WO2015063823A1

WO2015063823A1 - Train schedule preparation assist system, and train schedule preparation assist method

Info

Publication number: WO2015063823A1
Application number: PCT/JP2013/079083
Authority: WO
Inventors: 侑子武田
Original assignee: 株式会社日立製作所
Priority date: 2013-10-28
Filing date: 2013-10-28
Publication date: 2015-05-07
Also published as: JPWO2015063823A1; JP6224123B2

Abstract

In order to enable proper prior modification of a train schedule in accordance with predicted demand variation, a train schedule preparation assist system (1) is mainly provided with a human flow measurement/prediction device (100) and a schedule preparation device (200). In the human flow measurement/prediction device (100), a human flow measurement result from a human flow measurement device (700) and information about an external factor that may have an influence on transport demand received from an external information reception device (600) are stored in association with each other. Upon detection of a modification in the external factor, the human flow measurement/prediction device predicts the number of passengers getting aboard between stations in a target track section on the basis of a past human flow measurement result associated with the modified external factor, and stores the predicted number in a human flow prediction database (300). The schedule preparation device (200) acquires the predicted value of the number of passengers getting aboard between the stations from the human flow prediction database (300) with regard to the track section that has experienced the modification in the external factor, and extracts the corresponding number of trains between the stations with reference to an on-board passenger number versus train number table (223) that is retained in advance for the relevant track section.

Description

Train diagram creation support system and train diagram creation support method

The present invention relates to a train diagram creation support system and a train diagram creation support method.

In the conventional rail transport plan, basic train schedules are formulated based on transport demand and management policy of the management entity. The train schedule formulated in this way is operated for a relatively long period of time. Therefore, even if a change in demand can be predicted immediately before, it is difficult to flexibly change the set train schedule. In this regard, Japanese Patent Laid-Open No. 9-123913 (Patent Document 1) states that “the appropriate number of trains, departure delay time, and departure shortening time are determined based on the predicted demand number for each time zone of the representative section of the target line section. It is calculated, and train entry / exit settings are performed at the entry / exit station based on the calculated departure delay time and departure shortening time ”. In the following description, when simply described as “diamond”, it means “train diamond”.

JP-A-9-123913

As described above, in the current transportation plan, the train schedule once determined when the train schedule is revised is basically not changed until the next schedule revision. Even if it can be predicted that the demand will change due to factors such as weather and events, it is difficult to change the diagram flexibly in response to short-term demand fluctuations due to problems with the operation of vehicles and crew. As a result, a situation may arise where the transportation demand and the supply transportation capacity do not match. If the supply and transport capacity is excessive, the railway operator will use extra resources such as electricity and vehicles. On the other hand, if the transportation capacity is insufficient with respect to the transportation demand, the passengers will be congested and the convenience of the user may be impaired. In Patent Document 1, an appropriate number of trains is calculated based on the demand on the day, and the entry / exit of the train on the day is adjusted. However, the entry / exit on and after the next day is not changed. In addition, if the diamond is changed on the day, there is a concern that the burden on the crew and the vehicle base staff will increase because preparations cannot be made in advance.
One object of the present invention is to provide a train diagram creation support system and a train diagram creation support method that enable a train diagram to be appropriately changed in advance according to a predicted demand fluctuation.

In order to achieve the above object and the like, one aspect of the present invention is a train diagram creation support system for supporting a plan of a train diagram corresponding to demand fluctuation prediction, and is a station belonging to a managed line area The number of people getting on and off at each station is calculated from the flow measurement results collected for each station, and stored as flow measurement / external factor result information in association with external information that is information about external factors that cause demand fluctuations. The external information related to the external factor that is scheduled to occur in the future is stored as external factor prediction information, and when a change is detected in the external information of the external factor that is scheduled in the future, the external information is changed according to the changed external information. Update the factor prediction information and acquire the human flow measurement / external factor result information including the external information that matches the changed external information, and Calculate the number of passengers between each station in the line section where the external information change occurs from the flow measurement / external factor result information, and store the current flow prediction information and the change of the external information received from the flow prediction unit The person flow prediction information corresponding to the date and time of occurrence of the change is acquired based on the information, and driving between the stations should be performed based on the number of passengers between the stations of the line section where the external information change included in the person flow prediction information occurs. A train number calculation unit for calculating the number of trains.

According to one aspect of the present invention, the train schedule can be appropriately changed in advance according to the predicted demand fluctuation.

FIG. 1 is a configuration example of a train diagram creation support system 1 according to an embodiment of the present invention. FIG. 2 is a flowchart showing a processing example of the entire train diagram creation support system. FIG. 3 is a flowchart showing an example of normalization processing for converting the human flow measurement result into a useful data format. FIG. 4 is a flowchart showing an example of normalization processing for converting external information into a useful data format. FIG. 5 is a flowchart illustrating an example of a passenger number variation calculation process in each line section and each station. FIG. 6 is a flowchart illustrating an example of a human flow predicted value calculation process. FIG. 7 is a flowchart illustrating an example of a train number calculation process. FIG. 8 is a flowchart illustrating an example of a calculation process of the number of trains between stations. FIG. 9 is a flowchart illustrating an example of a process for calculating the number of trains for distinguishing lines. FIG. 10 is a flowchart illustrating an example of a process for calculating the optimum number of trains. FIG. 11 is an example of an output screen in the train diagram creation support system 1. FIG. 12 is a flowchart illustrating a train plan, vehicle operation plan, and crew member operation plan processing example. FIG. 13A is a configuration example of the human flow measurement result / external factor result table 107. FIG. 13B is a configuration example of the human flow measurement result / external factor result table 107. FIG. 14 is a configuration example of the external factor prediction table 108. FIG. 15 is a configuration example of the human flow prediction table 111. FIG. 16 is a configuration example of the number of passengers vs. number of trains table 114. FIG. 17 is a configuration example of the train number prediction table 115. FIG. 18 is a configuration example of the train number allowable range table 116. FIG. 19 is a configuration example of the basic number table 117. FIG. 20 is a configuration example of the alternative route table 118.

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. FIG. 1 is a diagram illustrating a configuration example of a diagram creation support system 1 according to the present embodiment. The diagram creation support system 1 includes a human flow measurement / prediction device 100 (human flow prediction unit), a diagram creation device 200, a human flow prediction database 300, an input / output device 400, an external information receiving device 600, and a human flow measurement device 700. The components are communicably connected by a communication network.

The human flow measurement / prediction device 100 has, for each railway line section for which the schedule is created, the human flow measurement data at each station received from the flow measurement device 700, the calendar data received from the external information reception device 600, and the weather prediction. It has a function of correlating external information data such as data and event holding data with each other, predicting the number of train passengers at each station in the target line section, and storing the result in the human flow prediction database 300.

Here, the human flow measuring device 700 is configured as a computer having a function of calculating human flow measurement data from a human flow monitoring device such as a camera and a sensor installed in each station, and having a communication function. Human flow measurement can be carried out by a known method, and for example, related technology is described in Japanese Patent Application Laid-Open No. 2013-116677.

The external information receiving device 600 receives external information that may cause fluctuations in the flow of people at each station, such as current and future weather and events, from an information server provided at a railway company or the like where the system 1 is installed. It is an apparatus which acquires and transmits to the human flow measurement / prediction apparatus 104, and can be configured as a computer having a communication function. The external information receiving device 600 includes an external information receiving unit 601 and an external information raw data table 602. The external information receiving unit 601 receives external information from an information server or the like not shown. The external information raw data table 602 stores the raw data received from the external information receiving unit 601. The external information raw data means a group of data that has been acquired from an information server or the like and has not been processed, and this external information raw data is used in the human flow measurement / prediction device 100 as described later. It is processed into a data format suitable for processing in

The human flow measurement / prediction device 100 includes a processor 110, a memory 120, and a data input / output unit 130. The processor 110 is an arithmetic device such as a CPU (Central Processing Unit) or an MPU (MicroProcessing Unit), and executes a program that realizes functions of the human flow measurement / prediction device 100 described later. The memory 120 has storage devices such as a ROM (Read Only Memory) and a RAM (Random Access Memory), and stores programs for realizing the functions of the human flow measurement / prediction device 100 described later, and data used by these programs. ing. Although not shown, the memory 120 is also mounted with system software (operating system, OS) that is the execution base of the program. The human flow measurement / prediction device 100 includes an auxiliary storage device such as a hard disk drive and a semiconductor drive in addition to the memory 120, and reads the program and data from the auxiliary storage device to the memory 120 as necessary. Also good. The data input / output unit 130 has an interface function for executing data transmission / reception processing with another device via a communication network, and an input / output processing function for the data.

In the human flow measurement / prediction apparatus 100, programs of a human flow processing unit 121, an external information processing unit 122, a change amount calculation unit 123, and a human flow calculation unit 124 are installed. The human flow processing unit 121 has a function of converting a human flow measurement result received from the human flow measurement device 700 into a data format suitable for processing in the human flow measurement / prediction device 100. The external information processing unit 122 has a function of converting raw external information data received from the external information receiving device 600 into a data format suitable for processing in the human flow measurement / prediction device 100. The change amount calculation unit 123 has a function of calculating the change amount of the number of passengers between the stations in the line area that is the processing target of the human flow measurement / prediction apparatus 100. The human flow calculation unit 124 has a function of predicting future human flow fluctuations in the line segment to be processed based on the data processed by the human flow processing unit 121 and the external information processing unit 122. Details of the processing by these programs will be described later using a processing flow example.

In the memory 120 of the human flow measurement / prediction apparatus 100, a human flow measurement / external factor result table 125 (human flow measurement external factor result information) storing data used by the program for realizing the function, and an external factor prediction table 126 (external factor prediction information) is held. The human flow measurement / external factor result table 125 stores the human flow measurement results associated with each other and the external factors that cause the fluctuation of the human flow extracted from the external information. The external factor prediction table 126 stores future external factor prediction values. Specific configuration examples of the human flow measurement / external factor result table 125 and the external factor prediction table 126 will be described later together with a processing flow example of a related program.

Similar to the human flow measurement / prediction device 100, the diagram creation device 200 is configured as a computer having a communication function including a processor 210, a memory 220, and a data input / output unit 240, and is calculated by the human flow measurement / prediction device 100. It has the function of calculating the number of future trains according to the demand from the forecast and realizing support for the train plan, vehicle operation plan, and crew member operation plan. The train schedule creation device 200 may include an auxiliary storage device such as a hard disk drive or a semiconductor drive in addition to the memory 220.

The memory 220 stores a program for realizing the function of the diagram creation device 200. The number-of-trains calculation unit 221 has a function of calculating the number of trains that run on the target line according to the predicted human flow. The diagram creation calculation unit 222 has a function of providing data such as the number of trains set corresponding to the demand forecast to these planning departments in order to execute a future train plan, a vehicle operation plan, and a crew member operation plan. Have. Although not shown in the figure, the memory 220 is also mounted with system software (operating system, OS) as an execution base of the program.

In the memory 220, various data used when the program is executed are recorded. Number of passengers vs. train number table 223 (number of passengers vs. number of trains information), number of trains prediction table 224 (train number prediction information), number of trains allowed A range table 225 (overall and inter-station train number allowable range information), a basic number table 226 (basic number information), and an alternative route table 227 (alternative route information) are stored. The number of passengers vs. number of trains table 223 stores information for calculating the number of trains according to the number of passengers at each station in the target line area. The train number prediction table 224 stores an appropriate number of future trains according to the flow of people at each station. The basic number table 226 stores a range of the number of trains that can travel between each line section and each station. The basic number table 226 stores the basic number of trains traveling on the route for each day of the week and each time zone. The alternative route table 227 stores data of other routes that can be substituted when the number of trains corresponding to the human flow prediction cannot be set in each section of the target line section. Configuration examples of these tables will be described later with reference to a processing flow example of a program that uses them.

In addition, a train plan table 228 that stores a future train plan, a vehicle operation plan, and a crew plan created in the memory 220 based on the number of trains in the target line section set by the train schedule creation device 200 from the demand prediction, A vehicle operation plan table 229 and a crew member operation plan table 230 are stored. The contents of these tables are, for example, result data created in each planning department in order to specifically realize the number of trains based on the demand prediction calculated by the train diagram creation device 200 for the target line section.

The input / output device 400 is calculated by the input device such as a keyboard, a mouse, and a touch panel for giving data input and operation command input to the human flow measurement / prediction device 100 and the diagram creation device 200 and the diagram creation device 200. It includes output devices such as liquid crystal displays, LED panels, and printers for displaying information such as the number of trains and the resulting diagram.

The human flow prediction database 300 is a database used in common by the human flow measurement / prediction device 100 and the diagram creation device 200, and can be configured as a computer having a communication function. The human flow prediction database 300 stores future human flow prediction values generated by the human flow measurement / prediction device 100. Since the human flow prediction database 300 is used in common by the human flow measurement / prediction device 100 and the diagram creation device 200, accurate and prompt information transmission to both devices is possible. The human flow prediction database 300 may be provided as independent hardware as shown in FIG. 1 or may be provided integrally with any component of the system 1 such as the human flow measurement / prediction device 100.

The related device 500 is a terminal device installed in an in-service department, for example, a vehicle base, a crew base, etc., for specifically realizing the plan diagram calculated by the diagram creation device 200. In the diagram creation support system 1 of the present embodiment, the diagram creation support processing based on human flow prediction is realized by the configuration as described above. This makes it possible to flexibly create future diagrams that meet demand. In addition, as the related apparatus 500, the operation management system etc. which actually carry out operation control of the train by the diamond created by the support function of this system 1 can also be assumed.

Next, processing executed by the entire diagram creation support system 1 of the present embodiment having the above-described configuration will be described. FIG. 2 is a flowchart showing a processing example of the entire diagram creation support system 1 of the present embodiment. The system 1 starts the entire process according to a process execution schedule set in the human flow measurement / prediction apparatus 100 or the like in advance or by a process start input from the input / output device 400 (S10). Thereafter, the human flow measurement / prediction apparatus 100 first receives the current flow measurement result from the human flow measurement apparatus 700 and simultaneously receives external information from the external information apparatus 600 that causes fluctuations in the human flow (S11). Next, the human flow measurement / prediction apparatus 100 extracts information to be used in the system 1 from the received human flow measurement result and the raw data of the external information, and converts the data into a data format that can be stored in the memory 120 (hereinafter, “ (Referred to as “normalization”) (S12). Next, the human flow measurement / prediction device 100 calculates the amount of change in the number of passengers in each line section and each station, which is the management target of the present system 1, from the normalized data, and stores it in the memory 120 (S13).

Next, when the human flow measurement / prediction apparatus 100 determines that the external factor prediction has changed when normalizing the external information in the future, the external factor prediction is changed from the external factor prediction and the stored passenger amount change amount. The human flow prediction process is executed at the date and time (S14). The calculated human flow prediction result data is stored in the human flow prediction database 300 and shared with the diagram creation device 200. The diagram creating apparatus 200 calculates the number of trains that can be handled based on the human flow prediction result data stored in the human flow prediction database 300, and outputs it to the display of the input / output device 400 (S15). Based on the calculated number of trains, a train schedule is created in each section of the train plan, vehicle operation plan, and crew operation plan, and a future schedule is formed by formulating the vehicle operation plan and crew operation plan (S16). ). The planned future diagram is transmitted to the related device 500 by the diagram creation device 200, and this process is terminated (S17, S18). According to the present embodiment, in order to create a diagram by calculating an appropriate number of trains based on the prediction of the flow of people based on changes in the flow of people due to changes in external factors, a diagram that can provide a transportation capacity in accordance with a change in transportation demand is planned. be able to.

Next, each processing step executed in the overall processing of FIG. 2 will be described with a processing flow example. First, the normalization process of the human flow measurement result in S12 of FIG. 2 will be described. FIG. 3 is a flowchart illustrating an example of a normalization process of human flow measurement results. When the processing starts (S100), the human flow processing unit 121 of the human flow measurement / prediction device 100 receives the current flow measurement result from the flow measurement device 700 and first converts the data into hourly flow data (S101). Next, the human flow processing unit 121 converts the data into human flow measurement data for each management target line section (S102), calculates the number of passengers before the train arrives at each station, and the number of passengers after departure (S103). The data is stored as data converted (normalized) in the measurement / external factor result table 125, and the process is terminated (S104, S105).

13A and 13B show a configuration example of the human flow measurement / external factor result table 125 that stores normalized human flow measurement values and external factors in association with each other. The human flow measurement / external factor result table 125 stores the daily flow measurement result and the external factor result of the day. As shown in FIG. 13A, the human flow measurement result includes the date, start time, end time, The following items are recorded: line area, up / down classification, station, number of passengers (before arrival), number of passengers (after departure), and change amount. In other words, the human flow measurement / external factor result table 125 stores daily human flow measurement results and external factor results for a predetermined period retroactive from the current day.

The start time and end time indicate the measurement time zone of the corresponding human flow measurement result in 24-hour notation. For example, the name of the route such as “AA line” is stored in the line section. In the up / down section, the operation direction in the line section is stored for the train subject to human flow measurement. In the station, the name of the station subject to human flow measurement is stored. The number of passengers (before arrival) and the number of passengers (after departure) store the number of passengers at the time of departure when arriving at the station. In the amount of change, a value obtained by subtracting the value of the number of passengers (before departure) from the number of passengers (after departure) calculated in the passenger number variation calculation process (FIG. 5) described later is stored. The number of people getting on and off at each station, as described with respect to the human flow measuring device 700, records the state of getting on and off of the trains coming and going to each home by means of measuring devices such as cameras and human sensors installed at each station, The number of passengers can be extracted and determined. As for the amount of change, for example, when “+500” is recorded, it indicates that the number of passengers exceeds the number of people getting off in the corresponding time zone at the corresponding station. By the above normalization processing of the human flow measurement result, the number of people getting on and off each station based on the current flow measurement result on the day can be grasped for each time zone.

Next, the external information normalization process will be described. FIG. 4 is a flowchart illustrating an example of normalization processing of external information. When the external information processing unit 122 of the human flow measurement / prediction device 100 starts processing in S200, it receives external information from the external information raw data table 602 of the external information receiving device 600, and first converts the external information into date and hourly external information. Data conversion is performed (S201). Here, the external information includes raw data such as weather along the railway, temperature, wind speed, precipitation, operation information on other railway lines, other companies' lines, bus routes, etc., event information along the railway, and calendar information. Raw data means that the data stored in the information server of the railroad company that is the recipient of external information is handled unprocessed, and the data format depends on the system configuration of the recipient, etc. Can take various forms. Next, the external information processing unit 122 extracts external information as an external factor that influences the flow of people and performs data conversion (normalization) (S202). It is determined whether the normalized external factor information is information of the current day (S203). If it is determined that the information is current day information (S203: current day), it is registered in the human flow measurement / external factor result table 125 and processed. Is finished (S204, S208).

When it is determined that the normalized external factor information is prediction information in the future (after the next day) and there is a change compared to the external factor prediction value of the date and time stored in the past (S205: Yes), The external information processing unit 122 stores the normalized data in the external factor prediction table 126 (S206). Next, the external information processing unit 122 transmits the change information to the human flow calculation unit 124 if the external factor predicted value of the date and time stored in the past is changed, and ends the processing (S207, S208). When it is determined in S205 that there is no change in the external factor prediction, the external information processing unit 122 ends the process as it is (S208). Through the above processing, factors related to fluctuations in human flow can be extracted from external information acquired from an information server of a railway company and used in a format suitable for processing by the human flow measurement / prediction apparatus 100.

FIG. 13B shows a configuration example of the human flow measurement / external factor result table 125. In the example of FIG. 13B, items such as a day of the week, a holiday (for example, record the symbol if it falls on a holiday), weather, temperature, wind speed, precipitation amount, operation information, and event are associated with the corresponding date. It is extracted from the information and recorded. Here, as for operation information, items such as a target company, line section, and event (construction, etc.) are stored when the operation of other line sections or other companies is different from the normal operation. As for the event, when the event is held along the line, items such as the presence / absence of the event, the venue, and the number of customers are stored.

FIG. 14 shows a configuration example of the external factor prediction table 126 that stores future external factor prediction values. In the example of FIG. 14, future external factor information that affects the human flow, normalized by the external information processing unit 122, is stored from the next day to one week later. Once the external factor is changed after the registration, the external information processing unit 122 changes the corresponding data (S205: Yes, S206 in FIG. 4). The items recorded in the external factor prediction table 126 are the same as those in the human flow measurement / external factor result table 125 in FIGS.

Next, the passenger number change calculation process (S13) in the overall process flow example of FIG. 2 will be described. FIG. 5 is a flowchart illustrating an example of a passenger number variation calculation process in each line section and each station that is the management target of the system 1. When the change amount calculation unit 123 of the human flow measurement / prediction apparatus 100 starts the process in S300, it acquires information on the current day from the human flow measurement result stored in the human flow measurement / external factor result table 125 in FIG. 13A (S301), By subtracting the value of the number of passengers before arrival from the value of the subsequent number of passengers, the amount of change in the number of passengers in each line section and each station is calculated (S302). Next, the change amount calculation unit 123 updates the human flow measurement / external factor result table 125 with the calculated change amount, and ends the processing (S303, S304). Through the above processing, the number of passengers in each line section and each station is updated on a daily basis based on the result of the measurement of people flow.

Next, the human flow predicted value calculation process (S14) in the overall process flow example of FIG. 2 will be described. FIG. 6 is a flowchart illustrating an example of a human flow predicted value calculation process. When the flow calculation unit 124 of the flow measurement / prediction apparatus 100 starts processing in S400, it receives the change information transmitted from the external information processing unit 122 (S401), and from the external factor prediction table 126 based on the change information. The external factor prediction item of the date and time when the change is made is acquired (S402). The start timing of this processing flow can be determined every predetermined time, and the processing may be started upon reception of change information. Next, the human flow calculation unit 124 acquires all of the human flow measurement / external factor results of the same external factor condition as the acquired external factor prediction of the acquired date / time from the human flow measurement / external factor result table 125 (S403). That is, in the external factor prediction table 126, all records that record the day of the week, holidays, weather, temperature, wind speed, precipitation, operation information, or events that match the change information are acquired. Next, the human flow calculation unit 124 extracts only the human flow measurement / external factor result of the target line section for creating a diagram from the acquired human flow measurement / external factor result (S404). Further, the human flow calculation unit 124 designates one station included in the corresponding line section, extracts the human flow measurement / external factor result of the station (S405), and extracts the current flow measurement / external factor result from the extracted human flow measurement / external factor result. The average value of the change in the number of passengers recorded for the station is calculated (S406). This is because when a certain external factor is changed, the results of changes corresponding to the relevant external factor are averaged to obtain a more reliable prediction result.

The flow calculation unit 124 determines whether or not the average amount of change for all stations has been calculated in S407 (S407), and repeats the processing of S405 and S406 until it is determined that all stations have been calculated (S407: Yes). Calculate the average change in the number of passengers at each station from the first station to the last station in the ward. Next, when the calculation is completed at all stations, the person flow calculation unit 124 calculates the number of passengers between the stations from the first station to the last station by adding the calculated average values in order from the first station (S408). The inter-station passenger count calculation result is stored in the human flow prediction database 300 (S409). The human flow calculation unit 124 transmits the external factor change information to the diagram creating apparatus 200 and ends the process (S410, S411). FIG. 15 is a configuration example of the human flow prediction database 300 that stores the results of the human flow prediction calculated from the records of the future external factor prediction table 126 and the past human flow measurement / external factor result table 125. In the example of FIG. 15, for each date, the number of passengers by station is recorded for each station from the first station to the last station of the corresponding line section in association with the time zone, line section, and up / down section. For example, in the example of FIG. 15, “In the time zone from 8:00 to 9:00 on October 2, 2013, 1300 people get on the section from the first station to the second station (next station) on the AA line. "Yes" is recorded. Since this human flow prediction database 300 is also shared by the diagram creation apparatus 200, accurate and quick information transmission in the system 1 is possible.

Through the above-described processing by the human flow calculation unit 124, it is possible to predict a future human flow from past human flow measurement values and future external factor predictions. Thereby, the transportation demand required to determine the number of trains operated can be calculated. Since the accuracy of the expected value increases as the accumulation of statistical values increases, the average value (expected value) of the amount of change in the number of passengers is gradually increased by accumulating daily flow measurement / external factor result table 125 records. The calculation accuracy of is expected to improve. In addition, since the accuracy of external factor prediction improves as it approaches the day, it is expected that the accuracy of the human flow prediction calculated based on it will also improve as it approaches the day.

Next, processing executed by the diagram creation device 200 subsequent to the processing by the human flow measurement / prediction device 100 will be described. First, the train number calculation process executed by the train number calculation unit 221 of the diagram creation apparatus 200 will be described. FIG. 7 is a flowchart illustrating an example of a train number calculation process. In the number-of-trains calculation process, the number of trains that can correspond to the transportation demand is calculated based on the results of the prediction of the flow of people stored in the prediction database 300 of the flow of people. When the train number calculation unit 221 of the diagram creation apparatus 200 starts the process in S500, the train number calculation unit 221 receives the change information transmitted from the human flow calculation unit 124 of the human flow measurement / prediction apparatus 100 (S501), and receives the change information from the human flow prediction database 300. Human flow prediction data for a certain date and time is acquired (S502). As shown in FIG. 15, since it is possible to obtain the number of passengers between stations from the human flow prediction data, the train number calculation unit 221 determines the number of trains between stations according to demand from the number of passengers between stations. The number is calculated (S503).

Next, the train number calculation unit 221 calculates the number of trains traveling in the entire line area from the calculated number of trains between stations (S504). Next, the train number calculation unit 221 determines whether the calculated number of trains between the stations and the number of trains in the entire line area are appropriate. The number of trains is calculated (S505). Next, the train number calculation unit 221 outputs the calculated result to an output device such as a display of the input / output device 400 (S506). In addition, the train number calculation unit 221 transmits change information regarding the number of trains to the diagram creation calculation unit 222 and ends the process (S507, S508). Through the above processing, information related to the number of trains calculated according to changes in external factors is presented to the person in charge implementing the train plan. As the minimum configuration of the present invention, the processing up to the presentation of the number of trains between stations calculated in S503 in FIG. 7 is executed, and the subsequent matching with the specific train setting conditions is performed in another configuration. It is also possible.

Hereinafter, the main processing steps in the train number calculation process of FIG. 7 will be described sequentially. First, the train number calculation processing for each station (S503 in FIG. 7) will be described. FIG. 8 is a flowchart illustrating a calculation process example (S503) of the number of trains by station. When the processing starts in S600, the train number calculation unit 221 first uses the number of passengers between stations acquired from the human flow prediction database 300 to determine the number of trains between the line segment and the stations from the number of passengers vs. train number table 223. Obtain (S601), and calculate the appropriate number of inter-station trains for the number of passengers based on the prediction of human flow (S602).

FIG. 16 shows a configuration example of the number of passengers vs. number of trains table 223. The number of passengers vs. number of trains table 223 is a table in which an appropriate number of trains for the number of passengers between stations in a specific line section is set in advance based on the boarding capacity, and is associated with the line section and section (between stations). Each item of passenger number lower limit value, passenger number upper limit value, and number is recorded. Referring to the example of FIG. 16, in the section AB of the line section AA, it is shown that the appropriate number of trains is 9 when the number of passengers is estimated to be 1000 to 1200. The number of trains according to demand can be determined from the number of passengers vs. number of trains table 223. Next, the train number calculation unit 221 registers the calculated number of trains between stations in the train number prediction table 224 and ends the process (S603, S604).

FIG. 17 is a configuration example of the train number prediction table 223. The number-of-trains prediction table 223 is a table for storing the number of future trains according to the demand prediction. Corresponding to the corresponding date, day of the week, start time, end time, line section, up / down classification, number of trains , Basic number, and difference items are recorded. Describing items peculiar to the table 223, the number of trains to be run calculated in S602 of FIG. 8 is stored in the number of trains between each station from the start station to the end station of the corresponding line section. The basic number stores the basic number of trains that travel on the entire line section at the time of the day and time acquired in S707 of the line-differentiated train number calculation process described later. Similarly, the difference stores the difference between the number of trains traveling in the entire line section and the basic number calculated in S708. Note that the processing of S601 to S603 in FIG. 8 is performed for each station in the corresponding line section, and appropriate calculation of the number of trains and registration in the train number prediction table 223 are performed for all stations in the line section. .

Next, a process for calculating the number of trains for distinguishing lines will be described. FIG. 9 is a flowchart illustrating a calculation processing example (S504) of the number of line-differentiated trains illustrated in FIG. When the train number calculation unit 221 starts processing in S700, first, the train number prediction value for each station in the relevant line section is obtained from the train number prediction table 223 (S701), and the obtained train number for each station in the relevant line section is obtained. In step S702, the minimum number of trains is calculated. Next, the train number calculation unit 221 obtains the allowable range of the number of trains that can run in the entire line section and between the stations from the train number allowable range table 225 (S703), and calculates the number of trains for each station calculated in advance. It is confirmed whether the minimum value is within the allowable range of the number of trains in the entire line section (S704). If it is determined that the minimum value of the number of trains between stations is within the allowable range (S704: Yes), the train number calculation unit 221 sets the minimum value as the total number of traveling lines (S705). If it is determined in S704 that the minimum value of the number of trains between stations is not within the allowable range (S704: No), the train number calculation unit 221 sets the lower limit value when the minimum value falls below the lower limit value of the allowable range. When the minimum value exceeds the upper limit value of the allowable range, the upper limit value is set as the number of traveling lines for the entire line section (S706).

FIG. 18 shows a configuration example of the train number allowable range table 225. The train number allowable range table 225 is set in advance before the operation of the system 1, and stores the lower limit value and the upper limit value of the number of trains that can run per hour between each line section and each station. For the ward, the total number lower limit value, the total number upper limit value, and the train number upper limit value and the lower limit value between each station from the starting station to the end station of the corresponding line ward are recorded. The overall number lower limit value and the overall number upper limit value store the lower limit value and the upper limit value of the number of trains that can travel the entire line section. The lower limit value and the upper limit value of the number of trains between the stations store the lower limit value and the upper limit value of the number of trains that can travel between the stations. From this table, it is possible to determine whether the number of trains between stations and the number of trains in the entire line area are appropriate.

Next, the train number calculation unit 221 obtains the basic number of the day of the week and the date / time from the basic number table 226 (S707), calculates the difference between the basic number and the total number of traveling lines (S708), and the number of trains The prediction table 223 is updated, and the process ends (S709, S710). FIG. 19 shows a configuration example of the basic number table 226. The basic number table 226 stores the basic number of trains traveling in the relevant line section for each day of the week and each time zone, and is set based on the basic demand forecast of each line section before the operation of the system 1 is started. The In the basic number table 226, items of day of the week, start time, end time, line section, up / down division, and basic number are recorded in association with each other. With this table, it is possible to confirm the number of basic trains in the specific line section in the time zone and the day of the week.

Next, the optimal number of trains calculation process will be described. FIG. 10 is a flowchart showing an example of the optimum train number calculation process (S505) shown in FIG. When the train number calculation unit 221 starts the process in S800, the train number calculation unit 221 first acquires the number of trains for each station in the train line registered in the train number prediction table 223 (S801). The allowable range of the number of trains that can be traveled between the stations is acquired (S802), and the number of trains for each station recorded in the train number prediction table 223 and between the stations recorded in the train number tolerance table 225 The allowable number of trains is compared (S803).

When it is determined that the number of trains between stations is lower than the lower limit value of the allowable range between the stations, the train number calculation unit 221 sets the lower limit value as the optimum value of the number of stations, and ends the process. (S804, S809). When it is determined that the number of trains between stations is within the allowable range of the number of trains between the stations, the train number calculation unit 221 uses the number of trains between stations acquired from the train number prediction table 223 as the optimum number of trains between the stations. The value is set as a value and the process is terminated (S805, S809). When it is determined that the number of trains between stations exceeds the upper limit value of the number of trains between the stations, the train number calculation unit 221 sets the upper limit value as the optimum value of the number of trains between the stations (S806). The difference between the number of trains between stations acquired from the train number prediction table 223 (the number of trains calculated from demand based on human flow prediction) and the upper limit value is set as an ideal value (S807).

Next, the train number calculation unit 221 refers to the alternative route table 227 and checks whether there is an alternative route candidate for the corresponding section. If there is a registration, the candidate is acquired and the processing is terminated (S808, S809). It should be noted that the processing of S803 to S808 is performed for each station in the target line section, thereby setting the optimum number of trains between all stations in the line section. FIG. 20 shows a configuration example of the alternative route table 227. The alternative route table 227 stores substitutable route data relating to each station for the management target line section of the system 1 and is set in advance before the operation of the system 1 is started. The alternative route table 227 stores the items of line sections, between stations, and alternative companies / routes in association with each other. With this table, if the number of passengers more than the number of trains that can run between certain stations is expected (if the required number of trains based on human flow prediction exceeds the upper limit of the allowable number of trains), you can request another transfer You can check if there is a railway company or route.

The output data obtained by the processing of the diagram creation support system 1 according to this embodiment described above will be described. FIG. 11 is an example of an output screen obtained by the train number calculation process of the diagram creation device 200. This output screen can be displayed when the train number calculation processing by the human flow measurement / prediction device 100 and the diagram creation device 200 is completed in accordance with the change of the external information. As shown in FIG. 11, the date, day of the week, line section, time zone, up / down section, the total number of trains set for the line section, and the number of stations between stations are displayed on the output screen. The

For the number of stations, the optimum number of trains, the ideal value, whether there is an excess of the upper limit of the allowable range between stations, and alternative route candidates are displayed for each corresponding station. The display item data relating to the number of trains is stored in the memory 220 of the diagram creating apparatus 200 in a suitable output format, which is calculated up to the time when the optimum train number calculation process (S505 in FIG. 7) is completed. It can be configured to perform display output or the like. In addition, if the display item is provided with an input means such as a pull-down menu so that the person in charge of diagram creation can specify data to be viewed, the usability as the system 1 can be further improved. For example, if the date, day of the week, line section, time zone, and up / down classification can be specified on the screen, the set number of trains in the desired line section, time zone, etc. can be called and confirmed.

This output screen enables the person in charge of diagram creation to check the number of trains according to demand for each line section. In addition, since the optimum number of trains is displayed for each station, it is possible to finely adjust the number of trains for each station. Thereby, the schedule for making the number of trains according to demand run at an appropriate time can be planned. In addition, if it is not possible to drive the number that matches the demand forecast between any of the stations, you can display the alternative route candidates of your company or other companies, so if necessary, you can set the number of traveling in your other lines Congestion can be alleviated by adding additional trains to other companies that have alternative routes. As a result, it is possible to form an appropriate timetable corresponding to future demand fluctuations and to improve convenience for passengers.

FIG. 12 shows a flow example of a train plan, vehicle operation plan, and crew member operation plan process to which the diagram creation support system 1 of the present embodiment is applied. When the diagram creation calculation unit 222 of the diagram creation device 200 starts the process in S900, the schedule creation calculation unit 222 receives the change information transmitted from the train number calculation unit 221 (S901). Are acquired from the train plan table 228, the vehicle operation plan table 229, and the crew member operation plan table 230 (S902). The person in charge of diamond creation confirms the necessary number of trains with reference to the output screen illustrated in FIG. 11, and creates or changes a train plan (S903). At this time, if necessary, a change request is made to the person in charge of the diagram creation in the other line section or a diamond change request is made to another company. Next, the person in charge of creating a diagram formulates a vehicle operation plan (S904) and a crew operation plan for the train (S905).

After the schedule creation or change is completed, the person in charge of schedule creation registers the change schedule in the train plan table 228, the vehicle operation plan table 229, and the crew member operation plan table 230, and ends the processing (S906, S907). Thus, by applying the diagram creation support system 1 of the present embodiment, it becomes possible to create and change a future diagram flexibly according to demand. Thereby, for example, it becomes possible to flexibly create a future diagram corresponding to a transportation demand that changes due to, for example, weather or an event. In addition, since a railway company can run a train in accordance with demand, resources such as electric power and vehicles can be used efficiently, which can contribute to stabilization of management. In addition, schedule changes can be planned in advance based on future demand forecasts, so crew officers and vehicle base managers can prepare in advance operations changes that accompany schedule changes, reducing the burden of schedule changes It becomes possible to make it.

In addition, this invention is not limited to the above-mentioned Example, Various modifications are included. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Further, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Further, it is possible to add, delete, and replace other configurations for a part of the configuration of each embodiment.

1 Diamond creation support system 100 Human flow measurement / prediction device 110 Processor 120 Memory 121 Human flow processing unit 122 External information processing unit 123 Change calculation unit 124 Human flow calculation unit 125 Human flow measurement / external factor result table 126 External factor prediction table 200 Diamond creation device 210 Processor 220 Memory 221 Train number calculation unit 222 Diagram creation calculation unit 223 Number of passengers vs. train number table 224 Train number prediction table 225 Train number allowable range table 226 Basic number table 227 Alternative route table 228 Train plan table 229 Vehicle operation plan table 230 Crew member operation plan table 300 Human flow prediction database 400 Input / output device 500 Related device 600 External information receiving device 601 External information receiving unit 602 External information raw data table 700 Human flow Measuring apparatus

Claims

A train diagram creation support system for supporting a plan of a train diagram corresponding to a demand fluctuation prediction,
Calculate the number of people getting on and off per unit time at each station from the results of people flow collected for each station belonging to the line to be managed, and correlate with external information that is information about external factors that cause demand fluctuations -Stored as external cause result information
Storing the external information related to external factors that are expected to occur in the future as external factor prediction information;
When the external information of the external factor scheduled in the future is detected, the external factor prediction information is updated with the changed external information, and the external information that matches the changed external information is included. A flow prediction unit that obtains the flow measurement / external factor result information, calculates the number of passengers between each station in the line area where the external information change occurs from the flow measurement / external cause result information, and stores it as flow prediction information; ,
Based on the change of the external information received from the human flow prediction unit, obtain the human flow prediction information corresponding to the change occurrence date and time, between each station of the line section where the external information change included in the human flow prediction information occurs A train number calculation unit that calculates the number of trains to be operated between stations based on the number of passengers
Train schedule creation support system equipped with.
The train diagram creation support system according to claim 1,
The human flow prediction unit acquires all of the human flow measurement / external factor result information including the external information that matches the changed external information, and a line on which the external information change is generated from the human flow measurement / external factor result information. Train diagram creation support system that calculates the average number of passengers between each station in the ward.
The train diagram creation support system according to claim 1,
The train number calculation unit refers to information on the number of passengers vs. the number of trains set for normal demand between stations in the line area to be managed, and the external information change included in the human flow prediction information occurs A train diagram creation support system that obtains the number of trains corresponding to the number of passengers between stations in a line district from the information on the number of passengers versus number of trains.
The train diagram creation support system according to claim 1,
The train number calculation unit refers to the entire number allowable range information that is the range of the allowable number of trains for the entire line area to be managed, and the line number of the line area where the external information change included in the human flow prediction information occurs When it is determined that the minimum value of the number of trains to be operated between the stations calculated based on the number of passengers between the stations is within the overall number allowable range, the minimum value is set as the number of trains in the line, A train diagram creation support system that sets an upper limit value or a lower limit value of the permissible range as the number of trains in the line section when it is determined that the minimum value is outside the permissible total number.
The train diagram creation support system according to claim 1,
The train number calculation unit refers to the inter-station train number allowable range information that is the range of the allowable number of trains for each station in the line area to be managed, and the external information change included in the human flow prediction information occurs If it is determined that the number of trains to be operated between each station calculated based on the number of passengers between each station in the line district to be within the allowable number of trains between the stations, the number of trains to the number of trains between the corresponding stations Set and the number of trains to be operated between stations calculated based on the number of passengers between stations in the line section where the external information change occurs included in the human flow prediction information is less than the lower limit value of the allowable number of trains between stations Each station calculated based on the number of passengers between each station in the line section where the external information change included in the human flow prediction information occurs, the lower limit is set to the number of trains between the stations Trains to drive between When it is determined that the number exceeds the upper limit of the allowable number of trains between stations, the upper limit is set to the number of trains between the corresponding stations, and the difference between the number of trains and the upper limit is stored as an ideal value. Train schedule creation support system.
The train diagram creation support system according to claim 1,
Stores alternative route information for each station in the line area being managed,
The number of trains calculating section is based on the number of trains to be operated between the stations calculated based on the number of passengers between the stations of the line section where the external information change occurs included in the human flow prediction information. If it is determined that the upper limit value is exceeded, a train diagram creation support system that searches for the presence or absence of the alternative route information between the stations.
The train diagram creation support system according to claim 5,
An output unit that outputs the processing result of the train number calculation unit;
The train number calculation unit includes all items or some items of the date, day of the week, time zone, line section, operation direction corresponding to the calculated number of trains, the number of trains for the entire line section, and A train diagram creation support system for outputting the number of trains between stations from the output unit.
The train diagram creation support system according to claim 7,
The train number calculation unit, for each station, the calculated number of trains, the ideal value when the number of trains between stations exceeds the allowable range, whether the number of trains between stations exceeds the upper limit allowable range, and the alternative route information A train diagram creation support system that outputs all or some of the items from the output unit.
A train diagram creation support method for supporting a train schedule plan corresponding to demand fluctuation prediction,
A computer having a processor and memory
Calculate the number of people getting on and off per unit time at each station from the results of people flow collected for each station belonging to the line to be managed, and correlate with external information that is information about external factors that cause demand fluctuations -Stored as external cause result information
Storing the external information related to external factors that are expected to occur in the future as external factor prediction information;
When the external information of the external factor scheduled in the future is detected, the external factor prediction information is updated with the changed external information, and the external information that matches the changed external information is included. Obtain the human flow measurement / external factor result information, calculate the number of passengers between each station of the line section where the external information change occurs from the human flow measurement / external factor result information, and store it as human flow prediction information,
Based on the change of the external information, the person flow prediction information corresponding to the change occurrence date and time is acquired, and each station based on the number of passengers between the stations of the line section where the external information change included in the person flow prediction information occurs Calculate the number of trains to be
Train schedule creation support method.