JP2021123271A - Proposal system and proposal method - Google Patents

Abstract

To propose a passenger guidance plan and an operation plan that satisfy constraints determined in advance by a transportation business entity.SOLUTION: A repetition determination unit determines whether or not a pattern in which a first index satisfies a predetermined constraint condition exists, outputs the pattern satisfying the predetermined constraint condition when the pattern in which the first index satisfies the predetermined constraint condition exists, generates the pattern in which at least one of passenger guidance information and operation information is updated when the pattern in which the first index satisfies the predetermined constraint condition does not exist, and repeatedly executes calculation of a passenger route until it is determined that the pattern in which the first index satisfies the predetermined constraint condition exists.SELECTED DRAWING: Figure 1

Description

The present invention relates to a proposed system and a proposed method.

In recent years, railroad transportation obstacles have frequently occurred due to aging transportation infrastructure and personal injury due to congestion. Since the retention of passengers in the station yard may lead to the occurrence of accidents, alleviating the congestion in the station yard is one of the problems to be solved.

As a solution, passenger guidance can be considered, which encourages actions such as detours and stays by delivering electric bulletin boards at stations and sending e-mails to individuals. In addition, it is also effective to reduce congestion by increasing the number of flights and changing the operation information for detour lines of transportation obstruction routes and routes with congestion.

Patent Document 1 accurately predicts passenger behavior when the timetable is disturbed, and creates an appropriate operation reorganization plan that minimizes passenger dissatisfaction based on the prediction result.

Japanese Unexamined Patent Publication No. 2010-018221

In Patent Document 1, a provisional operation reorganization plan is generated based on a planned schedule, and a passenger behavior simulation is performed. Based on the simulation results, the passengers' dissatisfaction points will be corrected, and a new provisional operation reorganization plan will be created repeatedly. Of the repeatedly created provisional operation reorganization plans, the provisional operation reorganization plan with the highest evaluation is output as the operation reorganization plan.

However, Patent Document 1 does not consider passenger behavior when passenger guidance is performed at the same time, and cannot be said to be effective in alleviating congestion. Moreover, even if the congestion can be alleviated, it cannot be taken into consideration that the profit and loss is too large. Patent Document 1 does not consider proposing passenger guidance measures and operation plans that satisfy predetermined restrictions by transportation companies.

An object of the present invention is to propose a passenger guidance measure and an operation plan that satisfy a predetermined constraint by a transportation business entity.

The proposal system of one aspect of the present invention has a prediction unit, a calculation unit, and a repeat determination unit, and is a proposal system that proposes passenger guidance information and operation information. The prediction unit includes destination information and destination information. A passenger route predicted to be adopted by a passenger is calculated based on a pattern that is a combination of the passenger guidance information and the operation information, and the calculation unit calculates a first index based on the passenger route and the pattern. It is calculated and managed for each of the patterns, and the repetition determination unit determines whether or not the pattern in which the first index satisfies a predetermined constraint condition exists, and as a result of the determination, the first index is determined. When the pattern satisfying the predetermined constraint condition exists, the pattern satisfying the predetermined constraint condition is output, and as a result of the determination, the first index satisfies the predetermined constraint condition. When the pattern does not exist, the pattern is generated by updating at least one of the passenger guidance information and the operation information, and it is determined that the pattern in which the first index satisfies the predetermined constraint condition exists. It is characterized in that the prediction unit repeatedly executes the calculation of the passenger route until the passenger route is calculated.

The proposal method of one aspect of the present invention is a proposal method that includes a prediction step, a calculation step, and a repeat determination step, and proposes passenger guidance information and operation information. The prediction step includes destination information and the above. A passenger route predicted to be adopted by a passenger is calculated based on a pattern that is a combination of passenger guidance information and the operation information, and the calculation step calculates a first index based on the passenger route and the pattern. Then, the pattern is managed for each pattern, and the repeat determination step determines whether or not the pattern in which the first index satisfies a predetermined constraint condition exists, and as a result of the determination, the first index is the said. When the pattern satisfying the predetermined constraint condition exists, the pattern satisfying the predetermined constraint condition is output.
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition does not exist, the pattern in which at least one of the passenger guidance information and the operation information is updated is generated, and the pattern is generated. It is characterized in that the prediction step repeatedly executes the calculation of the passenger route until it is determined that the pattern satisfying the predetermined constraint condition exists in the first index.

According to one aspect of the present invention, the transportation entity can propose passenger guidance measures and operation plans that satisfy predetermined restrictions.

It is a basic block diagram of the whole system of the proposal system of an embodiment. It is a figure explaining the flow of the proposal system of an embodiment. It is a figure explaining the record which stores the basic information about a route, a station, and a route. It is a figure explaining the record which stores the passenger guidance information such as an action condition and an operation condition, and the condition necessary for changing the operation information. It is a figure explaining the record which stores the priority of the input index, the congestion degree target, the amount amount upper limit, the number of flights that can be increased, and the destination information. It is a figure explaining the record which stores the information such as guidance guidance for each passenger, exclusion route ID, expected value, necessary cost and the like. It is a figure explaining the record structure of the diagram which is the operation information of a train. It is a figure explaining the record which manages the created guidance guide, the diagram, and the combination (pattern). It is a figure explaining the record which stores the information of the route used by a passenger. It is an equation showing the data structure of the model for calculating the route selection probability after passenger guidance for each passenger. It is a figure which shows the processing procedure which predicts a passenger's route from a pattern and a destination information. It is a figure which shows the processing procedure which calculates the 1st index and the 2nd index from a pattern, a passenger's route, and master data. It is a figure which shows the processing procedure which updates a pattern. It is the figure which showed the example of the input screen and the screen which can confirm the output to the system. It is the figure which showed the example of the screen which can confirm the operation plan plan, passenger guidance plan, and congestion rate as output.

Hereinafter, the proposed system of the embodiment will be described in detail with reference to the drawings. The proposed system of the embodiment relates to a system that realizes congestion mitigation by proposing a combination of passenger guidance and operation plan change that avoids various problems (for example, congestion) that occur at an abnormal time.

The overall configuration of the proposed system of the embodiment will be described with reference to FIG.
The proposed system 1 is a general computer. In the embodiment, it is described as one computer physically, but it can also be configured as a computer system composed of a plurality of computers configured logically or physically, and operates in separate threads on the same computer. It may operate on a virtual computer built on a plurality of physical computer resources.

The proposed system 1 includes a central control device 11, an input device 12 such as a keyboard and a mouse, an output device 13 such as a display, a communication device 14, a main storage device 15, and an auxiliary storage device 16. These are connected to each other by a bus. The prediction unit 21, the calculation unit 22, and the repetition determination unit 23 in the main storage device 15 are programs. After that, when the main body is described as "○○ part", the central control device 11 reads each program from the auxiliary storage device 16 and loads it into the main storage device 15, and then performs the function of each program (details will be described later). It shall be realized. These programs may be automatically executed according to a predetermined time interval (for example, every other day, every week, every month, etc.), or may be executed at a timing instructed by the system operator. .. Details of these programs will be described later.

The auxiliary storage device 16 stores the master data 31, the condition data 32, the input data 33, the guidance information 34, the diagram 35, the pattern table 36, the passenger route 37, and the model data 38. The proposed system 1 is equipped with a keyboard, mouse, etc., and is connected to an input interface that receives input from the planner, a display device, a printer, etc., and an output interface that outputs the program execution result in a format that the planner can see. have.

The proposed system 1 can communicate with the external system 2 and the external server 3 via the network 4. Here, the external system 2 is, for example, an operation schedule planning system, and the passenger route 37 output by the proposal system may be transmitted and input to the operation schedule planning system. In addition, the result calculated by the operation schedule planning system may be used as a diagram 35 in the proposal system.

The external server 3 is, for example, a server that aggregates and manages the number of passengers passing through the ticket gates read by the automatic ticket gate, receives historical data by the demand forecasting device 1 via the network, and accumulates it as input data 31. use. The proposed system receives the input data 31 at regular intervals of 5 minutes, 10 minutes, 15 minutes, etc. and is automatically executed, or is executed at the timing when the system operator inputs the input data 31.

The proposal system 1 may be owned by the railway company as a part of the business system, or may be owned by a service company different from the railway company and distribute the congestion prediction result to the railway company. It may be.

The operation of the proposed system of the embodiment will be described with reference to FIG.
First, the destination information and the pattern (passenger guidance information and operation information) group are received (step S101).

Next, it is determined whether the first index and the second index have been calculated for all the patterns (step S102). As a result of the determination, when the first index and the second index are calculated for all patterns, the constraint is received (step S105). As a result of the determination, if the first index and the second index are not calculated for all the patterns, the passenger route is predicted from the destination information and the pattern (step S103).

Next, the first index and the second index are calculated from the passenger route and pattern (step S104). Next, it is determined whether or not there is a pattern in which the first index satisfies the constraint (step S106). As a result of the determination, if there is a pattern in which the first index satisfies the constraint, the pattern in which the first index satisfies the constraint and the second index are output (step S107).

As a result of the determination, if there is no pattern in which the first index satisfies the constraint, passenger guidance information is generated from the passenger route and undelivered information (step S109). Next, operation information is generated from the undelivered information (step S110). Next, a pattern in which either or both of the passenger guidance information and the operation information are updated is generated in all combinations (step S111). Then, the calculation of the passenger route is repeatedly executed until it is determined that there is a pattern in which the first index satisfies the constraint.

In this way, the route predicted to be taken by the passenger from the pattern that is a combination of the destination information, the passenger guidance information, and the operation information is calculated by performing a human flow simulation (steps S101 to S103).

The first index and the second index are calculated from the output route and pattern, and are managed for each pattern (step S104). If the first index satisfies the constraint condition, the pattern and the second index are output and the processing is terminated (processing steps S105 to S108).

If the first index does not meet the constraint conditions, the passenger guidance information and the operation information are changed, one or more of them generate an updated pattern, and the route is calculated again (from step S109). Step S111).

As a method of changing the passenger guidance information, for example, a method of calculating an expected value of an action for each passenger and outputting the result having the highest expected value as passenger guidance information can be considered. If there is a passenger guidance information changing method other than the above method, it may be used. Further, as a method of changing the above operation information, for example, a method of outputting an increased number of flights to a route that does not satisfy the restrictions can be considered. If there is an operation information changing method other than the above method, it may be used.

FIG. 3 is a diagram showing a data structure of master data 31 stored in the auxiliary storage device 16. Here, the station master 100, the route master 101, and the route master 102 will be described as typical examples.

The station master 100 includes information such as a station ID, a station name, an owning company, and a location. In addition, latitude / longitude information and equipment information in the station yard (such as the installation status of surveillance cameras) may be included.

The route master 101 includes information such as a route ID, a route name, and an operating company. In addition, information on the jurisdiction may be included. The route master 102 stores information such as a route ID, a boarding station ID, and a disembarking station ID for identifying a route from a boarding station to a disembarking station in association with each other.

In addition, the route master 102 also includes a route ID for the number of transfers from the boarding station to the disembarking station, a transfer boarding station ID, and a transfer disembarking station ID. Finally, the boarding route from the boarding station to the disembarking station. Information such as the number, required time, and charge is stored in association with each other. In addition, the selection probability is stored in association with the route ID, which stores the result of calculating which route is likely to be used when there are multiple routes from the boarding station to the disembarking station. .. This may be obtained by the shortest time distance or by the cheapest route.

The master data 31 needs to be updated due to the addition of new stations and lines and the abolition of stations. The renewal work will be carried out by the system operator when the new station / new line actually opens. In addition, if you want to forecast demand in anticipation of a new station development plan scheduled for several years, it is necessary to prepare fictitious master data with the addition of a new station. In this case, the system operator or the user of the proposed system 1 (transportation company, etc.) carries out the fictitious master data creation work. As described above, in the proposal system 1, it is necessary to manage a plurality of master data. Transportation companies will specify and use master data according to the purpose of analysis.

FIG. 4 is a diagram showing a data structure of condition data 32 stored in the auxiliary storage device 16. Here, the action condition 200, the passenger behavior tendency 201, the operation condition 202, and the index master 203 will be described as typical examples.

The action condition 200 includes information such as action information, staying time, action ID, station ID, and time zone. In addition, information on the jurisdiction may be included. The action condition 200 is data that lists possible actions for the station ID and the time zone. The action condition 200 may be input by the user in advance, or may be created from the premise information that the action condition such as "use a detour" cannot be created when there is only one line for the station ID. .. The action ID is created for each action information, station ID, and time zone, and it is desirable not to add the action ID to the action condition 200 if the action cannot be taken depending on the station or time zone.

Passenger behavior tendency 201 includes information such as passenger ID, behavior ID, expected value, and cost utility value. The passenger behavior tendency is data showing the behavior that can be taken at the time of abnormality for each passenger ID. Appropriate initial values may be input for the expected value and cost utility value, and the values may be updated each time data at the time of abnormality is acquired. The operating condition 202 includes information such as a route ID and a flight increase cost per line. In addition, information on the jurisdiction may be included. The operating condition 202 manages the cost for each additional flight for the route. This may be entered by the transportation entity in advance, or may be statistically calculated from the past operation history and cost.

The index master 203 includes information such as an index ID and an evaluation index. Other information such as route information may be included. The index master is data that manages what the input index ID indicates. Other indicators such as working hours and power consumption of workers may be added. The action condition 201, the passenger behavior tendency 201, and the operation condition 202 need to be updated due to the addition of new stations and routes, the abolition of stations, the opening and closing times of facilities, and the like. The renewal work will be carried out by the system operator when the new station / new line actually opens.

FIG. 5 is a diagram showing a data structure of input data 33 stored in the auxiliary storage device 16.
The input data 33 holds the data input by the user. At this time, system input may be used instead of user input. Here, as typical examples, the index priority 300, the congestion degree target 301, the amount upper limit 302, the number of flights that can be increased 303, and the destination information 304 will be described.

The index priority 300 includes a priority, an index ID, and the like. The index priority 301 is data indicating the order that the user wants to achieve as a constraint and the index. When 1 is stored in the priority, the first index is stored, and when 2 is stored in the priority, the second index is stored. The second index is shown. The index ID is associated with the index master 202 in a form corresponding to the index master 202. Other priorities may be added as 3 and 4, and may be added as a third index and a fourth index.

The congestion degree target 301 includes an index ID, a route ID, a target value, and the like. The index ID is
It is linked in a form corresponding to the index master 202. The route ID may be changed to information such as a station ID. Other station ID information may be added. The congestion degree target indicates the target value of the congestion degree for a route or the like, and the target value may be the ratio of the number of people per area or the number of people. Further, the target value may be appropriately determined by user input, or the statistical value may be externally input from the past data.

The amount upper limit 302 includes information such as an index ID and a cost. In the amount upper limit 302, the cost that the transportation company can pay to eliminate the congestion is input. For the cost, you may enter Japanese Yen as the amount, or you may enter your own points owned by the transportation company. Further, the cost may be determined by the input of the user, or the statistical value may be input from the external system 2 from the past data.

The number of possible flights 303 includes, for example, an index ID, a route ID, a time zone, and a possible number of flights. In the number of flights that can be increased 303, for example, the number of flights that can be increased for each route and time zone is input. The index ID is associated with the index master 202 in a form corresponding to the index master 202. For the number of flights increased, a value uniquely determined manually may be input, or a statistical value of the number of flights increased in the past may be input from the external system 2.

The destination information 304 stores, for example, a passenger ID, an entry station ID, an entry station ID, an entry time, and an entry time. The passenger ID is an identifier for each passenger and may be associated with an IC card usage history or the like. The entrance station ID and the exit station ID are identifiers for each station, and are defined by the station master 100 of the master data 31. The destination information 304 may be input in advance by the passenger, or may be a statistical value of an entrance station, an exit station, an entrance time, and an exit time used by the passenger in the past.

FIG. 6 is a diagram showing a data structure of guidance information 34 stored in the auxiliary storage device 16.
Pre-update 400 means passenger guidance information before being updated by the repeat determination unit 23. After the update 401 means the passenger guidance information after being updated by the repeat determination unit 23. Since the type of data stored in the pre-update 400 and the post-update 401 is the same, the pre-update 400 will be described as a representative.

The 400 before the change includes information such as a passenger ID, an action ID, an exclusion route ID, and an expected value. Before the change 400, the action ID associated with the passenger ID is implemented as the passenger guidance, and the expected value of whether or not to follow the guidance is stored. At this time, the passenger ID is associated with the passenger ID of the destination information 304, and the action ID is associated with the action ID of the action condition 200. The expected value may be calculated using the behavioral condition 200 and the passenger behavioral tendency 201.

FIG. 7 is a diagram showing a data structure of the diagram 35 stored in the auxiliary storage device 16.
The pre-update 500 means the operation information before being updated by the repeat determination unit 23. The updated 501 means the operation information after being updated by the repeat determination unit 23. Since the type of data stored in the pre-update 500 and the post-update 501 is the same, the pre-update 500 will be described as a representative.

The pre-update 500 includes information such as a train number, a line ID, a station 1 ID, a station 2 ID, a time 1, a time 2, a capacity indicating an allowable value of a occupant for a train, and the number of occupants, which are train identifiers. It is desirable to enter the planning timetable as the initial value in the diagram.

FIG. 8 is a diagram showing a data structure of the pattern table 36 stored in the auxiliary storage device 16.
The pattern table 36 stores information such as pattern ID, passenger guidance, operation plan, index 1, index 2, congestion degree, amount of money, number of increased flights, and non-delivery information. The pattern ID is an ID for a pattern of passenger guidance information and operation information. In passenger guidance, information for determining whether the guidance information 34 is 400 before update or 401 after update is stored. Similarly, in the operation plan, information for determining whether the operation information 35 is 500 before update or 501 after update is stored.

The index 1, index 2, congestion degree, induction cost, and number of flights increased are updated each time the calculation unit 22 in FIG. 12 or the repetition determination unit 23 in FIG. 13 is executed. The calculation result of the first index is stored in the index 1. Similarly, the index 2 stores the calculation result of the second index. For example, the degree of congestion calculated by the calculation unit 22 is stored in the degree of congestion. As the guidance cost, for example, when the passenger guidance information update process (processing step S406) of the repeat determination unit 23 is executed, the amount of money required for guidance is stored. The number of increased flights stores, for example, the increased number of routes and the number of increased flights when the operation information update process (processing step S407) of the repeat determination unit 23 is executed. The line ID and station ID extracted in the processing step S406 are stored in the undelivered information.

FIG. 9 is a diagram showing a data structure of a passenger route 37 stored in the auxiliary storage device 16.
The passenger route 37 includes information such as a pattern ID, a passenger ID, a departure time, an arrival time, and a route ID. The passenger route 37 stores the route predicted to be taken by the passenger calculated by the prediction unit 23. The pattern ID is associated with the pattern table 36, and the route ID is associated with the route master 102.

FIG. 10 is a diagram showing a data structure of model data 38 stored in the auxiliary storage device 16.
The model data 38 includes information such as an action ID, an expression, a target route, and time addition. The model data 38 shows an expression of the route selection probability that changes for each action ID, and is stored for each action ID. The target route means a route for executing the action of the action ID, and for example, the exclusion route means the exclusion route stored in the guidance information 34. In addition, all routes mean all routes that passengers can take. Model data will need to be updated due to the addition of new stations and routes, the abolition of stations, and the opening and closing times of facilities. The renewal work will be carried out by the system operator when the new station / new line actually opens.

FIG. 11 is a diagram illustrating a prediction unit 21 which is a processing procedure for generating the passenger route 37 shown in FIG. 9 and storing it in the auxiliary storage device.
First, the prediction unit 21 of the main storage device 15 reads the pattern table 38 stored in the auxiliary storage device 16 (processing step S201).

One pattern is extracted from the pattern table 38, and the corresponding guidance information 34, operation information 35, master data 31, destination information 304, and model data 38 are read (processing step S202).

The formula of the action ID for each passenger specified in the guidance information is extracted. Using the extracted formula, the selection probability of whether or not to follow the induction (hereinafter referred to as induction establishment) is calculated. For example, the probability Y may be calculated by substituting the selection probability in the route master 102 in X, the expected value of the guidance information 34 in a, and the amount of money in b as variables of the equation. Further, b may substitute an expression for calculating the expected value for the amount of money, or may determine a certain expected value for each amount of money.

All possible routes that passengers can take from the destination information 304 are extracted from the route master 102, their probabilities and guidance probabilities are normalized, and the route selection probability for each passenger is calculated (processing step S203). The route selection probability and the diagram 305 are input to the human flow simulation, and the route predicted to be selected by the passenger is output as the passenger route 37 (processing step S204).

If the time addition of the extracted model data is not 0, it is added to the departure time for the described time at the time of the human flow simulation, and the simulation is performed. The human flow simulation may be called from the external system 2 or may be incorporated inside the system.

FIG. 12 is a diagram illustrating a calculation unit 22 which is a processing procedure for updating the first index and the second index of the pattern table 36 shown in FIG. 8 and storing them in the auxiliary storage device.
First, the calculation unit 22 of the main storage device 15 reads the condition data 32, the pattern table 38, and the passenger route 37 stored in the auxiliary storage device 16 (processing step S301).

The calculation unit 22 calculates the first index and the second index from the condition data 32, the pattern table 38, and the passenger route 37 (processing step S302), and stores the result in the pattern table 38 (processing step S303). ..

In the calculation method of the first index and the second index, for example, in the case of the number of passengers, the total number of people for a certain period of time with respect to the route ID or station ID may be stored as an index. In addition, when the index is the degree of congestion, the number of passengers may be the number of passengers per area as compared with the above method of calculating the number of passengers. If it is an amount, the total of the number of coupons issued and the cost of increasing flights for each route * the number of increasing flights may be output as an index.

FIG. 13 outputs the second constraint and pattern when the first index in the pattern table 36 shown in FIG. 8 satisfies the constraint, and guide information 34 when the first index does not satisfy the constraint. It is a figure explaining the repetition determination unit 23 which is the processing procedure which updates the diagram 35 and the pattern table 36 and stores them in the auxiliary storage device 16.

First, the repeat determination unit 23 of the main storage device 15 reads the input data 33 and the pattern table 36 stored in the auxiliary storage device 16 (processing step S401). The data of the index ID having the same index ID as the data having the priority 300 of the index of the read input data 33 of 33 is extracted from the congestion degree target 301, the upper limit of the amount of money 302, the number of flights that can be increased 303, and the like (hereinafter referred to as priority data).

The priority data is compared with the first index in the pattern table 36, and if the first index satisfies the result of the priority data, the pattern satisfying the constraint is extracted (processing step S411), and the guidance corresponding to the pattern proposal 36 is obtained. The information 34, the diagram 35, and the second index are output (processing step S412), and the processing is terminated. The fact that the first index satisfies the constraint may mean that, for example, the degree of congestion predicted in the pattern table 36 is equal to or less than the degree of congestion target 301.

The priority data is compared with the first index of the pattern table 36, and if the first index does not satisfy the result of the priority data, the input data 31 is received (processing step S403), and the induction cost of the pattern table 36 is input. When the upper limit of the amount of data 302 is exceeded and the number of flights increased in the pattern table 36 exceeds the number of flights that can be increased 303, the guidance information 34, the diagram 35, and the second index corresponding to the pattern table 36 are output (processing step S412). ) End the process. If the first index does not satisfy the constraint, for example, the degree of congestion predicted in the pattern table 36 may be equal to or higher than the degree of congestion target 301. In the process step S404, the patterns of the guidance information 34 and the diagram 35 stored in the pattern table 36 are always output even if the first index is not satisfied.

If the induction cost of pattern table 36 does not exceed the upper limit of the amount of input data 302, or the number of flights increased in pattern table 36 does not exceed the number of possible flights 303, the first index for which the constraint could not be achieved is shown in pattern table 36. Store (step S405). In the pattern table 36, the data closest to the first index satisfying the constraint is selected, and the passenger route 37 of the corresponding route is extracted (processing step S406). For example, when the first index is the degree of congestion, the pattern with the lowest degree of congestion is extracted from the pattern table 36.

The data stored in the updated 401 of the guidance information 34 is overwritten on the pre-update 400, and the post-update is initialized. The action condition 200 of the station corresponding to the extracted passenger route 37 is extracted, the passenger behavior tendency is extracted from the passenger route 37 and the action condition 200, and the guidance information 34 is stored in 401 after the update (processing step S407). .. For example, if the congestion degree of the route ID 2000 does not satisfy the constraint, the passenger ID 8000001 is extracted from the passenger route 37. In addition, the action condition 200 of the station ID to be used is extracted by referring to the route master 102. The passenger ID corresponding to the extracted passenger route 37 and the action ID corresponding to the extracted action condition 200 are extracted from the passenger behavior tendency 201, and the record having the highest expected value is set to 401 after the guidance information 34 is updated. Store. Further, the processing step S407 may output a passenger guidance plan from an external system 2, for example, a passenger guidance system.

Next, the data stored in the updated 501 of the diagram 35 is overwritten on the 500 before the update, and the updated 501 is initialized. The target route ID is extracted from the extracted passenger route 37, a diagram in which the number of increased flights is increased by an arbitrary number is generated, and the diagram 35 is updated and stored in 501 (processing step 408). At this time, as a process other than increasing the number of flights, the operation interval may be changed or the number of flights may be reduced. Further, the processing step 408 may be output from, for example, an operation schedule planning system of the external system 2.

Next, a pattern of 400 before update and 401 after update of the guidance information 34, 500 before update and 501 after update of the diagram 35 is generated, the amount of money and the number of flights increased are stored, and a combination of patterns including after update, for example, A pattern such as 400 before the update of the guidance information 34 and 501 after the update of the diagram 35 is output (processing step 409).

The amount may be updated each time the processing step 407 is executed, and the amount may be increased or decreased by a fixed amount from the pattern table before the processing step 409 is executed, or a model may be created in which the amount is increased or decreased depending on the number of repetitions. .. Further, the number of increased flights is updated every time the processing step 408 is executed. The pattern shows a combination of guidance information and a diagram, and one or more is the updated information. Therefore, the patterns generated at one time are "400 before update-501 after update", "401 after update-500 before update", and "401 after update-501 after update".

FIG. 14 is a diagram showing an example of a screen and an output screen in which the user of the proposal system 1 (congestion mitigation planner / commander) inputs data and restrictions necessary for user input when considering the congestion mitigation measure. be.

There are five input items in the upper part of the screen I100, (1) is the number of flights that can be increased 303, (2) is the upper limit of the amount of money 302, (3) is the congestion degree target 301, (4) is the destination information 304, (5). ) Is an input frame corresponding to the index priority 300. Further, in (6), it is possible to input 400 before updating the guidance information 34. In (7), it is possible to input 500 before updating the diagram 35. Items (1), (2), (3), (4), and (5) must be entered. Items (1), (2), (3), (4), and (5) may be manually input or input from the external system 2.

Items (6) and (7) are optional inputs. If the item (6) is not entered, empty data may be entered as the initial value. If the item (7) is not entered, the plan diagram may be entered as the initial value. In the example of the upper part of the screen I100, for example, (3) the target of the congestion degree target value may not be a line but a station unit. Further, regarding the number of flights that can be increased, the method of designating the departure station and the arrival station (for example, "SA station-SB station") or the method of designating "all stations-all stations" may be used instead of the line unit.

Further, there may be a plurality of combinations of departure stations and arrival stations. In that case, a combination list of departure stations and arrival stations may be prepared in a format such as a text file, and there may be an interface for uploading the list. In addition to stations and routes, it is also possible to specify by municipality or to define a station combination list freely by the user. The lower part of the screen I100 is an example of a screen on which the output result can be confirmed.

In the lower part of the screen I100, the pattern in which the first index satisfies the constraint is extracted from the pattern table 36, and the values of the corresponding passenger guidance information 34, the diagram 35, and the second index stored in the pattern table 36 are output. .. All the display results may be listed, or specific conditions, patterns with the best second index, etc. may be listed. The best second indicator may be, for example, the lowest predicted cost.

The first index, the second index, and the like of the corresponding pattern may be displayed in the lower part of the screen I100. Clicking the pattern button transitions to screen I101. At this time, the screen I101 may be displayed on the screen I100 without making a transition.

FIG. 15 is a diagram showing an example of a screen for displaying the output plan of the proposed system 1. The created diagram 35, passenger guidance information 34, the first index and the second index shown in the pattern table 36 are displayed on the screen I101, and the user can confirm the changed points.

For example, the upper part of the screen displays the watermark 35 generated as operation information. In the example, the diagram is displayed for each route, but the schedules for all the target routes may be displayed at once or may be displayed in an overlapping manner. The lower part of the screen displays the generated passenger guidance information. The guidance delivered for each passenger ID may be displayed, or the number of people may be output for each guidance content.

The user can distribute the new operation plan and the passenger guidance plan by clicking the distribution button after confirming the details on the screen I101. Further, the back button may be arranged to return to the screen I100 without distribution. At this time, the output pattern may be clicked to transition to the screen I101, or a new input may be accepted on the screen I100.

As described above, in the present embodiment, the proposal of the congestion mitigation plan is realized by performing each of the above-mentioned processes and calculating the pattern of the passenger guidance information and the operation information that satisfy the restrictions.

The present invention is not limited to the above-described examples, and includes various modifications. For example, the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to those having all the described configurations. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Further, it is possible to add / delete / replace a part of the configuration of each embodiment with another configuration.

In addition, each of the above configurations may be configured in part or in whole in hardware, or may be configured to be realized by executing a program in a processor. In addition, control lines and information lines are shown as necessary for explanation, and not all control lines and information lines are necessarily shown in the product. In practice, it can be considered that almost all configurations are interconnected.

1 Proposed system 2 External system 3 External server 4 Network 11 Central control device 12 Input device 13 Output device 14 Communication device 15 Main storage device 16 Auxiliary storage device 21 Prediction unit 22 Calculation unit 23 Repeat judgment unit 31 Master data 32 Condition data 33 Input Data 34 Guidance information 35 Diagram 36 Pattern table 37 Passenger route 38 Model data

Claims (15)

It is a proposal system that has a prediction unit, a calculation unit, and a repeat judgment unit, and proposes passenger guidance information and operation information.
The prediction unit
Based on the destination information and the pattern that is a combination of the passenger guidance information and the operation information, the passenger route predicted to be adopted by the passenger is calculated.
The calculation unit
Based on the passenger route and the pattern, a first index is calculated and managed for each pattern.
The repeat determination unit
It is determined whether or not the pattern in which the first index satisfies a predetermined constraint condition exists.
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition exists, the pattern satisfying the predetermined constraint condition is output.
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition does not exist, the pattern in which at least one of the passenger guidance information and the operation information is updated is generated.
A proposed system characterized in that the prediction unit repeatedly executes the calculation of the passenger route until it is determined that the pattern in which the first index satisfies the predetermined constraint condition exists. The calculation unit
Based on the passenger route and the pattern, a second index different from the first index is calculated together with the first index and managed for each pattern.
The repeat determination unit
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition exists, the pattern satisfying the predetermined constraint condition and the second index are output. The proposal system according to claim 1. The prediction unit
The passenger guidance information associated with the pattern, the operation information associated with the pattern, master data including a route master storing the route selection probability of whether or not to follow the guidance, and the route selection probability calculation for calculating the route selection probability. Read the model and the destination information,
The route master and the passenger guidance information are input to the route selection probability calculation model to update the route selection probability.
The proposed system according to claim 1, wherein the passenger route is calculated by inputting the operation information, the route selection probability, and the destination information into a human flow simulation. The prediction unit
As the destination information, the information of the entrance station and the information of the exit station are used.
As the passenger guidance information, behavioral information including the use, stay or cancellation of detours is used.
The proposed system according to claim 1, wherein a diagram is used as the operation information. The calculation unit
As the first index, the expected degree of congestion is calculated.
The proposed system according to claim 2, wherein the estimated cost is calculated as the second index. The repeat determination unit
When the pattern in which the first index satisfies the predetermined constraint condition does not exist, the passenger guidance information is generated from the passenger route and the undelivered information.
The operation information is generated from the undelivered information,
The proposal system according to claim 1, wherein at least one of the passenger guidance information and the operation information is updated. The repeat determination unit
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition does not exist,
The expected value of the behavior for each passenger is calculated as the passenger behavior tendency, and the passenger guidance information is generated based on the highest expected value.
The proposed system according to claim 1, wherein the first index generates the operation information with increased flights for a route that does not satisfy the predetermined constraint condition. The repeat determination unit
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition does not exist,
When the number of flights increased for a route whose first index does not satisfy the predetermined constraint condition reaches the upper limit, the pattern is output to end the repeated execution of the calculation of the passenger route. The proposal system according to claim 1. The repeat determination unit
A claim, characterized in that, when the degree of congestion as the first index is equal to or less than a predetermined target value, it is determined that the pattern in which the first index satisfies the predetermined constraint condition exists. The proposal system according to 5. It also has an output device for outputting information,
The output device is
The proposed system according to claim 1, wherein the pattern, which is a combination of the passenger guidance information and the operation information, and the first index are displayed. It is a proposal method that has a prediction step, a calculation step, and a repeat judgment step, and proposes passenger guidance information and operation information.
The prediction step is
Based on the destination information and the pattern that is a combination of the passenger guidance information and the operation information, the passenger route predicted to be adopted by the passenger is calculated.
The calculation step is
Based on the passenger route and the pattern, a first index is calculated and managed for each pattern.
The repeat determination step
It is determined whether or not the pattern in which the first index satisfies a predetermined constraint condition exists.
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition exists, the pattern satisfying the predetermined constraint condition is output.
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition does not exist, the pattern in which at least one of the passenger guidance information and the operation information is updated is generated.
A proposed method, characterized in that the prediction step repeatedly executes the calculation of the passenger route until it is determined that the pattern that the first index satisfies the predetermined constraint condition exists. The calculation step is
Based on the passenger route and the pattern, a second index different from the first index is calculated together with the first index and managed for each pattern.
The repeat determination step
As a result of the determination, when the pattern in which the first index satisfies the predetermined constraint condition exists, the pattern satisfying the predetermined constraint condition and the second index are output. The proposed method according to claim 11. The prediction step is
The passenger guidance information associated with the pattern, the operation information associated with the pattern, master data including a route master storing the route selection probability of whether or not to follow the guidance, and the route selection probability calculation for calculating the route selection probability. Read the model and the destination information,
The route master and the passenger guidance information are input to the route selection probability calculation model to update the route selection probability.
The proposed method according to claim 11, wherein the passenger route is calculated by inputting the operation information, the route selection probability, and the destination information into a human flow simulation. The repeat determination step
When the pattern in which the first index satisfies the predetermined constraint condition does not exist, the passenger guidance information is generated from the passenger route and the undelivered information.
The operation information is generated from the undelivered information,
The proposed method according to claim 11, wherein at least one of the passenger guidance information and the operation information is updated. It also has an output step to output information,
The output step
The proposed method according to claim 11, wherein the pattern, which is a combination of the passenger guidance information and the operation information, and the first index are displayed.

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