Vehicle dispatch reservation device, vehicle dispatch reservation system, vehicle dispatch reservation method, vehicle dispatch reservation program

Abstract

To provide a vehicle allocation reservation device, a vehicle allocation reservation system, a vehicle allocation reservation method, and a vehicle allocation reservation program, capable of smoothly performing transfer to other traffic means when a service interruption section is generated in a route of railroad stations.SOLUTION: A vehicle allocation reservation device 1 includes a passenger information estimation part 24 and an alternative transportation plan generation part 25. The passenger information estimation part 24 estimates the number of passengers in a train in a service interruption section and destinations for each passenger. The alternative transportation plan generation section 25 determines the kinds of other traffic means and the number of vehicles of the other traffic means which are required to road-transport the passengers who have entered from railroad stations in the service interruption section to the estimated destinations, and also generates operation plans of the respective vehicles.SELECTED DRAWING: Figure 2

Description

Technical Field

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[0004] , , , , ,

[0001] The present invention relates to a vehicle reservation device, a vehicle reservation system, a vehicle reservation method, and a vehicle reservation program for arranging vehicle allocation such as buses and taxis when transfer transportation occurs on the railway line of a railway station.

Background Art

[0002] Conventionally, when a railway suspension occurs due to the influence of vehicle failures or accidents on the railway line of a railway station, as an alternative means of transportation, transfer to another railway with a parallel line, transfer to other means of transportation such as buses and taxis, etc. are carried out. For example, in Patent Document 1, when transfer transportation occurs, an automatic ticket gate uses the section with no service and the transfer transportation section distributed from the railway operator server to determine whether a passenger using an IC card ticket is a transfer target, and settles the fare according to the result. An automatic ticket gate is disclosed for performing settlement at the fare (freight).

[0003] Also, in Patent Document 2, a shared vehicle operation management center device is disclosed that grasps the operation status of a shared vehicle in operation based on the vehicle ID, adjusts the operation plan, and creates instructions for the crew of the shared vehicle.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, the above conventional vehicle reservation device has the following problems. In other words, with the dispatch reservation system disclosed in the above-mentioned publication, when alternative transportation is required due to service suspensions caused by malfunctions or accidents on the railway lines at train stations, transfers to other means of transport are not smooth, and there is a risk of costs being incurred due to passengers switching to other companies' lines. The object of the present invention is to provide a vehicle dispatch reservation device, vehicle dispatch reservation system, vehicle dispatch reservation method, and vehicle dispatch reservation program that enable smooth transfers to other means of transportation when a section of a railway line at a station becomes impassable. [Means for solving the problem]

[0006] The first vehicle dispatch reservation device is a vehicle dispatch reservation device that arranges alternative transportation for passengers to means of transport other than trains in a section of a railway line where service is disrupted, Input reception unit, stopping information acquisition unit, It includes a passenger information estimation unit and an alternative transportation plan creation unit. The input reception unit receives operational information regarding the occurrence of service disruptions. The stop information acquisition unit retrieves train information and time information regarding trains that are stopped due to service disruptions from the operational information. The Passenger Information Estimation Department, Based on train information and timetable information, Sections that are out of service Due to the occurrence of the stopped The number of passengers on the train and the destination of each passenger will be estimated. The alternative transportation planning department will cover the disrupted section. Based on the time the incident occurred and the timetable information of the trains stopped due to the disruption, the nearest station for each stopped train is estimated, and based on the estimated number of passengers, each passenger's destination, and the nearest station, trains should be dispatched to each nearest station. The type of other means of transportation, and the number of vehicles of the other means of transportation. , the routes of the other means of transportation Decide do Create a schedule for each vehicle.

[0007] This section describes a section of railway line that is out of service due to a train malfunction, accident, or other incident. Due to the occurrence of the stopped When providing alternative transportation to means other than trains, the affected section Due to the occurrence The number of passengers on board the stopped train and their destinations are estimated, and based on these estimates, the types of other modes of transport and the number of vehicles are determined. , routes of other means of transport Determine the schedule and create an operating plan for each vehicle. Here, "other means of transportation" includes, for example, buses, taxis, and other means of transportation owned by the railway company that operates the affected section of the line.

[0008] As a result, When station staff at a railway station input information about a section of track being out of service, the system can be triggered to estimate the number of passengers on trains stopped due to the outage and their respective destinations. Based on these estimates, it can then create a schedule for alternative transportation services. The estimation of the number of passengers and their destinations for each train can be done by obtaining information on the train stopped due to the outage and the time of the stop. thus,By transmitting the estimated number of passengers on trains stopped due to service disruptions, along with their estimated destinations, to other transportation providers such as bus companies and taxi companies, for example, smoother transfers to other modes of transport can be facilitated. In particular, if a railway company owns vehicles such as buses for road transport, these vehicles can be used for passenger transport to provide faster service, thereby alleviating congestion and reducing costs incurred due to passengers switching to other companies. In this way, by determining the appropriate number of vehicles and routes based on the estimated number of passengers and their respective destinations, alternative transportation can be provided smoothly.

[0009] The dispatch reservation device according to the second invention is the same as the dispatch reservation device according to the first invention, wherein the passenger information estimation unit estimates the number of passengers and their destinations based on entry records obtained from automatic ticket gates installed at railway stations. This allows us to estimate the number of passengers on each train stopped due to a disrupted section of track, and their respective destinations, by using passenger entry and exit data acquired at automatic ticket gates installed at railway stations.

[0010] The third invention relates to a ride-hailing reservation device, which is a ride-hailing reservation device according to the first or second invention, wherein the passenger information estimation unit estimates the number of passengers and their destinations by referring to past OD (Origin-Destination) data. This allows us to estimate the number of passengers on each train stopped due to a disrupted section of track, as well as each passenger's destination, by using historical OD data for each passenger.

[0011] The dispatch reservation device according to the fourth invention is a dispatch reservation device according to any one of the first to third inventions, further comprising an output unit that outputs a vehicle operation plan created in an alternative transportation plan creation unit. This allows for the smooth implementation of alternative transportation by transmitting the outputted vehicle operation plans for other modes of transport to bus companies, taxi companies, etc.

[0014] The 5The vehicle reservation device according to the invention is from the first to the 4 A vehicle reservation device according to any one of the inventions of The nearest station to the train mentioned above . The alternative transport plan creation unit is such that the number of passengers targeted for transfer transport is large The nearest station to the train mentioned above , Prioritize Direct the vehicles of other means of transportation The operation plan for each vehicle is created in this manner. . As a result ,stop As a result of estimating the number of passengers on each train with many passengers, Nearest station By preferentially creating an operation plan so as to direct the vehicles of other means of transportation, transfer transportation can be smoothly performed.

[0015] The 6 The vehicle reservation device according to the invention is from the first to the 5 A vehicle reservation device according to any one of the inventions of The nearest station is further upstream. . The alternative transport plan creation unit is The nearest station is further upstream. , Prioritize Direct the vehicles of other means of transportation The operation plan for each vehicle is created in this manner. . As a result ,stop As a result of estimating the destination of each passenger on the train, The nearest station is further upstream. By preferentially creating an operation plan so as to direct the vehicles of other means of transportation, transfer transportation can be smoothly performed.

[0017] The 7 The vehicle reservation system according to the invention includes a vehicle reservation device according to any one of the inventions from the first to the 6 [[ID=and a plurality of automatic ticket gates installed at the railway station and recording the entry and exit of each passenger to and from the railway station. As a result, by using the entry and exit data of each passenger obtained at the automatic ticket gate, the number of passengers on each train stopped due to the occurrence of a non - through section and the destination of each passenger are estimated, and an operation plan for other means of transportation for performing transfer transportation is created using this estimation result.

[0018] The 8The vehicle reservation method according to the invention is a vehicle reservation method for arranging alternative transportation of passengers to means other than trains in a section of a railway line where service is disrupted, Input reception step, stopping information acquisition step, It includes a passenger information estimation step and an alternative transportation plan creation step. In the input reception step, the input reception unit receives operational information regarding the occurrence of service disruptions. In the stop information acquisition step, the stop information acquisition unit acquires train information and time information regarding the time of the stop from the operational information. In the passenger information estimation step, Based on train information and timetable information, The number of passengers on the train in the section where service is suspended and the destination of each passenger. The Passenger Information Estimation Department Estimate. In the alternative transportation plan creation step, the section that is out of service Based on the time of the incident and the timetable information of trains stopped due to the disruption, the Alternative Transportation Planning Department estimates the nearest station for each stopped train, and then, based on the estimated number of passengers, each passenger's destination, and nearest station, determines which trains should be dispatched to each nearest station. Identify other types of transportation and the number of vehicles using those other modes of transport. do Create a schedule for each vehicle.

[0019] This section describes a section of railway line that is out of service due to a train malfunction, accident, or other incident. Due to the occurrence of the stopped When providing alternative transportation to means other than trains, the affected section Due to the occurrence The number of passengers on board the stopped train and their destinations are estimated, and based on these estimates, the types of other modes of transport and the number of vehicles are determined. , routes of other means of transport Determine the schedule and create an operating plan for each vehicle. Here, "other means of transportation" includes, for example, buses, taxis, and other means of transportation owned by the railway company that operates the affected section of the line.

[0020] As a result, When station staff at a railway station input information about a section of track being out of service, the system can be triggered to estimate the number of passengers on trains stopped due to the outage and their respective destinations. Based on these estimates, it can then create a schedule for alternative transportation services. The estimation of the number of passengers and their destinations for each train can be done by obtaining information on the train stopped due to the outage and the time of the stop. thus, By transmitting the estimated number of passengers on trains stopped due to service disruptions, along with their estimated destinations, to other transportation providers such as bus companies and taxi companies, for example, smoother transfers to other modes of transport can be facilitated. In particular, if a railway company owns vehicles such as buses for road transport, these vehicles can be used for passenger transport to provide faster service, thereby alleviating congestion and reducing costs incurred due to passengers switching to other companies. In this way, by determining the appropriate number of vehicles and routes based on the estimated number of passengers and their respective destinations, alternative transportation can be provided smoothly.

[0021] The9 The vehicle dispatch reservation program according to the invention is a vehicle dispatch reservation program that arranges alternative transportation for passengers to means of transport other than trains in sections of railway lines where service is disrupted, Input reception step, stopping information acquisition step, The system causes a computer to execute a vehicle reservation method that includes a passenger information estimation step and an alternative transportation plan creation step. In the input reception step, the input reception unit receives operational information regarding the occurrence of service disruptions. In the stop information acquisition step, the stop information acquisition unit acquires train information and time information regarding the time of the stop from the operational information. In the passenger information estimation step, Based on train information and timetable information, The number of passengers on the train in the section where service is suspended and the destination of each passenger. The Passenger Information Estimation Department Estimate. In the alternative transportation plan creation step, the section that is out of service Based on the time of the incident and the timetable information of trains stopped due to the disruption, the Alternative Transportation Planning Department estimates the nearest station for each stopped train, and then, based on the estimated number of passengers, each passenger's destination, and nearest station, determines which trains should be dispatched to each nearest station. Identify the number of vehicles using other modes of transport. do Create a schedule for each vehicle.

[0022] This section describes a section of railway line that is out of service due to a train malfunction, accident, or other incident. Due to the occurrence of the stopped When providing alternative transportation to means other than trains, the affected section Due to the occurrence The number of passengers on board the stopped train and their destinations are estimated, and based on these estimates, the types of other modes of transport and the number of vehicles are determined. , routes of other means of transport Determine the schedule and create an operating plan for each vehicle. Here, "other means of transportation" includes, for example, buses, taxis, and other means of transportation owned by the railway company that operates the affected section of the line.

[0023] As a result, When station staff at a railway station input information about a section of track being out of service, the system can be triggered to estimate the number of passengers on trains stopped due to the outage and their respective destinations. Based on these estimates, it can then create a schedule for alternative transportation services. The estimation of the number of passengers and their destinations for each train can be done by obtaining information on the train stopped due to the outage and the time of the stop. thus, By transmitting the estimated number of passengers on trains stopped due to service disruptions, along with their estimated destinations, to other transportation providers such as bus companies and taxi companies, for example, smoother transfers to other modes of transport can be facilitated. In particular, if a railway company owns vehicles such as buses for road transport, these vehicles can be used for passenger transport to provide faster service, thereby alleviating congestion and reducing costs incurred due to passengers switching to other companies. In this way, by determining the appropriate number of vehicles and routes based on the estimated number of passengers and their respective destinations, alternative transportation can be provided smoothly. [Effects of the Invention]

[0024] According to the vehicle dispatch reservation device of the present invention, when a section of the railway line at a railway station becomes impassable, transfers to other means of transportation can be carried out smoothly. [Brief explanation of the drawing]

[0025] [Figure 1] A system configuration diagram showing the configuration of a ride-hailing reservation system including a ride-hailing reservation device according to one embodiment of the present invention. [Figure 2] A functional block diagram formed within the vehicle dispatch reservation device shown in Figure 1. [Figure 3] Figure 1 shows an example of passenger passage data acquired by the automatic ticket gates in a table format. [Figure 4] A schematic diagram illustrating an example where a single railway operator runs trains on multiple lines, including multiple stations. [Figure 5] (A) is a diagram showing an example of OD data in matrix form. (B) is a diagram showing an example of OD data by time period in matrix form. [Figure 6] Figure 2 shows the initialization process and first update process performed by the OD prediction unit included in the vehicle dispatch reservation system. [Figure 7] This figure shows the second update process performed by the OD prediction unit included in the vehicle dispatch reservation system shown in Figure 2. [Figure 8] Figure 2 shows the third update process performed by the OD prediction unit included in the vehicle dispatch reservation system. [Figure 9] This figure shows the train allocation process performed by the OD prediction unit included in the train dispatch reservation system. [Figure 10] (A) and (B) are diagrams showing bus operation plans created by the alternative transportation planning unit included in the dispatch reservation system in Figure 2. [Figure 11] A flowchart showing the processing flow of a vehicle dispatch reservation method according to an embodiment of the present invention. [Modes for carrying out the invention]

[0026] A dispatch reservation system 30 including a dispatch reservation device 1 according to one embodiment of the present invention will be described below with reference to Figures 1 to 11. In this embodiment, unnecessary details may be omitted. For example, detailed explanations of already well-known matters or redundant explanations of substantially identical configurations may be omitted. This is to avoid the following explanation becoming unnecessarily verbose and to facilitate understanding for those skilled in the art. Furthermore, the applicant provides the accompanying drawings and the following description so that those skilled in the art may fully understand the present invention, and not intends to limit the subject matter described in the claims.

[0027] (1) Configuration of the vehicle dispatch reservation system 30 The dispatch reservation system 30 of this embodiment is a system that arranges alternative transportation for passengers on a railway line that includes a section of track that is out of service due to a disruption, and as shown in Figure 1, it comprises a dispatch reservation device 1 connected via a communication network 9, a passage data collection server 2, an administrator terminal 3, a digital signage 4, a user terminal 5, and an automatic ticket gate 6 installed at a railway station.

[0028] The dispatch reservation device 1 arranges alternative transportation for passengers to other means of transport besides trains in sections of the railway line that are out of service. The detailed configuration of the dispatch reservation device 1 will be described in detail later. The passage data collection server 2 collects information about passengers entering and exiting the station, along with information about their tickets, from multiple automatic ticket gates 6 installed at each railway station, as passage data D10 (see Figure 3) indicating the movement of each passenger.

[0029] The administrator terminal 3 is, for example, an administrator's PC (Personal Computer) installed in the station master's office of a railway station, and receives and displays estimated data D12 of the number of passengers on each train that has stopped due to the disruption of service described later, estimated data D13 of each passenger's destination, bus arrangement data D14, etc. from the dispatch reservation device 1 via the communication network 9. Signage 4 is, for example, an electronic billboard installed at each station, and is used as a display device that shows various information output from output unit 14.

[0030] The user terminal 5 is an information terminal carried by passengers, such as a smartphone or tablet, and when a dedicated application 5A is installed, it can provide passengers with information regarding alternative transportation to other means of transport that become necessary due to the disruption of service. The provider of this application 5A is, for example, a railway operator that has introduced the train dispatch reservation system 1.

[0031] Automatic ticket gates 6 are a type of railway facility installed at railway stations that reads information recorded on tickets purchased by passengers. For example, if a passenger passes through automatic ticket gates 6 in the direction of moving from outside the station to inside the station and there is no entry record on the ticket, automatic ticket gates 6 will record an entry on the ticket, as if the passenger is entering. On the other hand, if a passenger passes through automatic ticket gates 6 in the direction of moving from inside the station to outside the station and there is an entry record on the ticket, automatic ticket gates 6 will record an exit on the ticket, as if the passenger is exiting (or collect the ticket).

[0032] The automatic ticket gate 6 transmits information about the ticket, along with information about the passenger's entry and exit, to the pass-through data collection server 2. Specifically, when a passenger passes through automatic ticket gate 6 to enter a station, the automatic ticket gate 6 transmits at least the entry station information and entry time information. When a passenger passes through automatic ticket gate 6 to exit a station, the automatic ticket gate 6 transmits at least the exit station information and exit time information. In addition, the automatic ticket gate 6 at the exit station transmits the entry record (entry station information and entry time information) read from the ticket along with the exit station information and exit time information.

[0033] (2) Configuration of the vehicle dispatch reservation device 1 The vehicle dispatch reservation device 1 according to this embodiment estimates the destination of each passenger using the passenger passage data D10 (entry / exit record) acquired by the automatic ticket gate 6. In the event of a section being out of service, it estimates the number of passengers on each train that stopped due to the outage. Based on these estimation results, it creates and outputs an alternative transportation plan for arranging vehicles to provide substitute transportation.

[0034] As shown in Figure 1, the vehicle dispatch reservation device 1 comprises a central processing unit 11, a storage unit 12, an input receiving unit 13, and an output unit 14, which are interconnected via a communication bus 15. The central processing unit 11 executes a vehicle dispatch reservation method according to the vehicle dispatch reservation program P stored in the storage unit 12. The central processing unit 11 or the vehicle dispatch reservation device 1 equipped therewith is an example of a computer that executes a vehicle dispatch reservation method.

[0035] The storage unit 12 temporarily or permanently stores the dispatch reservation program P, as well as data necessary to execute the dispatch reservation method. In this embodiment, the storage unit 12 includes a main storage unit 12a and an auxiliary storage unit 12b. The main memory unit 12a is implemented by a storage device such as ROM (Read-Only Memory), RAM (Random Access Memory), or EEPROM (Electrically Erasable Programmable Read-Only Memory). The main memory unit 12a stores the vehicle reservation program P. The main memory unit 12a also temporarily stores the OD prediction data D11, passenger number estimation data D12 for each train when a section of service is disrupted, passenger destination estimation data D13, and bus arrangement data D14, which will be described later.

[0036] The auxiliary storage unit 12b is a large storage device, such as a hard disk drive. The auxiliary storage unit 12b may also be implemented by a cloud server separated from the communication bus 15. The auxiliary storage unit 12b stores various types of data that are referenced when predicting passenger flow (target values, etc.). These types of data include past OD data D1, longest travel time data D2, operation data D3, holiday data D4, station data D5, route data D6, route data D7, and bus non-operation data D8, etc.

[0037] The input reception unit 13 collects transit data D10 (see Figure 3) indicating the movement of each passenger from the transit data collection server 2 via the communication network 9. The central processing unit 11 predicts passenger flow (target value, etc.) based on the collected transit data D10 and various data stored in the storage unit 12. In addition, when a section of track becomes inoperable due to a malfunction or accident, the input reception unit 13 receives operational information regarding the inoperable section (name of the stopped train, stopping time, etc.) from station staff at the railway station included in the inoperable section.

[0038] The output unit 14 outputs passenger flow prediction results (target values, etc.) and information regarding alternative transportation in the event of a service disruption (vehicle operation plans, etc.) to the administrator terminal 3, signage 4, and user terminal 5 via the communication network 9. Furthermore, in this embodiment, the dispatch reservation device 1 has a central processing unit 11 that reads the dispatch reservation program stored in the main memory unit 12a and generates the functional blocks shown in Figure 2. Specifically, the dispatch reservation device 1 includes a passenger information acquisition unit 21, an OD prediction unit 22, a stop information acquisition unit 23, a passenger information estimation unit 24, and an alternative transportation plan creation unit 25 as functional blocks.

[0039] The passenger information acquisition unit 21 sequentially acquires entry and exit data (passage data D10) recorded at each station by the automatic ticket gate 6 from the passage data collection server 2. The transit data D10 shows the entry and exit stations and times for each passenger (see Figure 3). However, the acquired transit data D10 may include incomplete data where only the entry station and entry time are shown due to the passenger not having exited. The acquisition cycle for transit data D10 is not particularly limited. For example, the acquisition cycle is set to the same as the collection period for transit data D10 on the transit data collection server 2 (e.g., 5 minutes).

[0040] The OD prediction unit 22 creates OD prediction data D11, which shows the prediction result of the OD data for the day, based on the day's passage data D10 for each passenger at each station acquired by the passenger information acquisition unit 21, and updates the created OD prediction data D11 as needed. The stop information acquisition unit 23 acquires train information (train number) and time information regarding the time of the stop from the operational information at the time of the disruption input to the input reception unit 13.

[0041] The passenger information estimation unit 24 estimates the number of passengers on a stopped train and the destination of each passenger based on the OD prediction data D11 created by the OD prediction unit 22 and the train information and stopping times obtained by the stopping information acquisition unit 23 that indicate the train is stopped due to a section of service disruption. The passenger information estimation unit 24 estimates the number of passengers on a stopped train and information on each passenger's destination, which is stored in the main memory unit 12a of the train reservation device 1 as estimated passenger number data D12 for each train and estimated passenger destination data D13.

[0042] The alternative transportation planning unit 25 determines the type of other means of transportation (such as buses) and the number of vehicles required to transport passengers from trains stopped due to the disruption to their estimated destinations. The alternative transportation planning unit 25 also creates an operation plan for each vehicle by referring to the bus non-operation data D8 (data on buses parked in the depot and ready to operate) stored in the auxiliary storage unit 12b of the vehicle reservation device 1. The operation plan created in the alternative transportation plan creation unit 25 is stored as bus arrangement data D14 in the main memory unit 12a of the vehicle reservation device 1.

[0043] (Transit data, OD data) A railway operator owns a complete set of railway facilities, including tracks and multiple stations, and operates trains on the tracks to transport passengers. The complete set of railway facilities includes automatic ticket gates 6 installed at each station. In Figure 4, as a mere example, a railway operator operates trains on two lines: the P line from stations A to F, and the Q line which branches off from the P line at station D and goes to stations G and H. "Train" refers to a train formation consisting of a single railway car or two or more railway cars coupled together.

[0044] Each passenger prepares the ticket required to pass through the automatic ticket gate 6, passes through the automatic ticket gate 6 to enter the departure station (hereinafter also referred to as the "entrance station"), travels by train operated by the railway company, and passes through the automatic ticket gate 6 to exit the destination station (hereinafter also referred to as the "exit station"). Hereafter, the entire sequence of travel for each passenger from entry at the departure station to exit at the destination station will be referred to as a "trip".

[0045] "Train tickets" include magnetic tickets and contactless IC (integrated circuit) cards, and each ticket records various information such as a ticket ID (Identity Document) to identify the ticket. "Train tickets" include regular tickets, commuter passes, and fare adjustment tickets. The automatic ticket gate 6 reads the information recorded on the ticket. If there is no entry record on the ticket and the passenger passes through the automatic ticket gate 6 in the direction of moving from outside the station to inside the station, the automatic ticket gate 6 records an entry on the ticket, treating it as an entry. If there is an entry record on the ticket and the passenger passes through the automatic ticket gate 6 in the direction of moving from inside the station to outside the station, the automatic ticket gate 6 records an exit on the ticket, treating it as an exit (or collects the ticket).

[0046] The automatic ticket gate 6 transmits information about the passenger's entry and exit, along with information about the ticket, to the pass-through data collection server 2. When a passenger passes through the automatic ticket gate 6 to enter, the automatic ticket gate 6 transmits at least the entry station information and entry time information. When a passenger passes through the automatic ticket gate 6 to exit, the automatic ticket gate 6 transmits at least the exit station information and exit time information. In addition, the automatic ticket gate 6 at the exit station transmits the entry record (entry station information and entry time information) read from the ticket, along with the exit station information and exit time information.

[0047] As shown in Figure 3, the transit data collection server 2 generates transit data D10 representing one trip, which consists of entry and exit as one set, based on information transmitted from automatic ticket gates 6 at numerous stations. The transit data D10 includes entry station information, entry time information, exit station information, and exit time information. The entry station information indicates the entry station where the automatic ticket gate 6 that read the ticket information is installed. The entry time information indicates the time the passenger passed through the automatic ticket gate 6 at the entry station. The exit station information indicates the exit station where the automatic ticket gate 6 that read the ticket information is installed. The exit time information indicates the time the passenger passed through the automatic ticket gate 6 at the exit station.

[0048] While a passenger is in transit, there is no information about the departure station or departure time (see the passage data D10 on the second line). Therefore, the passage data collection server 2 stores the incomplete passage data D10 until the passenger departs. The passage data collection server 2 can also transmit the incomplete passage data D10 to the dispatch reservation device 1 upon request from the dispatch reservation device 1. Once the day's train operations are complete, all passengers depart from their destination stations, and no passengers enter their departure stations until the first train of the following day. Thus, all trips for the day are finalized. Based on the finalized group of transit data D10, the transit data server 2 generates OD data D1 for this day (see Figure 5(A)).

[0049] As shown in Figure 5(A), the OD data D1 shows the number of passengers (i.e., number of trips) for each combination of entry station and exit station among multiple stations within the data measurement range (in the example in Figure 4, stations A to H on lines P and Q operated by a single railway operator). The OD data D1 is represented, for example, in a matrix with entry stations in rows and exit stations in columns. Referring to Figures 4 and 5(A), the symbols "a~h" correspond to stations A~H. Although not shown, the symbols "i,j" used in this embodiment represent any two different stations and can be appropriately replaced with the symbols "a~h". The symbol "Tij" is the total number of passengers who entered at station i and exited at station j. In other words, it is the number of trips where station i is the entry station and station j is the exit station. Further in other words, it is the number of passage data D10 in the aggregated passage data group D10 where the entry station information is station i and the exit station information is station j. The symbol "Gi" indicates the total number of passengers entering at station i, and the symbol "Ai" indicates the total number of passengers exiting at station i. Ga is the sum of Tab, Tac, ..., Tag, Tah, and Aa is the sum of Tba, Tca, ..., Tga, Tha. The symbol "Σ" represents the total number of trips (the number of aggregated transit data D10), which is the sum of Ga, Gb, ..., Gg, Gh, and also the sum of Aa, Ab, ..., Ag, Ah.

[0050] The collection period for transit data D10 to generate OD data D1 is not limited to a daily period, but may be a predetermined time unit shorter than one day (for example, an hourly period, a 10-minute period, etc.). In this case, as shown in Figure 5(B), multiple "time-specific OD data D1A" are generated, each with a different collection period for transit data D10. Hereinafter, the collection period for transit data D10 corresponding to each time-specific OD data D1A will be referred to as the "target time period T1".

[0051] Figure 5(B) shows a simplified example of time-based OD data D1A for the same day, where the collection period is set to 5-minute intervals. Multiple time-based OD data D1A examples are shown, with target time period T1 being 14:50-14:55, the next target time period T1 being 14:55-15:00, and the next target time period T1 being 15:00-15:05. If the collection period is short, such as in 5-minute increments, the duration of a trip may be longer than the collection period. Time-based OD data D1A includes all trips where the entry time falls within the target time period T1, regardless of whether the exit time falls within the target time period T1. In time-based OD data D1A, the symbol "Σ" indicates the total number of trips where the entry time falls within the target time period T1, and the symbol "Gi" indicates the number of passengers entering at station i during the target time period T1.

[0052] The transit data collection server 2 generates OD data D1 after the last train of the day and before the first train of the next day. The input reception unit 13 (see Figure 1) obtains the OD data D1 from the transit data collection server 2 before the first train of the day, and the obtained OD data D1 is stored in the storage unit 12 (see Figure 1) as past OD data D1. The dispatch reservation device 1 may also store time-based OD data D1A as past OD data D1. Time-based OD data D1A may be generated by the transit data collection server 2 or by the dispatch reservation device 1.

[0053] (OD prediction) The OD prediction unit 22 updates the OD prediction data D11, which shows the prediction result of the OD data for the day, based on the acquired transit data D10 for the day. In particular, the OD prediction unit 22 generates multiple time-segment OD prediction data. The length of the target time period T1 for each time-based OD prediction data is not particularly limited. For example, the length of the target time period T1 is set to be the same as the acquisition cycle of the transit data D10 in the passenger information acquisition unit 21 (for example, 5 minutes).

[0054] The OD prediction unit 22 performs an initialization process to set the initial value of the OD prediction data D11 based on past OD data D1 stored in the memory unit 12, and then performs an update process to correct the initial value of the OD prediction data D11 based on the day's transit data D10 which is acquired as it progresses, thereby updating the OD prediction data D11 as it progresses. In other words, the OD prediction unit 22 updates the OD prediction data D11 multiple times based on the latest version of the transit data D10 which is acquired intermittently as time progresses.

[0055] In this embodiment, updates are performed three times. The update process includes a first update process, a second update process, and a third update process. The OD prediction unit 22 executes the first update process at the end time t1 of the target time period T1 of the OD prediction data D11, and also executes the second update process and the third update process at the second update time t2 and the third update time t3, respectively, which are after the end time (first update time) t1 of the target time period T1.

[0056] The second update time t2 and the third update time t3 may be set in any way. In this embodiment, as just one example, the second update time t2 is set to a point in time that is the length of the target time period T1 after the end time t1 of the target time period T1 (for example, 10 minutes after the start time t0 and 5 minutes after the end time t1). The third update time t3 is set to a point in time that is the same length after the second update time t2 (15 minutes after the start time t0, 10 minutes after the end time t1 and 5 minutes after the second update time t2).

[0057] Furthermore, the target time zones T1 for multiple time-based OD prediction data are set to be continuous without interruption. The end time t1 of a target time zone T1 for one time-based OD prediction data is the same as the start time t0 of the target time zone T1 for the next time-based OD prediction data. The second update time t2 of a time-based OD prediction data is the same as the start time t0 of the target time zone T1 for the second-to-last time-based OD prediction data. Therefore, multiple time-based OD prediction data are generated simultaneously.

[0058] (initialization) Figure 6 shows the initialization process and the first update process. In Figure 6 and subsequent figures, for the sake of simplicity, only the four stations A, D, F, and H shown in Figure 4 are selected as entry and exit stations, but the number of passengers traveling between other two stations is predicted in the same way. Note that A and F are terminal stations on the P line. D is an intermediate station on the P line and the terminal station on the Q line, and is a transfer station between the P line and the Q line. H is the terminal station on the opposite side of the Q line.

[0059] During the initialization process, the OD prediction unit 22 extracts data from past OD data D1 that is estimated to be similar to the time-of-day OD prediction data to be generated this time. The OD prediction unit 22 sets the extracted data as initial values. This generates the initialized time-of-day OD prediction data (initial data). There are no particular limitations on the extraction method, the number of past OD data points D1 to extract, or whether or not the extracted data needs to be processed. In the example shown, the numerical values ​​of past OD data points D1 for the same day of the week and time of day one week prior are set as the initial values. On routes with high commuter and school traffic demand, it is easier to extract similar data by using the same day of the week.

[0060] The OD prediction unit 22 may also extract past time-based OD data for the same time period yesterday. On days when events with high drawing power (e.g., sports matches, concerts, festivals, etc.) are held along the railway line, the OD prediction unit 22 extracts past time-based OD data for the same time period on days when similar events were held. The OD prediction unit 22 may set the numerical value of a single historical time-segment OD data as its initial value, or it may set the average value of multiple time-segment OD data as its initial value. The initialization process can be executed at any time as long as it is completed by the end time t1 of the target time period T1. For example, the initialization process is executed at the start time t0 of the target time period T1.

[0061] (1st update) The first update process is executed at the end of the target time period T1, t1. The OD prediction unit 22 aggregates the passage data D10(t1) acquired at the end of the target time period T1, specifically the passage data D10 whose entry time falls within the target time period T1. Based on this, the OD prediction unit 22 determines the number of passengers Gi entering each station during the target time period T1. Note that some passengers may have already exited during the target time period T1, but the OD prediction unit 22 does not require exit station information or exit time information from the passage data D10(t1) in the first update process.

[0062] The OD prediction unit 22 allocates the confirmed number of passengers entering each station, Gi, as the number of passengers exiting other stations, using the same ratio as the initial values. This corrects the initial values ​​and generates the first updated time-specific OD prediction data (first update data). If Gi(t0) is the number of passengers entering station i in the initial data, and Tij(t0) is the number of passengers entering station i and exiting station j in the initial data, then the number of passengers entering station i and exiting station j, Tij(t1), is predicted based on the formula: Tij(t1) = Gi × (Tij(t0) / Gi(t0)). This predicted value Tij(t1) is then used to replace the initial value Tij(t0).

[0063] Specifically, in the first updated data, the number of passengers Tad(t1) entering at station A and exiting at station D is predicted to be 10. This is derived by multiplying the confirmed number of passengers entering at station A, Ga(80), by the ratio (11 / (11+33+44)) of the number of passengers entering at station A, Tad(t0), in the initial data to the number of passengers entering at station A, Ga(t0).

[0064] In other words, in the initial data, 88 passengers who entered at Station A exited at other stations (Station D, Station F, Station H) in a ratio of 1:3:4. When generating the first update data, the confirmed number of passengers entering Station A, Ga (80 people), was allocated to the other stations (Station D, Station F, Station H) as passengers exiting at the same ratio of 1:3:4 as the initial values ​​(10 people, 30 people, 40 people).

[0065] (2nd update) Figure 7 shows the second update process. The second update process is executed at the second update time t2, which is after the end time t1 of the target time period T1. At the second update time t2, some of the passengers who entered during the target time period T1 begin to exit. In the second update process, the exit station information and exit time information are referenced from the transit data D10 whose entry time falls within the target time period T1.

[0066] In the second update process, the OD prediction unit 22 extracts from the transit data D10(t2) acquired at the second update time t2 that the number of passengers traveling between two stations is greater than the corresponding number of passengers in the first update data. Then, the numerical value in the first update data is corrected by increasing it to the extracted number of passengers. Next, the OD prediction unit 22 offsets the increase correction amount by decreasing the number of passengers for other combinations where the entry station is the same but the exit station is different, thereby maintaining the number of passengers entering the entry station at the confirmed number.

[0067] The proportion of the reduction correction is determined by the ratio of passenger numbers for other combinations in the first update data. In this way, the time-specific OD forecast data (second update data) that has undergone the second update processing is generated. Specifically, at the second update time t2, the number of passengers Tfd(t2) who entered at station F and exited at station D was found to be 12 from the transit data D10(t2). This is more than the corresponding number of passengers Tfd(t1) of 10 from the first update data. Therefore, the OD prediction unit 22 applies an increase correction by replacing the number of passengers Tfd(t1) related to the movement between the two stations with the number of passengers Tfd(t2) found from the transit data D10(t2) acquired at the second update time t2.

[0068] The increase correction amount ΔTfd(Tfd(t2)-Tfd(t1)) is 2 people. If the increase correction were to be applied individually, the number of passengers entering station F, Gf, would increase to 47, and the confirmed number of 45 would not be maintained. Therefore, the number of passengers Tfa(t1) and Tfh(t1) for other combinations, using the same station F as the entry station but with a different exit station, is reduced. The decrease correction applies to the passenger numbers Tfa(t1) and Tfh(t1) for all combinations other than those for which an increase correction was applied, assuming the entry station is the same. The amount of the decrease correction is equal to the amount of the increase correction ΔTfd, thereby maintaining the number of entering passengers Gf. The ratio of the amount of the decrease correction is the ratio of the passenger numbers Tfa(t1) and Tfh(t1) for the combinations for which the decrease correction was applied, which in this embodiment is 3:2.

[0069] The number of passengers Tfa(t1) departing from station A will be subject to a 60% reduction adjustment, decreasing from 21 to 1.2 passengers. The number of passengers Tfh(t1) departing from station H will be subject to a 40% reduction adjustment, decreasing from 14 to 0.8 passengers. The ratio of passenger numbers Tfa and Tfh for the combinations subject to the reduction adjustment will remain at 3:2, the same as before the adjustment. Note that while the unit of passenger numbers is people, the predicted values ​​of passenger numbers do not need to be integers.

[0070] (3rd update) Figure 8 shows the third update process. The third update process is executed at the third update time t3, which is after the end time t1 of the target time period T1 and the second update time t2. By the third update time t3, it is assumed that all passengers who entered during the target time period T1 and whose destination was close to the entry station have already exited. Therefore, the OD prediction unit 22 determines the number of passengers traveling between two stations in combinations where the entry station and exit station are close to each other.

[0071] The OD prediction unit 22 refers to the longest travel time data D2 stored in the memory unit 12 in order to determine the number of passengers. The longest travel time data D2 defines the correspondence between combinations of entry and exit stations and the longest expected travel time required to travel from the entry station to the exit station. The longest travel time for each combination is a value obtained empirically by referring to the passage data D10 accumulated so far, and can be predetermined during the design and manufacturing stages of the dispatch reservation device 1.

[0072] In the illustrated example, the cell where the row for Station A and the column for Station D intersect is labeled "8". That is, in the longest travel time data D2, the combination of Station A as the entry station and Station D as the exit station is associated with a longest travel time of 8 minutes. It is also possible that the longest time may change if the entry and exit stations are swapped. This embodiment also handles this case (see "11" in the cell where the row for Station D and the column for Station A intersect). In this embodiment, when the number of stations within the data measurement range is n, n × (n-1) correspondence relationships are defined by the longest travel time data D2.

[0073] The OD prediction unit 22 determines the number of passengers for two-station travel where the longest travel time is shorter than the period T3 from the start time t0 of the target time period T1 to the third update time t3, based on the passage data D10(t3) acquired at the third update time t3. The closer the exit station is to the entry station, the shorter the longest travel time. By executing this process, the number of passengers for combinations where the exit station is close to the entry station is determined.

[0074] The OD prediction unit 22 then estimates the number of passengers who have not yet exited by subtracting the number of passengers in the confirmed combination from the number of passengers who have entered for the confirmed combinations of the same entry station. The estimated number of passengers who have not yet exited is then allocated as the number of passengers in the unconfirmed combinations. This generates the OD prediction data that has undergone the third update process (hereinafter referred to as the third update data). Specifically, if a passenger enters at Station A, the longest travel time to exit at Station D (8 minutes) and the longest travel time to exit at Station F (10 minutes) are both shorter than the total travel time during the above period T3 (15 minutes). From the transit data D10 (t3) obtained at the third update time t3, it was determined that the number of passengers Tad who entered at Station A and exited at Station D was 9. These 9 people are determined to be the number of passengers Tad (t3) for the combination of Station A as the entry station and Station D as the exit station. Similarly, 25 people are determined to be the number of passengers Taf (t3) for the combination of Station A as the entry station and Station F as the exit station.

[0075] On the other hand, the longest travel time (16 minutes) when H station is the exit station is longer than the above period T3. Therefore, the value (10 people) obtained from the transit data D10(t3) is not used to estimate the number of passengers Tah(t3) for the combination of A station as the entry station and H station as the exit station. Instead, the sum of the number of passengers Tad(t3) and Taf(t3) for combinations in which passengers entered A station and exited is confirmed is subtracted from the number of passengers Ga entering A station. This estimates the number of passengers who entered A station but did not exit (80-(9+25)=46).

[0076] In this embodiment, there is only one combination remaining where the longest travel time is longer than period T3 and departure cannot be confirmed. Therefore, the estimated number of passengers who have not yet departed (46 people) is directly allocated as the number of passengers Tah(t3) for that combination. If there are two or more combinations where the longest travel time is longer than period T3, the estimated number of passengers who have not yet departed may be allocated as the number of passengers for the two or more remaining undetermined combinations in proportion to the number of passengers in the second update data. Furthermore, the determination of the number of passengers using this longest travel time may be performed in the second update process at the second update time t2.

[0077] (Train allocation) The operation plan data referenced by the OD prediction unit 22 is stored in the memory unit 12. The operation plan data includes various information regarding the train operation schedule and specifications, such as which trains will run on which days and at what times, the operating section and stations for each train, the stopping and departure times at each station, the number of cars that make up each train, and the transport capacity (passenger capacity) of each train.

[0078] As an example of operation plan data, the memory unit 12 stores operation data D3 and holiday data D4, as shown in Figure 1. The operation data D3 includes operation pattern information that shows the train's operating pattern, and train information that shows the train's specifications (for example, the train's transport capacity). The operation pattern information is like a timetable. If trains operate according to different timetables on weekdays, weekends, and holidays, the operation data D3 includes multiple operation pattern information corresponding to multiple timetables. If extra trains operate on event days when events are held along the line, the memory unit 12 includes operation pattern information corresponding to these extra trains as operation data D3.

[0079] The holiday data D4 includes calendar information to determine whether the day is a weekday, weekend, or public holiday. This calendar information also includes information indicating whether or not it is an event day. By referring to the holiday data D4, it is possible to determine which operational pattern information should be applied when the operational data D3 contains multiple operational pattern information. The OD prediction unit 22 references search data necessary to find trains in order to estimate which train each passenger who enters a station will board, in addition to the operation plan data. The storage unit 12 stores station data D5, route data D6, and path data D7 as examples of search data.

[0080] Station data D5 contains information about the time required for transfers (in this embodiment, Station D is the transfer station) and the time required to move from the automatic ticket gate 6 at each station to the platform. Route data D6 contains information about the route map within the data measurement range. Path data D7 contains information about the route used when moving from a certain time, when on the platform of a certain entry station, to a certain exit station. By combining this path data D7 with past passage data D10, a path table is generated. Travel path tables are generated in advance for each station, for each time period, and for each condition such as the earliest travel path and the shortest transfer travel time, and these multiple travel path tables are stored in the train reservation device 1.

[0081] Figure 9 shows the train allocation process performed by the OD prediction unit 22. In the illustrated example, the OD prediction unit 22 performs the train allocation process by referring to the first update data in which the current estimated time is the end time t1 of the target time period T1. As mentioned above, in the first update data, the number of passengers entering each station during the target time period T1 is determined using the transit data D10(t1) acquired at the end of time t1 (i.e., the estimated time). Based on this determined number of entering passengers and the initial values, the number of passengers for each combination of entering and exiting stations is predicted. However, in the first update data, the number of passengers who have already exited has not been determined.

[0082] The OD prediction unit 22 searches for trains that passengers entering an entry station will use to travel to an exit station based on predetermined search conditions, and allocates the passengers to the searched trains as crew members. The search conditions include two or more conditions. Examples of search conditions include the condition for reaching the exit station as quickly as possible (condition 1) and the condition for minimizing the number of transfers (condition 2). The OD prediction unit 22 allocates passengers to each condition at a predetermined ratio according to the number of search conditions.

[0083] The OD prediction unit 22 further distributes the passengers assigned according to the conditions according to their entry time. The OD prediction unit 22 sets multiple estimated entry times by dividing the target time period T1 into predetermined time units (for example, 1-minute units). Then, the passengers assigned according to the conditions are further distributed as passengers who entered at each of the multiple estimated entry times. As an example, the OD prediction unit 22 evenly distributes the passengers assigned according to the conditions as passengers who entered at each estimated entry time.

[0084] The OD prediction unit 22 refers to the station data D5 to estimate the time when passengers who entered at each estimated entry time will arrive at the platform. Then, the OD prediction unit 22 refers to the operation data D3, route data D7, or route table to predict which train passengers who arrived at the platform at the estimated time will use to get to the departure station. The above process will be explained in more detail. For example, in the first update data, it is predicted that 30 passengers will enter station A and exit station F. The OD prediction unit 22 predicts which trains these 30 people will take to travel to station F.

[0085] Passengers' preferences also play a role in the trains they choose. These 30 passengers are then sorted according to multiple search criteria that correspond to their preferences. In this embodiment, two conditions are set: Condition 1, which ensures the fastest arrival at the departure station, and Condition 2, which ensures the fewest number of transfers. For example, the ratio of passengers traveling according to Condition 1 to those traveling according to Condition 2 is set to 6:4.

[0086] The OD prediction unit 22 estimates that 18 of the 30 passengers will travel according to condition 1, and 12 will travel according to condition 2. Thus, the 30 passengers are assigned to the two conditions. In this embodiment, the target time period T1 is 15:00 to 15:05, and five estimated entry times are set to the nearest minute. The OD prediction unit 22 evenly distributes the 18 passengers assigned to condition 1 as passengers who entered at each of the five estimated entry times. That is, the OD prediction unit 22 estimates that 18 / 5 passengers entered Station A by passing through the automatic ticket gate 6 at Station A at each estimated entry time. Similarly, the OD prediction unit 22 evenly distributes the 12 passengers assigned to condition 2 as passengers who entered at each of the five estimated entry times. More precisely, the entry time "15:00" refers to the time period "15:00:00 to 15:00:59," but for convenience, the time period with seconds omitted is referred to as "time." Also, the estimated number of passengers does not need to be an integer.

[0087] Here, as illustrated in the operation data D3, on Saturday, at Station A, trains bound for Station F, the terminus of Line P, and trains bound for Station H, which connects directly from Station D to Line Q, depart alternately every 5 minutes. Although detailed illustrations are omitted, trains operate on Line P, running back and forth between Station D and Station F. Passengers who board a train bound for Station H at Station A and alight at Station D can smoothly transfer to the aforementioned round-trip train. However, this operation pattern is merely a simplified example for the sake of explanation.

[0088] Furthermore, as exemplified in station data D5, it is assumed that at Station A, it takes 2 minutes to travel from automatic ticket gate 6 to the platform. The OD prediction unit 22 searches for the trains that passengers who entered Station A at each estimated entry time would likely take to travel to Station F, according to the search conditions. A passenger who passed through automatic ticket gate 6 at Station A at 15:00 will reach the platform at Station A at 15:02. If the passenger who arrived on the platform at 15:02 wants to travel to Station F as quickly as possible, it is estimated that they will board train A bound for Station F departing at 15:04. Therefore, the OD prediction unit 22 estimates that the 18 out of 5 passengers who entered at 15:00 will board train A departing at 15:04. Similarly, the OD prediction unit 22 estimates that the 18 out of 5 passengers who entered at 15:01 and the 18 out of 5 passengers who entered at 15:02 will also board the same train A in order to travel to Station F as quickly as possible.

[0089] Passengers who entered at 15:03 will reach the platform at 15:05, after train A has departed. Passengers arriving at the platform at 15:05 are estimated to board train B bound for station H, departing at 15:09, and transfer to a train bound for station F at station D, in order to reach station F as quickly as possible. The OD prediction unit 22 estimates that the 18 out of 5 passengers who entered at 15:03 will board train B departing at 15:09 and the round-trip train between stations D and F. Similarly, the OD prediction unit 22 estimates that the 18 out of 5 passengers who entered at 15:04 will also board train B and the round-trip train in order to reach station F as quickly as possible.

[0090] On the other hand, a passenger who enters Station A at 15:00 and arrives at the platform at 15:02 is estimated to board train A bound for Station F departing at 15:04 if they wish to travel to Station F with the fewest possible transfers. The OD prediction unit 22 estimates that 12 out of 5 passengers who entered at 15:00 will board train A. The OD prediction unit 22 also estimates that 12 out of 5 passengers who entered at 15:01 and 12 out of 5 passengers who entered at 15:02 will board train A in order to travel to Station F with the fewest possible transfers.

[0091] A passenger who enters Station A at 15:03 and arrives at the platform at 15:05 is estimated to want to travel to Station F with the fewest transfers possible. In this case, they would likely pass by train B departing at 15:09 bound for Station H, which requires a transfer at Station D, and instead board the next train C departing at 15:14 bound for Station F. The OD prediction unit 22 estimates that 12 out of 5 passengers who enter at 15:03 and travel according to condition 2 will board train C departing at 15:14. Similarly, the OD prediction unit 22 estimates that 12 out of 5 passengers who enter at 15:04 will also board train C in order to travel to Station F with the fewest transfers possible.

[0092] The train allocation process described above applies to the passenger count Taf(t1) for one combination of all possible combinations of entry and exit stations in the first update data. The OD prediction unit 22 performs the same process for all remaining combinations in the first update data. Then, the OD prediction unit 22 refers to initialization data where the estimated time is the start time t0 of the target time period T1, and performs the same processing as described above.

[0093] Furthermore, the OD prediction unit 22 refers to the second update data whose estimated time is the second update time t2 and performs the same processing as described above, and refers to the third update data whose estimated time is the third update time t3 and performs the same processing as described above. Unlike the initialization data and the first update data, the second and third update data have partially determined the number of passengers who have already departed. Passengers who have departed have already completed their journey by train. Therefore, when using this update data, the OD prediction unit 22 estimates how many passengers boarded which trains for combinations of passengers whose departure is not yet determined.

[0094] (Handling of sections where service is disrupted) As described above, the dispatch reservation device 1 of this embodiment uses the estimation results from the train allocation process performed by the OD prediction unit 22 to estimate how many passengers are on a train that is stopped due to a section of track being closed due to equipment failure or an accident such as a vehicle or signal failure. The dispatch reservation device 1 also estimates the destination of each passenger on the stopped train when a section of track is closed. Furthermore, when a section of track is closed, the dispatch reservation device 1 determines the type of other means of transportation (such as buses) and the number of vehicles for the other means of transportation necessary to transport passengers by road to the estimated destination, based on the estimated number of passengers on each stopped train and the destination of each passenger, and creates an operation plan for each vehicle.

[0095] Specifically, in the vehicle dispatch reservation device 1 of this embodiment, as shown in Figure 9, the number of passengers for each train stopped due to the disruption in service and the destination (disembarking station) of each passenger are estimated using the passage data D10 recorded at the automatic ticket gate 6. Then, based on the estimated number of passengers for each train and the destination of each passenger, the vehicle dispatch reservation device 1 creates an operation plan that determines how many buses to send to which station.

[0096] In other words, when a section of the line becomes inoperable due to a malfunction, accident, etc., information about the inoperable section is entered by station staff or others into the input reception unit 13 shown in Figure 1. At this time, the dispatch reservation device 1 receives information about the occurrence of a section of track that is out of service, and the central processing unit 11 reads the dispatch reservation program P and executes the dispatch reservation method. The stop information acquisition unit 23 receives information about the occurrence of a section of service disruption and acquires information identifying the stopped train (train information) and information regarding the time of the stop.

[0097] The passenger information estimation unit 24 then compares the information of the stopped train with the information of the train whose number of passengers was estimated by the OD prediction unit 22 described above. If there are multiple stopped trains, the estimated number of passengers for each train is referred to. Furthermore, the passenger information estimation unit 24 estimates the number of passengers for each stopped train and the destination of each passenger, which is stored in the main memory unit 12a of the storage unit 12 as passenger number estimation data D12 and passenger destination estimation data D13.

[0098] The alternative transportation planning unit 25 arranges multiple buses as alternative means of transporting passengers from each train to their destinations, based on estimated data D12 and D13 regarding the number of passengers for each stopped train and each passenger's destination. Specifically, the alternative transportation planning unit 25 creates a bus operation plan to transport passengers from stopped trains to their respective destinations, for example, based on data on buses not currently in operation (bus non-operation data D8) owned by a bus company owned by a railway company that owns a line including a train station.

[0099] The bus operation plan, which is created in the alternative transportation plan creation unit 25, is stored as bus arrangement data D14 in the main memory unit 12a of the storage unit 12. Here, we will specifically explain, using Figure 9, the estimation of the number of passengers on a stopped train and the estimation of each passenger's destination when information about a disrupted section of the line is entered during a certain time period. For example, as shown in Figure 9, of the 30 passengers estimated to enter between 15:00 and 15:05 and whose destination is Station F, under the condition of reaching the exit station as quickly as possible (Condition 1), the train allocation process estimates that 30 × 0.6 / 5 × 3 = 10.8 people are on the 15:04 train.

[0100] Similarly, among the 30 passengers estimated to enter the station between 15:00 and 15:05 and whose destination is Station F, under the condition of having the fewest number of transfers (Condition 2), the train allocation process estimates that 30 × 0.4 / 5 × 3 = 7.2 people are on the 15:04 train. Furthermore, of the 30 passengers who entered between 15:00 and 15:05 and whose destination was estimated to be Station F, under the condition of reaching the exit station as quickly as possible (Condition 1), it is estimated that 30 × 0.6 / 5 × 2 = 7.2 people were on the 15:09 train, according to the train allocation process.

[0101] Furthermore, among the 30 passengers estimated to have entered the station between 15:00 and 15:05 and whose destination was Station F, under the condition of having the fewest number of transfers (Condition 2), the train allocation process estimates that 30 × 0.4 / 5 × 2 = 4.8 people were on the 15:14 train. In the train dispatch reservation device 1 of this embodiment, the number of passengers on board each stopped train is estimated as described above.

[0102] As shown in Figure 9, for example, for the train departing at 15:04, the number of passengers disembarking at Station F (destination) is estimated to be 10.8 people (condition 1) + 7.2 people (condition 2) = 18 people. Similarly, for the train departing at 15:09, the estimated number of passengers disembarking at Station F (destination) is 7.2 (Condition 1).

[0103] Similarly, for the train departing at 15:14, the estimated number of passengers disembarking at Station F (destination) is 4.8 (Condition 2). Similarly, the number of passengers per train can be estimated for passengers whose destination is a station other than Station F. In the vehicle reservation device 1 of this embodiment, as described above, the destination of each passenger on each train is estimated, and the number of passengers at each destination is estimated. Therefore, the alternative transportation plan creation unit 25 can recognize how many passengers on each train are scheduled to disembark at each station, and then create an alternative transportation plan using other means of transport, such as buses.

[0104] Then, the dispatch reservation device 1 identifies the nearest station to the stopped train based on the time the disruption occurred and the train schedule information, and determines how many buses to send to which station. Here, for example, if a section of track is disrupted between stations C and D as shown in Figure 3, stations A, B, and C, which are upstream of that section, will become the nearest stations to the stopped train.

[0105] For example, if it is estimated that there are 90 passengers on a train whose nearest station is Station C and 40 passengers on a train whose nearest station is Station B, then, as shown in Figure 10(A), three buses A, B, and C, each with a capacity of 30 passengers, will be preferentially allocated to Station C, which is the nearest station to the train with the most passengers, and will be arranged to proceed to their respective destinations (Station F or Station H).

[0106] Furthermore, at Station B, which is the nearest station to the next busiest train, two 30-seat buses, D and E, are arranged to go to their respective destinations (Station F or Station E). This bus allocation process continues until there are no more buses available to operate. In the example shown in Figure 10(A), we described an example where the alternative transportation schedule is created so that buses are preferentially allocated to the nearest stations of trains with a large number of passengers. However, as shown in Figure 10(B), the alternative transportation schedule may also be created so that buses are preferentially allocated to the number of destinations in descending order.

[0107] Specifically, since the destinations of passengers on board tend to be higher towards the nearest station further upstream, for example, at station A, as shown in Figure 10(B), there are four destinations for passengers: stations D, E, F, and H. At station B, there are three destinations: stations D, E, and F. Therefore, in order of priority to allocating buses to stations with a greater number of destinations, such as stations A and B, a replacement transportation plan is created to send four buses A-D to station A and three buses E-G to station B.

[0108] (output) As shown in Figure 1, the output unit 14 outputs passenger flow forecast results (OD forecast data D11), estimated passenger number data for each train D12, estimated passenger destination data D13, and bus arrangement data D14 to the administrator terminal 3, signage 4, and user terminal 5. The signage 4 and user terminal 5 will display information from the prediction and estimation results, such as bus operation plans as an alternative means of transportation when a section of the line is out of service.

[0109] This allows passengers on trains stopped due to service disruptions to be aware, via the user terminal 5, that buses have been arranged as an alternative means of transportation from the nearest station. Furthermore, via the administrator terminal 3, station staff can easily determine how many buses have been arranged as an alternative means of transportation from the nearest station to trains stopped due to service disruptions.

[0110] <How to book a ride> Figure 11 is a flowchart showing the vehicle dispatch reservation method according to this embodiment. The operation of each part of the vehicle dispatch reservation device 1 is realized by the vehicle dispatch reservation program P, which causes the computer to execute the vehicle dispatch reservation method. Therefore, the vehicle dispatch reservation method will be explained briefly. The flow shown in Figure 11 is executed sequentially at the aforementioned acquisition cycle of the passage data D10 (for example, every 5 minutes). First, the passenger information acquisition unit 21 acquires the passage data D10 from the automatic ticket gate 6 via the communication network 9 and the passage data collection server 2. Next, in step S12, the OD prediction unit 22 performs OD prediction. Next, in step S13, based on the time-of-day OD prediction data generated by the OD prediction in step S12, it is estimated which train each passenger who passed through the automatic ticket gate 6 boarded, and the passengers are assigned to each train.

[0111] Next, in step S14, the input reception unit 13 determines whether or not information about a service disruption has been entered. If it is determined that information about a service disruption has been entered, it is determined that an alternative means of transportation needs to be arranged because a service disruption has occurred, and the process proceeds to step S15. On the other hand, if information about a service disruption has not been entered, the system waits until information is entered. Next, in step S15, since it was determined in step S14 that information regarding the occurrence of a section of service disruption had been input, the stop information acquisition unit 23 acquires information regarding trains that are stopped due to the occurrence of a section of service disruption (train number, stopping time, etc.) based on the operation data D3 etc. stored in the auxiliary storage unit 12b of the storage unit 12.

[0112] Next, in step S16, the passenger information estimation unit 24 estimates the number of passengers per train by destination based on the time-of-day OD prediction data generated by the OD prediction in step S12 and the passenger train allocation performed in step S13 (passenger information estimation step). Next, in step S17, the alternative transportation planning unit 25 estimates the nearest station for each train that is stopped due to the disruption, based on the time the disruption occurred and the timetable information.

[0113] Next, in step S18, based on the estimated nearest station where the train is stopped, which was estimated in step S17, and the bus non-operation data D8 stored in the auxiliary storage unit 12b, the alternative transportation plan creation unit 25 assigns bus destinations and bus routes to each passenger on the train until there are no more buses available, and creates an alternative transportation plan (alternative transportation plan creation step).

[0114] Next, in step S19, based on the alternative transportation plan created in step S18, notifications regarding the alternative transportation are sent via the administrator terminal 3, signage 4, and user terminal 5. This allows railway companies to efficiently arrange alternative transportation in the event of service disruptions, and, if they own a bus company as an affiliate, they can prevent passengers from switching to other companies.

[0115] Furthermore, station staff at railway stations can easily grasp the status of arrangements for alternative transportation in the event of a service disruption via the administrator terminal 3, allowing them to efficiently carry out necessary processing. Furthermore, passengers on trains on lines experiencing service disruptions can recognize that alternative transportation has been arranged via user terminals such as smartphones 5. As a result, when their train arrives at the nearest station, they can board a bus arranged to take them to their destination.

[0116] [Other embodiments] Although one embodiment of the present invention has been described above, the present invention is not limited to the above embodiment, and various modifications are possible without departing from the spirit of the invention.

[0117] (A) In the above embodiments, examples of the present invention were described as a vehicle dispatch reservation device and vehicle dispatch reservation method. However, the present invention is not limited thereto. For example, the present invention may be implemented as a vehicle dispatch reservation program that causes a computer to execute the vehicle dispatch reservation method described above.

[0118] This vehicle dispatch reservation program is stored in the memory (storage unit) installed in the vehicle dispatch reservation device. The CPU reads the vehicle dispatch reservation program stored in memory and causes the hardware to execute each step. More specifically, the CPU reads the vehicle dispatch reservation program and executes the passenger information estimation step and the alternative transportation plan creation step described above, thereby achieving the same effect as above. Furthermore, the present invention may be implemented as a recording medium that stores a vehicle dispatch reservation program.

[0119] (B) In the above embodiment, an example was given in which the number of passengers on a train stopped in a disrupted section and the destination of each passenger are estimated from passenger entry and exit data acquired by multiple automatic ticket gates 6 installed at a railway station. However, the present invention is not limited to this. For example, past OD data for each passenger stored in a memory unit or similar device may be used to estimate the number of passengers on a train stopped in a section where service is suspended, and the destination of each passenger.

[0120] (C) In the above embodiment, an example was given in which a bus was used as an alternative means of transportation in the event of a section being out of service. However, the present invention is not limited to this. For example, alternative means of transportation do not have to be buses; other means of transportation such as taxis may also be used. [Industrial applicability]

[0121] The vehicle dispatch reservation device of the present invention has the effect of enabling smooth transfers to other means of transportation when a section of a railway line at a station is disrupted, and therefore can be widely applied to various devices that provide alternative transportation. [Explanation of symbols]

[0122] 1. Vehicle dispatch reservation system 2. Transaction data collection server 3. Administrator terminal 4. Digital Signage 5. User terminals 5A App 6 Automatic ticket gates 9. Communication Network 11 Central processing unit 12 Storage section 12a Main memory 12b Auxiliary storage 13 Input Reception Section 14 Output section 15 Communications Bus 21 Passenger Information Acquisition Department 22 OD prediction unit 23 Stop information acquisition section 24 Passenger Information Estimation Department 25. Alternative Transportation Planning Department 30. Ride-hailing reservation system D1 Past OD data D2 Longest Travel Time Data D3 Operation Data D4 Public Holiday Data D5 Station Data D6 Route Data D7 Route Data D8 Bus non-operation data D11 OD prediction data D12 Estimated passenger count data for each train D13 Passenger destination estimation data D14 Bus arrangement data P Ride-hailing reservation program

Claims

1. A vehicle dispatch reservation system that arranges alternative transportation for passengers to other means of transport besides trains in sections of railway lines where service is disrupted, An input receiving unit into which operational information regarding the occurrence of the aforementioned section of service disruption is entered, A stop information acquisition unit acquires, from the aforementioned operational information, train information and time information regarding the time of the stop for the train that is stopped due to the occurrence of the aforementioned section of service disruption. A passenger information estimation unit estimates the number of passengers on a train stopped due to the disruption in service and the destination of each passenger, based on the aforementioned train information and time information. Based on the time the aforementioned section of service was disrupted and the timetable information of the trains stopped due to the disruption, the system estimates the nearest station for each stopped train, and based on the estimated number of passengers, each passenger's destination, and the nearest station, determines the type of other means of transportation to be dispatched to each nearest station, the number of vehicles for the other means of transportation, and the route of the other means of transportation, and creates an alternative transportation plan for each vehicle. A ride-hailing reservation system equipped with the following features.

2. The passenger information estimation unit estimates the number of passengers and their destinations based on entry records obtained from automatic ticket gates installed at the railway station. The vehicle dispatch reservation device according to claim 1.

3. The passenger information estimation unit estimates the number of passengers and their destinations by referring to past Origin-Destination (OD) data. A vehicle dispatch reservation device according to claim 1 or 2.

4. The system further includes an output unit that outputs the vehicle operation plan created in the alternative transportation plan creation unit. A vehicle dispatch reservation device according to claim 1 or 2.

5. The alternative transportation planning unit creates an operation plan for each vehicle so as to prioritize sending the vehicles of the other means of transportation to the nearest station of the train that has a large number of passengers subject to alternative transportation. A vehicle dispatch reservation device according to claim 1 or 2.

6. The alternative transportation planning unit creates operation plans for each vehicle so that the nearest station located further upstream is given priority in directing the vehicles of the other means of transportation toward it. A vehicle dispatch reservation device according to claim 1 or 2.

7. A vehicle dispatch reservation device according to claim 1 or 2, The aforementioned railway station is equipped with multiple automatic ticket gates that record the entry and exit of each passenger to and from the railway station, A ride-hailing reservation system equipped with these features.

8. A method for arranging alternative transportation for passengers on a railway line that is out of service due to a disruption in service, using means other than trains. An input reception step in which the input reception unit receives input of operational information regarding the occurrence of the aforementioned section of service disruption, A stop information acquisition step in which the stop information acquisition unit acquires train information and time information regarding the time of stopping from the aforementioned operational information, the aforementioned stop information acquisition step, A passenger information estimation step in which, based on the aforementioned train information and time information, the passenger information estimation unit estimates the number of passengers on the train that is stopped due to the disruption in service and the destination of each passenger, Based on the time the aforementioned section of service was disrupted and the timetable information of the trains stopped due to the disruption, the Alternative Transportation Planning Unit estimates the nearest station for each stopped train, and based on the estimated number of passengers, each passenger's destination, and the nearest station, the Alternative Transportation Planning Unit determines the type of other means of transportation to be dispatched to each nearest station, the number of vehicles for the other means of transportation, and the operating route for the other means of transportation, and then creates an operating plan for each vehicle in the Alternative Transportation Planning Unit step. A ride-hailing reservation method that includes the following features.

9. A vehicle dispatch reservation program that arranges alternative transportation for passengers on a railway line that is out of service due to a disruption in service, An input reception step in which the input reception unit receives input of operational information regarding the occurrence of the aforementioned section of service disruption, A stop information acquisition step in which the stop information acquisition unit acquires train information and time information regarding the time of stopping from the aforementioned operational information, the aforementioned stop information acquisition step, A passenger information estimation step in which, based on the aforementioned train information and time information, the passenger information estimation unit estimates the number of passengers on the train that is stopped due to the disruption in service and the destination of each passenger, Based on the time the aforementioned section of service was disrupted and the timetable information of the trains stopped due to the disruption, the Alternative Transportation Planning Unit estimates the nearest station for each stopped train, and based on the estimated number of passengers, each passenger's destination, and the nearest station, the Alternative Transportation Planning Unit determines the type of other means of transportation to be dispatched to each nearest station, the number of vehicles for the other means of transportation, and the operating route for the other means of transportation, and then creates an operating plan for each vehicle in the Alternative Transportation Planning Unit step. A ride-hailing reservation program that uses a computer to execute a ride-hailing reservation method that includes the following features.

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