corresponding timetable replanning rule, the number of occurrences, and the implementation rate (step S79). The processing from step S76 to step S79 corresponds to the steps of generating timetable replanning rule candidate information to be used for issuing a timetable replanning instruction for the train 51, based on the timetable replanning rule, operation performance information, and congestion level information or station facility data.

[0084] Thereafter, the output processing unit 25 outputs the timetable replanning rule candidate information (step S80). In one example, the output processing unit 25 outputs the timetable replanning rule candidate information to the information processing terminal 53. In another example, the output processing unit 25 outputs the timetable replanning rule candidate information to the display device 54 connected to the traffic management device 1A. As a result, the timetable replanning rule candidate information is displayed on the display unit of the information processing terminal 53 or the display device 54 connected to the traffic management device 1A and presented to the dispatcher. Thereafter, or if no corresponding timetable replanning rule exists in step S78 (No in step S78), the timetable replanning determination method ends.

[0085] In the above example, running history data is acquired from the train 51, and station facility data is acquired from the station 52. In the first embodiment, the running history data and station facility data may have any content as long as operation history information and user usage information can be generated. In one example, when the congestion degree of the train 51 is used as the user usage information, the operation history information and user usage information can be generated from the running history data acquired from the train 51, so the data acquisition unit 21 does not need to acquire station facility data from the station 52.

[0086] In another example, when the degree of congestion of train 51 and at least one of ticket gate entry / exit record data and OD data are used as user usage information, data acquisition unit 21 acquires operation performance information from the running performance data of train 51 and acquires at least one of ticket gate entry / exit record data and OD data from station 52 as station facility data.

[0087] In another example, it may not be possible to obtain ticket gate entry / exit record data and OD data from the station 52. In such cases, the degree of congestion of the train 51 and video data from a camera installed in the premises of the station 52 can be used as user usage information. When video data is used, the video data acquired from the camera may be transmitted as is to the traffic management device 1A as station facility data, or a device on the station 52 side may generate people flow data from the video data acquired from the camera and transmit the people flow data to the traffic management device 1A as station facility data. When the video data is transmitted as station facility data, the data acquisition unit 21 of the traffic management device 1A estimates the number of people passing through each section in the premises of the station 52 from the acquired video data to generate people flow information and stores the generated people flow information in the people flow information database 222. When the people flow data generated from the video data is transmitted as station facility data, the people flow data is acquired from the station facility data and stored in the people flow information database 222 as people flow information. In this way, even if ticket gate entry / exit record data or OD data is not available, the usage status of users at station 52 can be estimated using video data from cameras installed at station 52, and the estimated data can be used to perform the operation rescheduling rule extraction process or operation rescheduling determination process. In addition, movement history data acquired by the GPS function of portable information terminals carried by passengers, payment data from IC cards, etc. may be used instead of ticket gate entry / exit record data or OD data.

[0088] Furthermore, the user usage information may be a combination of congestion level, ticket gate entry / exit record data or OD data, and video data or people flow data estimated from the video data. Also, as will be explained in the third embodiment, if congestion level cannot be obtained, only station facility data may be used as user usage information.

[0089] As described above, in the traffic management device 1A according to the first embodiment, the rule analysis unit 23 uses data mining techniques to extract correlations between antecedents, including the conditions or circumstances under which a traffic replanning was implemented, and conclusions, which are the details of the traffic replanning implemented when the preconditions indicated in the antecedents are met, from the actual traffic performance information, user usage information, train schedule information, and traffic replanning history information. The rule analysis unit 23 then stores the correlations as traffic replanning rule information in the traffic replanning rule information database 225. The traffic replanning determination unit 24 determines whether a traffic replanning rule corresponding to the current actual traffic performance information and user usage information exists, and if so, outputs traffic replanning rule candidate information including the extracted traffic replanning rule. This has the effect of enabling traffic replanning support for train 51 not only when a delay occurs in train 51, but also when a high probability of a delay is predicted. In particular, it is possible to extract a traffic rescheduling rule in which user usage information, including congestion information on train 51 or pedestrian flow information at station 52, which may be the cause of a delay of train 51, is used as the premise, and the traffic rescheduling content is used as the conclusion. Therefore, when a delay of train 51 occurs or is predicted due to user usage information, the traffic rescheduling content can be presented to the dispatcher before a major delay occurs. In other words, the user usage information can be used to prevent delays of train 51 from occurring. In this way, by utilizing other user information, such as congestion information or pedestrian flow information at station 52, which is operation information other than service delays, it becomes possible to propose traffic rescheduling content that takes congestion into consideration even for situations that are unlikely to manifest as changes in operation, such as delays.

[0090] Embodiment 2 16 is a diagram schematically illustrating an example of the configuration of a timetable replanning support system according to embodiment 2. The same components as those described in embodiment 1 are denoted by the same reference numerals, and their description will be omitted. The timetable replanning support system 5B includes an operation management device 1B and a timetable replanning support device 2B.

[0091] The traffic management device 1B is a device that manages the operation of a plurality of trains 51 on a railway. The traffic management device 1B is connected to a timetable replanning support device 2B, each of the plurality of trains 51, and an information processing terminal 53 via a network. The traffic management device 1B is a device that has the functions of the traffic management unit 11 of the traffic management device 1A in FIG. 1. In the second embodiment, the traffic management device 1B acquires running history data from the trains 51. Then, the traffic management device 1B transmits the running history data acquired from the trains 51 to the timetable replanning support device 2B.

[0092] The traffic replanning support device 2B is a device that supports traffic replanning work to restore a schedule disruption caused by a delay of a train 51 due to weather, earthquake, accident, etc., or a delay of a train 51 caused by the degree of congestion on the train 51 or the user usage status of a station 52 to a normal state. Note that the traffic replanning work may be performed to suppress a schedule disruption that may occur due to a delay of a train 51 caused by the degree of congestion on the train 51 or the user usage status of a station 52, i.e., to suppress the occurrence of a schedule disruption in advance. The traffic replanning support device 2B is connected to the traffic management device 1B, each of the multiple stations 52, and an information processing terminal 53 via a network. The traffic replanning support device 2B is the traffic management device 1A of FIG. 1 from which the function of the traffic management unit 11 has been removed. Therefore, the configuration of the traffic replanning support device 2B is the same as the configuration of the traffic management device 1A described in the first embodiment. However, in the second embodiment, the data acquisition unit 21 acquires running performance data from the operation management device 1B rather than from each of the multiple trains 51, and the output processing unit 25 also outputs the candidate operation rescheduling rule information to the operation management device 1B, which are different from the first embodiment.

[0093] In one example, the timetable replanning support device 2B is configured by one or more cloud servers. A cloud server is a server built in a cloud environment that includes computer resources provided by a cloud service platform. Note that the timetable replanning support device 2B may be a server other than a cloud server, and in one example, may be an on-premise server. Furthermore, the timetable replanning support device 2B may be a personal computer.

[0094] The method of supporting timetable replanning in the timetable replanning support device 2B is the same as that described in the first embodiment, and therefore the description thereof will be omitted. However, it differs from the first embodiment in that the running performance data is acquired not from the train 51 but from the traffic management device 1B.

[0095] Furthermore, the output processing unit 25 of the timetable replanning support device 2B may output the timetable replanning rule candidate information to the traffic management device 1B, and cause a display unit (not shown) of the traffic management device 1B to display the timetable replanning rule candidate information.

[0096] The timetable replanning support system 5B and timetable replanning support device 2B according to the second embodiment can also achieve the same effects as those of the first embodiment. Moreover, in the second embodiment, the timetable replanning support device 2B is configured to be externally attached to the traffic management device 1B. This has the effect of making it possible to utilize the existing traffic management device 1B without discarding it, and to introduce the timetable replanning support system 5B. Furthermore, since the timetable replanning support device 2B is configured as a device separate from the traffic management device 1B, it also has the effect of distributing the processing load compared to the first embodiment.

[0097] Embodiment 3 17 is a diagram schematically illustrating an example of the configuration of a timetable replanning support system according to embodiment 3. The same components as those described in embodiment 1 are denoted by the same reference numerals, and their description will be omitted. The timetable replanning support system 5C includes an operation management device 1C and a timetable replanning support device 2C.

[0098] The traffic management device 1C is a device that manages the operation of multiple trains 51 on a railway. The traffic management device 1C is connected to a traffic replanning support device 2C, an information processing terminal 53, and a signaling system 55 via a network. The traffic management device 1C is a device that has the functions of the traffic management unit 11 of the traffic management device 1A in FIG. 1. In the third embodiment, a case is illustrated in which neither the traffic replanning support device 2C nor the traffic management device 1C can acquire running history data from the train 51. In this case, the traffic management device 1C acquires train position data from the signaling system 55. The signaling system 55 can determine whether the train 51 is at a station 52 or between stations 52, and generates train position data from this information and transmits it to the traffic management device 1C. The traffic management device 1C can determine the delay status of the train 51 using the train position data transmitted from the signaling system 55. The traffic management device 1C generates running history data of the train 51 from the train position data and transmits it to the traffic replanning support device 2C. However, since the signaling system 55 cannot acquire the congestion degree of the train 51, the congestion degree is not included in the train position data. Therefore, the congestion degree is not included in the running performance data generated by the traffic management device 1C either.

[0099] The traffic replanning support device 2C is a device that supports traffic replanning work to restore a schedule disruption caused by a delay of a train 51 due to weather, earthquake, accident, etc., or a delay of a train 51 caused by the degree of congestion on the train 51 or the user usage status of a station 52 to a normal state. Note that the traffic replanning work may be performed to suppress a schedule disruption that may occur due to a delay of a train 51 caused by the degree of congestion on the train 51 or the user usage status of a station 52, i.e., to suppress the occurrence of a schedule disruption in advance. The traffic replanning support device 2C is connected to the traffic management device 1C, each of the multiple stations 52, and an information processing terminal 53 via a network. The traffic replanning support device 2C is the traffic management device 1A of FIG. 1 from which the function of the traffic management unit 11 has been removed. Therefore, the configuration of the traffic replanning support device 2C is the same as that described in the first embodiment. However, in the third embodiment, the data acquisition unit 21 acquires running performance data that does not include congestion levels from the operation management device 1C rather than from each of the multiple trains 51, and the output processing unit 25 also outputs candidate operation rescheduling rule information to the operation management device 1C, which are different from the first embodiment.

[0100] Since the running performance data does not include congestion levels, the operation information between stations converted by the data acquisition unit 21 does not include values ​​related to congestion level information. FIG. 18 is a diagram showing an example of operation information. As shown in FIG. 18, the occupancy rate field corresponding to the congestion level information in the operation information is left blank. In other words, in the third embodiment, the operation information includes actual operation information but does not include congestion level information. For this reason, the timetable replanning support device 2C according to the third embodiment must acquire station facility data from the stations 52.

[0101] In addition, in the third embodiment, since the operation information does not include congestion information, the rule analysis unit 23 extracts operation replanning rule information using the operation performance information, pedestrian flow information, bus schedule information, and operation replanning history information of the operation information. Similarly, the operation replanning determination unit 24 extracts operation replanning rules using the operation performance information, pedestrian flow information, and bus schedule information of the operation information.

[0102] In one example, the timetable replanning support device 2C is configured by one or more cloud servers. A cloud server is a server built in a cloud environment that includes computer resources provided by a cloud service platform. Note that the timetable replanning support device 2C may be a server other than a cloud server, and in one example, may be an on-premise server. Furthermore, the timetable replanning support device 2C may be a personal computer.

[0103] The method of supporting traffic replanning in the traffic replanning support device 2C is the same as that explained in the first embodiment, and therefore the explanation thereof will be omitted. However, it differs from the first embodiment in that the running performance data is acquired not from the train 51 but from the traffic management device 1C, and that the traffic information does not include congestion degree information.

[0104] Furthermore, the output processing unit 25 of the timetable replanning support device 2C may output the timetable replanning rule candidate information to the traffic management device 1C, and cause a display unit (not shown) of the traffic management device 1C to display the timetable replanning rule candidate information.

[0105] The timetable replanning support system 5C and timetable replanning support device 2C according to the third embodiment can also achieve the same effects as those of the first and second embodiments. Furthermore, in the third embodiment, the traffic management device 1C generates running history data of the train 51 using train position data from the signaling system 55 and transmits the data to the timetable replanning support device 2C. This has the effect of enabling the timetable replanning rule extraction process and the timetable replanning determination process to be executed even when running history data cannot be acquired from the train 51.

[0106] In addition, in the first and second embodiments and the fourth and fifth embodiments described below, a signaling system 55 (not shown) is connected to the traffic management devices 1A, 1B, 1D, and 1E. In the first, fourth, and fifth embodiments, the data acquisition unit 21 of the traffic management devices 1A, 1D, and 1E may generate operation information using running history data from the train 51 and train position data from the signaling system 55. In the second embodiment, the traffic management device 1B may generate running history data from the data from the train 51 and the train position data from the signaling system 55 and transmit the running history data to the traffic replanning support device 2B. In this way, even if running history data from the train 51 cannot be obtained due to a temporary equipment malfunction, the traffic history information is supplemented using the train position data from the signaling system 55, and it is possible to determine a traffic replanning rule corresponding to the current traffic history information and pedestrian flow information.

[0107] Embodiment 4 FIG. 19 is a diagram schematically illustrating an example of the configuration of a traffic management device including a timetable replanning support device according to the fourth embodiment. The same components as those described in the first embodiment are denoted by the same reference numerals, and their description will be omitted. The traffic management device 1D further includes a simulation unit 27. The simulation unit 27 performs a simulation for the timetable replanning rule determined by the timetable replanning determination unit 24 to meet the prerequisite conditions and returns the simulation results to the timetable replanning determination unit 24. In one example, when there are multiple timetable replanning rules output by the timetable replanning determination unit 24 according to the current traffic situation, the simulation unit 27 performs a simulation for each timetable replanning rule and outputs the simulation results to the timetable replanning determination unit 24. The simulation unit 27 simulates changes in the traffic situation due to the timetable replanning rule using operation performance information, user usage information, and bus schedule information up to the start of the simulation in addition to the timetable replanning rule. In one example, the simulation unit 27 performs a simulation using the traffic situation, pedestrian flow information, and bus schedule information.

[0108] The timetable replanning determination unit 24 generates timetable replanning rule candidate information using the simulation results from the simulation unit 27, and outputs it to the output processing unit 25. In one example, when there are multiple extracted timetable replanning rules, the timetable replanning determination unit 24 generates timetable replanning rule candidate information including only the timetable replanning rule with the best simulation results, and outputs the timetable replanning rule candidate information to the output processing unit 25. In one example, the timetable replanning rule with the best simulation results is the timetable that takes the shortest time to recover from a delay.

[0109] Furthermore, when passing a timetable replanning rule to the simulation unit 27, the timetable replanning determination unit 24 may pass all of the current operation information and pedestrian flow information that meet the prerequisites of the timetable replanning rule to the simulation unit 27, or may pass only those of the current operation information and pedestrian flow information that meet the prerequisites of the timetable replanning rule and whose implementation rate is equal to or exceeds a predetermined third threshold to the simulation unit 27. When those with implementation rates equal to or exceeding the third threshold are passed to the simulation unit 27, it is possible to reduce the load on the simulation unit 27, and the time required to display the timetable replanning rule candidate information can be shortened compared to when all are simulated.

[0110] The method of supporting timetable replanning in the traffic management device 1D is the same as that described in embodiment 1, and therefore its description will be omitted. However, if the answer is Yes in step S78 of Fig. 15, a process is added in which the simulation unit 27 performs a simulation of the relevant timetable replanning rule for the current traffic situation and returns the simulation result to the timetable replanning determination unit 24. Furthermore, in step S79, the timetable replanning determination unit 24 generates timetable replanning rule candidate information that includes only the timetable replanning rule with the best simulation result.

[0111] In the fourth embodiment, the simulation unit 27 simulates timetable replanning rules for which the current operation performance information and user usage information extracted by the timetable replanning determination unit 24 meet the prerequisites for the timetable replanning rules, and the timetable replanning determination unit 24 outputs the best simulation result as the timetable replanning rule candidate information. This enables the traffic management device 1D to perform timetable replanning using a timetable replanning rule that provides optimal results for the current operation conditions. Specifically, it enables the fastest delay recovery time for the current operation conditions. Furthermore, when the timetable replanning rule candidate information includes multiple timetable replanning rules, different dispatchers may select different timetable replanning rules. However, the present timetable replanning rule candidate information includes only the optimal timetable replanning rule as a result of the simulation. This allows the same timetable replanning to be performed regardless of the dispatcher, and also reduces the number of decisions the dispatcher must make. Furthermore, it enables the implementation of a standardized, optimal timetable replanning based on the simulation results, independent of the dispatcher.

[0112] 19 shows an example of a configuration in which the simulation unit 27 is provided in the traffic management device 1A of the first embodiment, but the simulation unit 27 may be provided in the timetable replanning support device 2B of the second embodiment or the timetable replanning support device 2C of the third embodiment. A similar effect can be obtained with a timetable replanning support device having such a configuration.

[0113] Embodiment 5. FIG. 20 is a diagram schematically illustrating an example of the configuration of a traffic management device including a traffic replanning support device according to the fifth embodiment. Note that the same components as those described in the first embodiment are denoted by the same reference numerals, and their description will be omitted. The traffic management device 1E further includes a simulation unit 28. The simulation unit 28 performs a real-time simulation of future traffic operations using actual traffic information, user usage information, and train schedule information. In one example, the simulation unit 28 performs a train operation simulation of the train 51 for a predetermined time from the present time using the traffic information from the traffic information database 221, the pedestrian flow information from the pedestrian flow information database 222, and the train schedule information from the train schedule database 223. In another example, the simulation unit 28 performs a train operation simulation of the train 51 for a predetermined time from the present time using the traffic information and pedestrian flow information acquired and processed in real time by the data acquisition unit 21, and the train schedule information from the train schedule database 223. The simulation unit 28 then outputs the results of the traffic simulation to the traffic replanning determination unit 24. The determined time can be set arbitrarily, but in one example it can be set to one hour.

[0114] The timetable replanning determination unit 24 further has the function of determining whether a relevant timetable replanning rule exists based on the simulated actual operation information, user usage information, and bus schedule information output from the simulation unit 28. If a timetable replanning rule corresponding to the simulated actual operation information and user usage information exists, the timetable replanning determination unit 24 outputs timetable replanning rule information including the relevant timetable replanning rule to the output processing unit 25 as timetable replanning rule candidate information. This causes the timetable replanning rule candidate information to be presented to the dispatcher via the display unit of the information processing terminal 53. If the actual operation situation becomes similar to the simulated operation situation, the dispatcher implements a timetable replanning rule selected from the presented timetable replanning rule candidate information. Examples of the operation history information and user usage information used here are simulated operation information and pedestrian flow information.

[0115] The method of supporting traffic replanning in traffic management device 1E is the same as that described in embodiment 1, and therefore its description will be omitted. However, the difference is that traffic management device 1E performs a traffic simulation from the present to a predetermined time point in the future, and also executes the traffic replanning judgment method shown in Fig. 15 on the traffic information and people flow information simulated by simulation unit 28.

[0116] In the fifth embodiment, the simulation unit 28 uses the actual operation information, user usage information, and bus schedule information to perform a train operation simulation for a predetermined period of time from the present. Furthermore, if a train operation rescheduling rule exists that matches the simulated actual operation information and user usage information, which are the results of the train operation simulation performed by the simulation unit 28, the train operation rescheduling determination unit 24 presents the corresponding train operation rescheduling rule candidate information to the dispatcher. That is, if the train operation simulation predicts future delays or worsening congestion, the train operation rescheduling rule corresponding to this prediction result is presented if available. As a result, if the condition predicted by the train operation simulation occurs in actual train operation, the dispatcher can implement train operation rescheduling using the previously presented train operation rescheduling rule candidate information. That is, even if no delay is currently occurring, if a prediction result indicates a future delay, the prediction result can be compared with the extracted train operation rescheduling rule, thereby realizing train operation rescheduling that prevents future delays or congestion.

[0117] 20 shows an example of a configuration in which the simulation unit 28 is provided in the traffic management device 1A of the first embodiment, but the simulation unit 28 may also be provided in the traffic replanning support device 2B of the second embodiment or the traffic replanning support device 2C of the third embodiment, or the simulation unit 28 may also be provided in the traffic management device 1D of the fourth embodiment. Similar effects can be obtained with traffic replanning support devices configured in this way.

[0118] Next, a description will be given of the hardware configuration for realizing the traffic management devices 1A, 1D and the traffic replanning support devices 2B, 2C according to the first to fifth embodiments. The processing functions of the traffic management devices 1A, 1D and the traffic replanning support devices 2B, 2C are realized by a processing circuit. The processing circuit may be a circuit in which a processor executes software, or may be a dedicated circuit.

[0119] 21 is a diagram illustrating an example of a hardware configuration for realizing the traffic management device and the timetable replanning support device according to embodiments 1 to 5. The traffic management device 1A, 1D and the timetable replanning support device 2B, 2C each include a processing circuit 70 having a processor 72 and a memory 73, an input unit 71, and an output unit 74.

[0120] The input unit 71 is an interface circuit that receives data transmitted from outside the traffic control devices 1A, 1D and the traffic replanning support devices 2B, 2C to the traffic control devices 1A, 1D and the traffic replanning support devices 2B, 2C and provides the data to the processor 72. The output unit 74 is an interface circuit that outputs data from the processor 72 or the memory 73 to outside the traffic control devices 1A, 1D and the traffic replanning support devices 2B, 2C.

[0121] The processing units of the traffic management devices 1A, 1D and the traffic replanning support devices 2B, 2C are implemented by software, firmware, or a combination of software and firmware. The software or firmware is written as a program and stored in the memory 73. In the processing circuit 70, the processor 72 reads and executes the program stored in the memory 73 to implement each function of the processing unit. That is, the processing circuit 70 includes a memory 73 for storing a program that results in the processing of each function of the processing unit. This program can be said to cause a computer to execute the procedures and methods implemented by the traffic management devices 1A, 1D and the traffic replanning support devices 2B, 2C. The processing units of the traffic management devices 1A, 1D and the traffic replanning support devices 2B, 2C, namely, the data acquisition unit 21, the rule analysis unit 23, the traffic replanning determination unit 24, the simulation unit 27, and the simulation unit 28, are implemented by the processor 72 reading and executing the program stored in the memory 73. The memory 73 is also used as temporary memory when the processor 72 executes various processes. The storage unit 22 included in the traffic management devices 1A, 1D and the timetable replanning support devices 2B, 2C is realized by a memory 73. In addition, the output processing unit 25 included in the traffic management devices 1A, 1D and the timetable replanning support devices 2B, 2C is realized by an output unit 74.

[0122] The processor 72, for example, includes one or more of a central processing unit (CPU), a digital signal processor (DSP), and a system large-scale integration (LSI). The memory 73 includes one or more of a random access memory (RAM), a read-only memory (ROM), a flash memory, an erasable programmable read-only memory (EPROM), and an electrically erasable programmable read-only memory (EEPROM). The memory 73 also includes a recording medium on which a computer-readable program is recorded. Such a recording medium includes one or more of a nonvolatile or volatile semiconductor memory, a magnetic disk, a flexible memory, an optical disk, a compact disk, and a digital versatile disc (DVD).

[0123] The configurations shown in the above embodiments are merely examples, and may be combined with other known technologies, or different embodiments may be combined with each other. It is also possible to omit or modify parts of the configurations as long as they do not deviate from the gist of the invention.

[0124] Various aspects of the present disclosure are summarized below as appendices.

[0125] [Appendix 1] a storage unit that stores train schedule information indicating train operation plans and train schedule rescheduling history information including details of train schedule rescheduling that has been implemented in the past; a data acquisition unit that acquires user usage information of users who use the train or station and operation information of the train; a rule analysis unit that extracts a train timetable rescheduling rule based on the operation information, the train schedule information, and the train timetable rescheduling history information; a timetable replanning determination unit that generates timetable replanning rule candidate information to be used for issuing a timetable replanning instruction for the train based on the timetable replanning rule, the operation information, and the user usage information; A traffic replanning support device comprising: [Appendix 2] The timetable replanning support device according to claim 1, further comprising a display device that displays the timetable replanning rule candidate information. [Appendix 3] The timetable replanning support device described in Appendix 1 or 2, further comprising an output processing unit that outputs the timetable replanning rule candidate information to an operation management device that manages the train operations or to an information processing terminal operated by a dispatcher. [Appendix 4] The timetable replanning support device described in Appendix 1 is characterized in that, when the timetable replanning is performed, the data acquisition unit acquires timetable replanning data indicating the operation content of the timetable replanning and stores it in the timetable replanning history information. [Appendix 5] The timetable replanning support device described in any one of Appendices 1 to 4, characterized in that the rule analysis unit extracts correlation rules regarding timetable replanning operations between the user usage information, the operation information, the train schedule information, and the timetable information, and the timetable replanning history information, as the timetable replanning rules, using a data mining technique. [Appendix 6] The rule analysis unit a rule extraction database generation unit that generates a rule extraction database from the user usage information, the operation information, the bus schedule information, and the timetable replanning history information in accordance with item definition information that defines predetermined items whose values ​​are true or false and methods for calculating values ​​corresponding to these items, and that generates a timetable replanning content rule extraction database by extracting only records whose values ​​are true for items corresponding to the timetable replanning history information from the rule extraction database; and a timetable replanning rule extraction unit that extracts the timetable replanning rules by the data mining method using the rule extraction database and the timetable replanning content rule extraction database; 6. The timetable replanning support device according to claim 5, comprising: [Appendix 7] The timetable rescheduling rule extraction unit Using the database for extracting rules containing timetable replanning contents, extract the timetable replanning rule, which is a combination of one or more items of prerequisites corresponding to the user usage information, the operation information, and the bus schedule information, for which an index indicating relevance is equal to or greater than a predetermined reference value, and one or more items of timetable replanning contents corresponding to the timetable replanning history information; extracting from the rule extraction database the number of occurrences of the prerequisite conditions of the extracted timetable rescheduling rule; extracting the number of times the extracted timetable replanning rule has been implemented from the timetable replanning content rule extraction database; Calculating an implementation rate, which is the ratio of the number of times the extracted timetable replanning rule is implemented to the number of times the prerequisite of the extracted timetable replanning rule occurs; The timetable replanning support device described in Appendix 6 is characterized in that it generates timetable replanning rule information including the prerequisites and timetable replanning contents of the extracted timetable replanning rules, the number of occurrences of the prerequisites, and the implementation rate. [Appendix 8] The timetable replanning support device described in Appendix 7 is characterized in that the timetable replanning judgment unit generates the timetable replanning rule candidate information so as to include the relevant timetable replanning rules whose implementation rate is equal to or greater than a predetermined first threshold. [Appendix 9] The timetable replanning support device described in Appendix 7 or 8 is characterized in that the timetable replanning judgment unit generates the timetable replanning rule candidate information with instructions to display the timetable replanning rule information whose implementation rate is equal to or greater than a predetermined second threshold in a manner different from others. [Appendix 10] The rule analysis unit extracts the timetable rescheduling rule outside of commercial operating hours, 10. The timetable replanning support device according to any one of appendices 1 to 9, wherein the timetable replanning determination unit generates the timetable replanning rule candidate information during commercial operating hours. [Appendix 11] The user usage information includes people flow information indicating the flow of people at the station, The train rescheduling support device according to claim 1, wherein the data acquisition unit acquires video data from a camera installed at the station as station facility data and estimates the people flow information from the video data. [Appendix 12] The user usage information includes people flow information indicating the flow of people at the station, The train rescheduling support device according to claim 1, wherein the data acquisition unit acquires people flow data estimated from video data from a camera installed at the station as station facility data, and uses the people flow data as the people flow information. [Appendix 13] The timetable replanning rule includes a precondition for the timetable replanning to be implemented and a content of the timetable replanning to be implemented when the precondition is satisfied, A simulation unit performs a simulation for the timetable replanning rule that is determined to meet the prerequisite by the timetable replanning determination unit, and returns the simulation result to the timetable replanning determination unit, The timetable replanning support device described in any one of Appendices 1 to 12, characterized in that the timetable replanning judgment unit generates the timetable replanning rule candidate information including only the operation rules that require the shortest time to recover from delays as a result of the simulation. [Appendix 14] a simulation unit that performs a train operation simulation from the present time until a predetermined time later, The timetable replanning support device described in any one of Appendices 1 to 12, characterized in that the timetable replanning determination unit determines whether there is a timetable replanning rule that corresponds to the simulated operation information and the user usage information, and if there is a corresponding timetable replanning rule, generates the timetable replanning rule candidate information including the corresponding timetable replanning rule. [Appendix 15] A train rescheduling support system including a train operation management device that manages train operations and a train rescheduling support device that supports train rescheduling, The timetable replanning assistance device a storage unit that stores train schedule information indicating the train operation plan and train schedule history information including details of train schedule adjustments that have been implemented in the past; a data acquisition unit that acquires user usage information of users who use the train or station and operation information of the train; a rule analysis unit that extracts a train timetable rescheduling rule based on the operation information, the train schedule information, and the train timetable rescheduling history information; a timetable replanning determination unit that generates timetable replanning rule candidate information to be used for issuing a timetable replanning instruction for the train based on the timetable replanning rule, the operation information, and the user usage information; A traffic rescheduling support system comprising: [Appendix 16] a step of storing train schedule information indicating a train operation plan and train operation rescheduling history information including details of train operation reschedulings that have been implemented in the past; acquiring user usage information of users who use the train or station and operation information of the train; extracting a train timetable rescheduling rule based on the operation information, the train schedule information, and the train timetable rescheduling history information; generating, based on the timetable rescheduling rule, the operation information, and the user usage information, candidate timetable rescheduling rule information to be used for issuing instructions for timetable rescheduling of the train; A traffic rescheduling support method comprising: [Appendix 17] On the computer, a step of storing train schedule information indicating a train operation plan and train operation rescheduling history information including details of train operation reschedulings that have been implemented in the past; acquiring user usage information of users who use the train or station and operation information of the train; extracting a train timetable rescheduling rule based on the operation information, the train schedule information, and the train timetable rescheduling history information; generating, based on the timetable rescheduling rule, the operation information, and the user usage information, candidate timetable rescheduling rule information to be used for issuing instructions for timetable rescheduling of the train; A traffic rescheduling support program characterized by executing the above. [Explanation of symbols]

[0126] 1A, 1B, 1C, 1D, 1E Traffic management device, 2B, 2C Traffic rescheduling support device, 5B, 5C Traffic rescheduling support system, 11 Traffic management unit, 21 Data acquisition unit, 22 Memory unit, 23 Rule analysis unit, 24 Traffic rescheduling determination unit, 25 Output processing unit, 27, 28 Simulation unit, 51 Train, 52 Station, 53 Information processing terminal, 54 Display device, 55 Signal system, 70 Processing circuit, 71 Input unit, 72 Processor, 73 Memory, 74 Output unit, 221 Traffic information database, 222 People flow information database, 223 Train schedule database, 224 Traffic rescheduling history database, 225 Traffic rescheduling rule information database, 231 Rule extraction database generation unit, 232 Traffic rescheduling rule extraction unit, 236 Rule extraction database, 237 Traffic rescheduling content containing rule extraction database.

Claims

1. a storage unit that stores train schedule information indicating train operation plans and train schedule rescheduling history information including details of train schedule rescheduling that has been implemented in the past; a data acquisition unit that acquires user usage information of users who use the train or station and operation information of the train; a rule analysis unit that extracts a train timetable rescheduling rule based on the operation information, the train schedule information, and the train timetable rescheduling history information; a timetable replanning determination unit that generates timetable replanning rule candidate information to be used for issuing a timetable replanning instruction for the train based on the timetable replanning rule, the operation information, and the user usage information; A traffic replanning support device comprising:

2. The timetable replanning support device according to claim 1 , further comprising a display device that displays the timetable replanning rule candidate information.

3. The timetable replanning support device according to claim 1, further comprising an output processing unit that outputs the timetable replanning rule candidate information to a traffic management device that manages the train operations or to an information processing terminal operated by a dispatcher.

4. The timetable replanning support device described in claim 1, characterized in that when the timetable replanning is performed, the data acquisition unit acquires timetable replanning data indicating the operation details of the timetable replanning and stores it in the timetable replanning history information.

5. The timetable replanning support device of claim 1, characterized in that the rule analysis unit extracts correlation rules regarding timetable replanning operations between the user usage information, the operation information, the bus schedule information, and the timetable information, and the timetable replanning history information, as the timetable replanning rules, using a data mining technique.

6. The rule analysis unit a rule extraction database generation unit that generates a rule extraction database from the user usage information, the operation information, the bus schedule information, and the timetable replanning history information in accordance with item definition information that defines predetermined items whose values ​​are true or false and methods for calculating values ​​corresponding to these items, and that generates a timetable replanning content rule extraction database by extracting only records whose values ​​are true for items corresponding to the timetable replanning history information from the rule extraction database; and a timetable replanning rule extraction unit that extracts the timetable replanning rules by the data mining method using the rule extraction database and the timetable replanning content rule extraction database; 6. The timetable replanning support device according to claim 5, further comprising:

7. The timetable rescheduling rule extraction unit Using the database for extracting rules containing timetable replanning contents, the timetable replanning rule is extracted, which is a combination of a prerequisite, which is one or more items corresponding to the user usage information, the operation information, and the bus schedule information, for which an index indicating relevance is equal to or greater than a predetermined reference value, and a timetable replanning content, which is one or more items corresponding to the timetable replanning history information; extracting from the rule extraction database the number of occurrences of the prerequisite conditions of the extracted timetable rescheduling rule; extracting the number of times the extracted timetable replanning rule has been implemented from the timetable replanning content rule extraction database; Calculating an implementation rate, which is the ratio of the number of times the extracted timetable replanning rule is implemented to the number of times the prerequisite of the extracted timetable replanning rule occurs; The timetable replanning support device according to claim 6, characterized in that it generates timetable replanning rule information including the preconditions and the timetable replanning content of the extracted timetable replanning rule, the number of occurrences of the preconditions, and the implementation rate.

8. The timetable replanning support device described in claim 7, characterized in that the timetable replanning judgment unit generates the timetable replanning rule candidate information so as to include the relevant timetable replanning rules whose implementation rate is equal to or greater than a predetermined first threshold value.

9. The timetable replanning support device described in claim 7, characterized in that the timetable replanning judgment unit generates the timetable replanning rule candidate information that instructs the timetable replanning rule information whose implementation rate is equal to or greater than a predetermined second threshold to be displayed in a different manner from others.

10. The rule analysis unit extracts the timetable rescheduling rule outside of commercial operating hours, The timetable replanning support device according to claim 1 , wherein the timetable replanning determination unit generates the timetable replanning rule candidate information during commercial operating hours.

11. The user usage information includes people flow information indicating the flow of people at the station, 2. The train replanning support device according to claim 1, wherein the data acquisition unit acquires video data from a camera installed at the station as station facility data, and estimates the people flow information from the video data.

12. The user usage information includes people flow information indicating the flow of people at the station, The train replanning support device according to claim 1, characterized in that the data acquisition unit acquires people flow data estimated from video data from a camera installed at the station as station facility data, and uses the people flow data as the people flow information.

13. The timetable replanning rule includes a precondition for the timetable replanning to be implemented and a content of the timetable replanning to be implemented when the precondition is satisfied, A simulation unit performs a simulation for the timetable replanning rule that is determined to meet the prerequisite by the timetable replanning determination unit, and returns the simulation result to the timetable replanning determination unit, The timetable replanning support device according to any one of claims 1 to 12, characterized in that the timetable replanning determination unit generates the timetable replanning rule candidate information including only the operation rule that requires the shortest time to recover from delays as a result of the simulation.

14. a simulation unit that performs a train operation simulation from the present time until a predetermined time later, The timetable replanning support device described in any one of claims 1 to 12, characterized in that the timetable replanning determination unit determines whether there is a timetable replanning rule that corresponds to the simulated operation information and the user usage information, and if there is a corresponding timetable replanning rule, generates the timetable replanning rule candidate information including the corresponding timetable replanning rule.

15. A train rescheduling support system including a train operation management device that manages train operations and a train rescheduling support device that supports train rescheduling, The timetable replanning assistance device a storage unit that stores train schedule information indicating the train operation plan and train schedule history information including details of train schedule adjustments that have been implemented in the past; a data acquisition unit that acquires user usage information of users who use the train or station and operation information of the train; a rule analysis unit that extracts a train timetable rescheduling rule based on the operation information, the train schedule information, and the train timetable rescheduling history information; a timetable replanning determination unit that generates timetable replanning rule candidate information to be used for issuing a timetable replanning instruction for the train based on the timetable replanning rule, the operation information, and the user usage information; A traffic rescheduling support system comprising:

16. a step of storing train schedule information indicating a train operation plan and train operation rescheduling history information including details of train operation reschedulings that have been implemented in the past; acquiring user usage information of users who use the train or station and operation information of the train; extracting a train timetable rescheduling rule based on the operation information, the train schedule information, and the train timetable rescheduling history information; generating, based on the timetable rescheduling rule, the operation information, and the user usage information, candidate timetable rescheduling rule information to be used for issuing instructions for timetable rescheduling of the train; A traffic rescheduling support method comprising:

17. On the computer, a step of storing train schedule information indicating a train operation plan and train operation rescheduling history information including details of train operation reschedulings that have been implemented in the past; acquiring user usage information of users who use the train or station and operation information of the train; extracting a train timetable rescheduling rule based on the operation information, the train schedule information, and the train timetable rescheduling history information; generating, based on the timetable rescheduling rule, the operation information, and the user usage information, candidate timetable rescheduling rule information to be used for issuing instructions for timetable rescheduling of the train; A traffic rescheduling support program characterized by executing the above.

Images