WO2017056528A1 - Congestion predicting system and congestion predicting method - Google Patents

Congestion predicting system and congestion predicting method Download PDF

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Publication number
WO2017056528A1
WO2017056528A1 PCT/JP2016/059093 JP2016059093W WO2017056528A1 WO 2017056528 A1 WO2017056528 A1 WO 2017056528A1 JP 2016059093 W JP2016059093 W JP 2016059093W WO 2017056528 A1 WO2017056528 A1 WO 2017056528A1
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countermeasure
congestion
time
candidate
index value
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PCT/JP2016/059093
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French (fr)
Japanese (ja)
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鋭 寧
加藤 学
正康 藤原
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株式会社日立製作所
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Priority to GB1804500.5A priority Critical patent/GB2556828B/en
Priority to JP2017542764A priority patent/JP6445175B2/en
Publication of WO2017056528A1 publication Critical patent/WO2017056528A1/en

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    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/123Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
    • G08G1/127Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams to a central station ; Indicators in a central station
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0631Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40Business processes related to the transportation industry
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • the present invention relates to a technique for managing the congestion state of a predetermined space.
  • partial spaces There are various spaces (hereinafter sometimes referred to as “partial spaces”) where passengers come in and out of the railway station and move through the train station.
  • partial spaces In such a space of a railway station, in addition to the occurrence of daily congestion such as commuting hours, congestion often occurs due to the influence of railway transportation failures and events. Due to the increase in congestion, there is a concern that the time required for passengers to get on and off the train will increase, resulting in a delay in train operation, and a crowd accident such as a passenger falling from the platform.
  • Patent Document 1 uses a camera to measure the number of people entering and leaving the guarded area, and predicting the number or density of passengers in the guarded area from the number of entering and leaving, Congestion status in the case of traffic alerts and a function to notify danger when a danger warning value is set in advance for congestion (population) in the security target area and the predicted value of congestion exceeds the danger warning value
  • An event security monitoring device having a function of predicting the above is disclosed.
  • An object of the present invention is to provide a technique that makes it possible to determine an appropriate countermeasure and an appropriate implementation time for congestion requiring countermeasures in managing the congestion status of a predetermined space.
  • a congestion prediction system includes a countermeasure candidate database storing information on countermeasure candidates that can be implemented for congestion in a predetermined space, and a transition of congestion index values at a future time for the predetermined space.
  • a simulation unit to calculate, a countermeasure-necessary congestion detection unit for detecting a countermeasure-necessary congestion which is a congestion requiring countermeasures and specified by space and time, and the countermeasure-necessary congestion is detected
  • An output unit that outputs an evaluation result of the countermeasure candidate including whether or not a congestion index value calculated by a simulation of a condition that applies a countermeasure candidate applicable to the space exceeds the threshold value.
  • the countermeasure candidates applicable to the congestion and the evaluation result are output together with the space and time in which the countermeasure countermeasure congestion occurs, so that it is easy to determine an appropriate countermeasure against the countermeasure congestion. Become.
  • FIG. 1 It is a figure which shows the structural example of the congestion prediction system by this embodiment. It is a figure which shows an example of the predicted number information 210 recorded on the predicted number information database. It is a figure showing an example of the spatial information 220 recorded on the spatial information database. It is a figure which shows an example of the partial space information 230 recorded on the spatial information database. It is the figure which showed the range of each partial space contained in the partial space information 230 of FIG. 4 on the plane. It is a figure showing an example of the congestion prediction result 240 calculated by simulation. It is a figure showing an example of the countermeasure candidate 250 recorded on the countermeasure candidate database 113. FIG.
  • FIG. 10 is a diagram for explaining a processing example of a countermeasure start time calculation unit 140.
  • FIG. 5 is a flowchart illustrating a processing example of a countermeasure start time calculation unit 140.
  • 10 is a flowchart illustrating a processing example of a countermeasure priority evaluation unit 160.
  • 10 is a flowchart illustrating a processing example of a countermeasure plan evaluation unit 170.
  • 6 is a flowchart illustrating a processing example of an output unit 180. 6 is a diagram illustrating an example of screen display by the output unit 180. FIG. It is a flowchart which shows the example of a process of the whole system.
  • FIG. 1 is a diagram illustrating a configuration example of a congestion prediction system according to the present embodiment.
  • the congestion prediction system is a computer system that monitors passenger congestion in the space of a railway station and supports the implementation of countermeasures by a supervisor as necessary.
  • the congestion prediction system includes one computer or a plurality of computers connected to each other.
  • the congestion prediction system includes a predicted number-of-persons information database 111, a spatial information database 112, a countermeasure candidate database 113, a simulation unit 120, a countermeasure required congestion detection unit 130, a countermeasure start time calculation unit 140, a condition change unit 150, and a countermeasure priority evaluation unit 160.
  • the countermeasure plan evaluation unit 170 and the output unit 180 are provided.
  • the congestion prediction system includes predicted number information 210 shown in FIG. 2, spatial information 220 shown in FIG. 3, partial space information 230 shown in FIG. 4, congestion prediction result 240 shown in FIG. 6, countermeasure candidate 250 shown in FIG.
  • the processing is executed using the countermeasure countermeasure congestion information 270 shown in FIG. 9, the countermeasure proposal 280 shown in FIG. 9, the countermeasure priority evaluation result 290 shown in FIG. 10, and the countermeasure proposal evaluation result 300 shown in FIG. 11 as data.
  • the congestion prediction system has a predicted number information database 111 in which predicted number information 210 is recorded, a spatial information database 112 in which spatial information 220 and partial space information 230 are recorded, and a countermeasure candidate database 113 in which countermeasure candidates 250 are recorded as databases. is doing.
  • the predicted number-of-persons information 210 is data indicating the state of passenger movement in each time zone within the railway station.
  • the simulation unit 120 receives the predicted number of people information 210 and the spatial information 220 as inputs, and in the space represented by the spatial information 220, as shown in the predicted number of people information 210, each partial space in the space when the passenger moves.
  • the congestion situation is predicted, and the prediction result is output as the congestion prediction result 240.
  • the congestion prediction result 240 is a table indicating the degree of congestion (congestion index value) in each partial space at each time.
  • the countermeasure required congestion detection unit 130 receives the congestion prediction result 240 and determines whether or not the congestion index value indicated by the congestion prediction result 240 exceeds a predetermined threshold. When it is detected that the congestion index value exceeds the threshold, the countermeasure required congestion detection unit 130 identifies the countermeasure required congestion that is a congestion requiring countermeasure based on the time and the partial space information when the congestion index value exceeds the threshold. Information 270 is output.
  • the time to identify countermeasure congestion is the predicted congestion time, and the subspace is indicated by the detection subspace name.
  • the countermeasure start time calculation unit 140 receives the countermeasure candidate 250 having the detected partial space name of the countermeasure necessary congestion information 270 as the target partial space name, and executes the countermeasure candidate 250 so that the congestion index value does not exceed the threshold value.
  • the countermeasure start time that is the time to start at the latest is output.
  • the candidate for countermeasure is a candidate for countermeasure to be implemented for countermeasure congestion.
  • the condition changing unit 150 outputs the predicted number information 210 and the spatial information 220 when the countermeasure plan 280 is applied as a countermeasure against the countermeasure congestion.
  • the countermeasure plan 280 includes a countermeasure candidate 250 and a countermeasure start time that is a time at which application of the countermeasure candidate 250 is started. When application of the countermeasure candidate 250 is started at the countermeasure start time, the subsequent movement of the passenger in each partial space changes.
  • the countermeasure priority evaluation unit 160 evaluates the priority of each countermeasure countermeasure congestion and outputs the evaluation result as a countermeasure priority evaluation result 290.
  • countermeasure required congestion is evaluated from the degree of influence of congestion in the partial space, a grace time until a time when a countermeasure candidate should be executed in order to avoid a state requiring countermeasures, and the like.
  • the measure plan evaluation unit 170 uses the congestion prediction result 240 when the measure plan 280 is applied, which is calculated by the simulation unit 120 with the predicted number of people information 210 and the spatial information 220 changed by the condition change unit 150 as inputs.
  • the measure plan 280 is evaluated, and the evaluation result is output as the measure plan evaluation result 300.
  • the output unit 180 receives the countermeasure priority evaluation result 290 and the countermeasure plan evaluation result 300 as input, and the computer terminal possessed by the personnel (for example, a guide) who should implement the countermeasure priority evaluation result 290 and the countermeasure plan evaluation result 300 To display. ⁇ Function>
  • the predicted number information database 111 is a database that records the predicted number information 210, and has functions of recording, searching, and reading.
  • the predicted number information 210 stored in the predicted number information database 111 is a predicted value.
  • the predicted value of the predicted number of people information 210 may be sequentially calculated using, for example, a well-known route simulation, with the record data of the number of people passing through the ticket gates as input, and additionally stored in the predicted number of people information database 111.
  • the spatial information database 112 is a database that records the spatial information 220 and the partial spatial information 230, and has recording, searching, and reading functions.
  • the spatial information 220 and the partial space information 230 are created in advance for each target station for which congestion prediction is performed.
  • the spatial information 220 is map data in which the space of the railway station is divided into a grid pattern and the function of each position is assigned to each grid.
  • the partial space information 230 is information in which a range and attributes are assigned to a partial space defined in a predetermined range included in the entire space.
  • the countermeasure candidate database 113 is a database that records the countermeasure candidates 250 and has recording, searching, and reading functions.
  • the countermeasure candidate 250 is list data of candidate countermeasures applicable to the congestion for each partial space.
  • the countermeasure candidate 250 is created in advance for each target station for which congestion prediction is to be performed.
  • the simulation unit 120 receives the predicted number of people information 210, the spatial information 220, and the partial space information 230 as input, and in the space when the passenger is moved in the space represented by the spatial information 220 according to the predicted number of people information 210.
  • Is predicted using a known pedestrian simulation device and a congestion prediction result 240 that is a time-series transition of the congestion index value of each partial space is output.
  • the congestion index for example, the number of people staying in the space, the crowd density, and the flow line density are used.
  • a known cellular automaton is used as an example of a pedestrian simulation apparatus.
  • the countermeasure-necessary congestion detection unit 130 receives the congestion prediction result 240 output from the simulation unit 120 as an input, and the congestion prediction result 240 for each partial space exceeds the threshold for determining whether a countermeasure is required. If there is data exceeding the threshold value, information on the partial space and time is output as the countermeasure required congestion information 270.
  • the threshold value for example, an index value that indicates that the risk of crowd accident is higher than a predetermined value in the congestion index that is used, or an index value that is input in advance by a monitor is used.
  • the countermeasure start time calculation unit 140 uses the congestion prediction result 240 of the partial space in which the countermeasure required congestion is detected as the first congestion prediction result when the countermeasure required congestion detection unit 130 outputs the countermeasure required congestion information 270.
  • a temporary countermeasure plan 280 is created with the candidate as an arbitrary time within a range from the current time to the time when countermeasure congestion is detected, and is input to the condition changing unit 150.
  • the simulation unit 120 Using the first congestion prediction result and the second congestion prediction result as the second congestion prediction result, the congestion prediction result 240 of the subspace in which the countermeasure required congestion is calculated is used as a second congestion prediction result, and the countermeasure candidates are congested. Since the index value does not exceed the threshold value, the countermeasure start time that is the time at which the congestion condition should be implemented is calculated and output at the latest.
  • the condition changing unit 150 receives the countermeasure plan 280 as an input, changes at least one of the predicted number of people information 210 and the spatial information 220 based on the countermeasure plan 280, and outputs the predicted number of people information 210 and the spatial information 220 with the changes. .
  • countermeasure candidates are applied at the countermeasure start time for countermeasure countermeasure congestion
  • For 220 the space information 220 in which the ticket gate is changed from bidirectional to one-way (out) at the countermeasure start time is output.
  • the countermeasure priority evaluation unit 160 receives the countermeasure required congestion information 270 when the countermeasure required congestion detection unit 130 detects the countermeasure required congestion, and the congestion prediction result of the partial space where the countermeasure required congestion has occurred, The measure priority evaluation value is calculated using the measure candidate, the measure start time, and the priority of the subspace, and the calculated result is output as the measure priority evaluation result 290.
  • the measure plan evaluation unit 170 calculates the evaluation value when the measure candidate is applied, using the congestion prediction result when the measure plan 280 composed of the measure candidate and the measure start time is applied in the simulation unit 120 as an input.
  • the result is output as a measure proposal evaluation result 300.
  • the output unit 180 has a function of outputting the countermeasure priority evaluation result and the countermeasure plan evaluation result and displaying them on the screen.
  • the display is performed, for example, on a digital signage in the station premises for the purpose of providing information to passengers or computers held by station staff who are monitoring staff.
  • the countermeasure priority evaluation results are displayed with priorities based on the countermeasure priority evaluation values.
  • the countermeasure evaluation results are displayed with priorities based on the countermeasure proposal evaluation values of the countermeasure proposal evaluation results. Displaying with priorities means, for example, arranging and displaying in order based on evaluation values, or changing the design such as size, color, and icon to be displayed according to the evaluation values.
  • each part of the congestion prediction system of the present embodiment described above is realized by a computer having an arithmetic device, a control device, a storage device, and an input / output device, and software operating on the computer.
  • the congestion prediction system may be configured by a plurality of components.
  • the components can be connected to each other via a bus or a network and can perform data communication with each other.
  • FIG. 2 is a diagram showing an example of the predicted number of people information 210 recorded in the predicted number of people information database 111.
  • the predicted number of people information 210 is data in which the number of passengers moving between the departure point and the destination is recorded by time.
  • the station entrance and platform (train) are the departure point and destination.
  • the departure place is a home (train)
  • the arrival time of the train is set as the start time
  • the departure time of the train is set as the end time.
  • the number of people who move from the doorway 1 to the starting point and from the time 7:00 to the time 7:10 with the home 1 as the destination is ten.
  • the number of people who move from home 7 as the destination and from home 7 as the destination between time 7:01 and time 7:02 is 30. This means that 30 passengers who arrive at the home 1 at the time 7:01 and get off from the train 1 leaving at the time 7:02 travel with the home 2 as the destination.
  • FIG. 3 is a diagram illustrating an example of the spatial information 220 recorded in the spatial information database 112.
  • Spatial information 220 is data for recording station structure and facility information, and is created in advance based on the station structure.
  • the spatial information 200 is represented using a lattice space obtained by dividing a space into a lattice shape, which is used in a pedestrian simulation using a known cellular automaton.
  • the lattice space is composed of unit lattices such as a passage lattice, a wall lattice, a stair lattice, a ticket gate lattice, an entrance / exit position lattice depending on a partial space to which the lattice space belongs.
  • unit lattices such as a passage lattice, a wall lattice, a stair lattice, a ticket gate lattice, an entrance / exit position lattice depending on a partial space to which the lattice space belongs.
  • For each grid for example, information on whether or not it is possible to pass, speed that can pass, direction that can pass, distance cost required for passing, and whether or not pedestrians can enter and leave the entire space is given.
  • FIG. 3 is an example in which the structure of a station having one ticket gate and two platforms is represented as a space using a unit grid.
  • FIG. 4 is a diagram illustrating an example of the partial space information 230 recorded in the spatial information database 112.
  • the partial space information 230 is data of a partial space that is a unit for detecting the countermeasure required congestion.
  • FIG. 5 is a diagram showing a range of each partial space included in the partial space information 230 of FIG. 4 on a plane.
  • a partial space is an individual space created by separating a space at a point where traffic restriction or direction restriction can be performed or where a branch of a route occurs.
  • ranges A001 to A004 shown in FIG. 5 are partial spaces, and are separated by points A011 to A014 (stairs) and A021 (ticket gates).
  • a range that can be set as a unit for detecting the countermeasure congestion is set, and may be set more finely than the examples in FIGS.
  • the partial space name “home 1” may be divided into a plurality of partial spaces, and the range of the partial space may be set in finer units.
  • partial space information 230 a partial space name, a range, a partial space priority, a connection point, and a connected partial space name are recorded in association with each other.
  • the partial space name is a name of the partial space, and one partial space name corresponds one-to-one with respect to one partial space.
  • the range indicates the range of the subspace, and in the present embodiment, the range is a set of lattices constituting the partial space, and is represented as, for example, an array of lattices constituting the partial space.
  • the ranges described in FIG. 4 correspond to the ranges A001 to A004 shown in FIG.
  • the partial space priority is an evaluation value set in advance for use in determining the priority for implementing a countermeasure when a countermeasure required congestion is detected for a plurality of partial spaces. For example, congestion on the platform is likely to cause dangerous accidents compared to concourses, such as falling to a track. Therefore, higher priority is set for congestion at home than for concourse.
  • connection point is a point where a partial space is connected to another partial space.
  • the home 1 (range A001) is connected to another partial space using the staircase 1 (point A011) and the staircase 2 (point A012) as connection points.
  • the connection point is a set of lattices, and is represented, for example, as an array of lattices representing the connection points.
  • connection subspace name records the subspace name of another subspace to which the subspace is connected via the connection point.
  • home 1 (range A001) is connected to the inside of the concourse ticket gate (range A003) via stairs 1 (point A011) and stairs 2 (point A012).
  • FIG. 6 is a diagram illustrating an example of the congestion prediction result 240 calculated by simulation.
  • the congestion prediction result 240 is data composed of time-series predicted values of the congestion index of each partial space.
  • the congestion index for example, the number of people staying in the partial space, the crowd density, or the flow line density can be used.
  • FIG. 7 is a diagram illustrating an example of the countermeasure candidate 250 recorded in the countermeasure candidate database 113.
  • the countermeasure candidate 250 is data representing countermeasures against congestion that can be implemented for each space such as a station.
  • the target subspace name indicates a subspace to be subjected to countermeasures.
  • the target point is a point corresponding to the connection point of the partial space information 230. By changing the state of the target point, measures against congestion can be implemented.
  • the countermeasure state represents a state that the target point can take.
  • the state that can be taken includes both a state that the machine can take such as the direction of traffic of the ticket gate and a state that occurs when the station staff performs traffic control such as regulation of the direction of passage of stairs.
  • FIG. 8 is a diagram illustrating an example of countermeasure required congestion information 270 that is data output when the countermeasure required congestion detection unit 130 detects countermeasure required congestion.
  • the detection subspace name is a name of the subspace detected when the countermeasure required congestion occurs.
  • the predicted congestion time is a time zone in which the countermeasure required congestion occurs.
  • the maximum congestion is the maximum value of the congestion index in the predicted countermeasure congestion.
  • FIG. 9 shows countermeasure candidate data combining the countermeasure candidate 250 for countermeasure congestion required and the countermeasure start time.
  • FIG. 9 illustrates the case where the partial space where the countermeasure required congestion is detected is the home 1. Since the congestion index value obtained by the simulation under the condition that the countermeasure of the countermeasure candidate 250 is applied does not exceed the threshold, the data includes the countermeasure start time that is the time when the countermeasure candidate should be executed at the latest.
  • FIG. 10 is a diagram showing a countermeasure priority evaluation result 290 that is data obtained by evaluating the priority at which countermeasures should be taken against the countermeasure congestion required and adding the final countermeasure start time and the countermeasure priority evaluation value.
  • the countermeasure priority evaluation result 290 is data obtained by evaluating the priority at which countermeasures should be taken for countermeasure countermeasure congestion, and adding the final countermeasure start time and the countermeasure priority evaluation value.
  • the final countermeasure start time represents the latest countermeasure start time among the countermeasure proposals using the detection subspace name as the target subspace name.
  • the countermeasure priority evaluation value is an evaluation value calculated by the countermeasure priority evaluation unit 160 based on the predicted congestion time, the maximum congestion, and the final countermeasure start time.
  • the maximum congestion is used for evaluation of countermeasure required congestion, but the present invention is not limited to this. Instead of the maximum congestion, another index indicating the degree of congestion such as an average value of the congestion index may be used.
  • FIG. 11 is a diagram illustrating a countermeasure plan evaluation result 300 that is data obtained by adding a congestion mitigation evaluation value and a countermeasure plan evaluation value to the countermeasure plan 280 illustrated in FIG. 9.
  • the congestion alleviation evaluation value is an evaluation value of the congestion mitigation effect when the countermeasure plan 280 is calculated, which is calculated from the difference between the congestion index value calculated by simulation under the condition that the countermeasure plan 280 is applied and the threshold value. is there.
  • the measure plan evaluation value is an evaluation value of the measure plan 280 calculated from the length of the grace time from the current time to the measure start time and the congestion alleviation evaluation value.
  • FIG. 12 is a diagram for explaining a processing example of the countermeasure start time calculation unit 140.
  • FIG. 12 shows the first congestion prediction result indicating the time transition of the congestion index of the partial space where the countermeasure required congestion is detected, and the range from the current time to the time when the countermeasure required congestion is detected as a temporary countermeasure plan.
  • the graph shows a second congestion prediction result indicating a time transition of the congestion index calculated by simulation under a condition that the countermeasure candidate is applied as early as possible, for example, at an arbitrary time.
  • FIG. 13 is a flowchart illustrating a processing example of the countermeasure start time calculation unit 140.
  • a processing example of the countermeasure start time calculation unit 140 will be described with reference to each step of FIG.
  • the congestion prediction result of the partial space in which the countermeasure required congestion is detected among the congestion prediction results in which the countermeasure required congestion is detected is the first.
  • the first congestion prediction result and the countermeasure candidate are input as the congestion prediction result.
  • the countermeasure required congestion focused here is an object for calculating the countermeasure start time of the countermeasure candidate.
  • a temporary countermeasure plan is created by setting an arbitrary time within the range from the current time to the time when countermeasure required congestion is detected as a temporary countermeasure start time and adding the temporary countermeasure start time to the candidate for countermeasure. .
  • S103 By inputting the provisional countermeasure plan to the condition changing unit 150, the simulation unit 120 is caused to calculate the congestion index when the provisional countermeasure plan is applied.
  • the congestion prediction result of the partial space in which the target countermeasure required congestion calculated by the simulation unit 120 is detected is set as the second congestion prediction result.
  • S104 Referring to the first congestion prediction result, the maximum value of the congestion index is calculated for each time range in which the congestion index exceeds the threshold, and the time when the maximum value is taken is set as time t.
  • S105 Smooth the first congestion prediction result. Smoothing can be performed using, for example, a moving average method.
  • S108 A straight line having the slope calculated in S108 and having a congestion index that matches the threshold at time t is calculated.
  • S109 A point where the straight line calculated in S108 and the curve of the first congestion prediction result intersect before time t is calculated, and the time at that point is set as the countermeasure start time.
  • the process of calculating the countermeasure start time can calculate the countermeasure start time with a smaller amount of calculation than the process of repeating the simulation while moving the time and searching for the countermeasure start time delayed as much as possible.
  • S201 Input information about the countermeasure required congestion detected by the countermeasure required congestion detection unit 130, the congestion prediction result including the countermeasure required congestion, and the countermeasure proposal applicable to the partial space where the countermeasure required congestion is detected.
  • the countermeasure countermeasure congestion to which information is input is a target for evaluating the countermeasure priority.
  • the time from the time when the congestion index exceeds the threshold to the time when the congestion index falls below the threshold is set as the predicted congestion time.
  • S202 The subspace priority of the subspace where the countermeasure required congestion is detected is acquired from the spatial information database 112.
  • S203 The difference between the maximum value of the congestion index and the threshold value in the countermeasure required congestion is calculated.
  • the countermeasure plan includes a countermeasure candidate and a countermeasure start time.
  • the length of the predicted congestion time, the subspace priority extracted in S202, the difference between the maximum congestion calculated in S203 and the threshold, and the final countermeasure start time calculated in S206 are set as evaluation target values.
  • the evaluation target value By multiplying the evaluation target value by a predetermined arbitrary weight and adding them together, the countermeasure required congestion countermeasure priority evaluation value is calculated.
  • the difference between the maximum congestion and the threshold value is an example of an index indicating the degree of congestion, and another index indicating the degree of congestion may be used instead.
  • the countermeasure required congestion information 270, the final countermeasure start time, and the countermeasure priority evaluation value are output as the countermeasure priority evaluation result 290.
  • the countermeasure countermeasure congestion countermeasure priority is calculated and displayed as a comprehensive evaluation of countermeasure implementation priority for countermeasure countermeasure congestion.
  • the present invention is not limited to this.
  • the length of the predicted congestion time, the subspace priority extracted in S202, the difference between the maximum congestion and the threshold calculated in S203, and part or all of the final countermeasure start time calculated in S206 are individually monitored. This may be presented to a member to determine which countermeasure congestion is prioritized.
  • S301 The congestion prediction result indicating the time transition of the congestion index calculated by the simulation by the simulation unit 120 under the condition that the countermeasure plan is applied to the countermeasure required congestion is input.
  • S303 Calculate the difference between the maximum value and threshold value of the congestion index value calculated by the simulation of the condition for implementing the countermeasure candidate from any time between the current time and the detection of countermeasure required congestion. Use the relaxation evaluation value.
  • the difference between the maximum value of the congestion index value and the threshold value is an example of an index indicating the degree of improvement in the congestion index value, and another index indicating the degree of congestion improvement may be used instead.
  • the countermeasure proposal evaluation result 300 is output by associating the congestion mitigation evaluation value and the countermeasure proposal evaluation value with the countermeasure proposal as a countermeasure proposal evaluation result.
  • the example which calculates and displays a countermeasure plan evaluation value as comprehensive evaluation about a countermeasure plan was shown here, it is not limited to this.
  • both or one of the countermeasure postponement time and the congestion alleviation evaluation value may be individually presented to a monitor to determine which countermeasure plan to adopt.
  • FIG. 16 is a flowchart illustrating a processing example of the output unit 180.
  • FIG. 17 is a diagram illustrating an example of screen display by the output unit 180.
  • the countermeasure priority evaluation result 290 is displayed on the screen of a computer terminal held by a monitor (for example, station staff) managing the congestion state of the station.
  • the countermeasure priority congestion included in the countermeasure priority evaluation result 290 is prioritized and displayed in descending order of countermeasure priority evaluation values.
  • the detected subspace name, the estimated congestion time, and the countermeasure priority evaluation value are displayed for the countermeasure priority congestion of the countermeasure priority evaluation result 290.
  • the predicted congestion time for each partial space can be represented by a horizontal bar graph
  • the measure priority evaluation value can be represented by the color of the band-like display indicating the estimated congestion time or the shade of the color.
  • the countermeasure priority evaluation result display screen 310 of FIG. 17 lists home 1, home 2, and the inside of the concourse ticket gate as partial spaces where countermeasures need to be congested.
  • the time required for countermeasures in each subspace is indicated by hatching in the horizontal bar graph.
  • the level of countermeasure priority for each countermeasure congestion is expressed by shades of hatching, and the darker color means that the countermeasure priority is higher.
  • the countermeasure priority evaluation result 290 may be displayed in a table format.
  • prioritization can be expressed by sorting based on the measure priority evaluation value.
  • the countermeasure required congestion may be sorted based on the maximum congestion (the maximum value of the congestion index) or the last countermeasure start time. Or you may enable it to change the evaluation value used for a sort by operation of a monitoring person.
  • S403 The monitor looks at the display of the countermeasure priority evaluation result, and selects countermeasure congestion requiring countermeasures. For example, on the countermeasure priority evaluation result display screen 310 shown in FIG. 17, the monitor selects the display 311 displaying the countermeasure required congestion of the home 1.
  • the countermeasure plan evaluation result corresponding to the selected countermeasure required congestion is displayed on the computer terminal held by the supervisor. If a plurality of countermeasure proposals can be applied to the countermeasure required congestion, the countermeasure proposal evaluation results of the plurality of countermeasure proposals may be prioritized and displayed in descending order of the countermeasure proposal evaluation values. As another example, a priority order based on a countermeasure start time or a congestion mitigation evaluation value may be attached. Or you may enable it to change the evaluation value used for prioritization by operation of a monitoring person.
  • display may be performed so that it is possible to distinguish whether or not the maximum congestion of the countermeasure degree evaluation result exceeds a threshold for detecting the countermeasure congestion required.
  • the countermeasure plan evaluation result of countermeasure required congestion may be displayed differently depending on whether or not the maximum congestion exceeds a threshold value. For example, you may distinguish by display color, the presence or absence of an icon, or the kind of icon. Alternatively, only countermeasures whose maximum congestion of countermeasure proposal evaluation results does not exceed the threshold may be displayed.
  • the countermeasure plan evaluation result is displayed as a list of countermeasure plans corresponding to the countermeasure required congestion selected on the countermeasure priority evaluation result display screen 310 as in the countermeasure plan evaluation result display screen 320 shown in FIG. Ranking and displaying based on the proposed evaluation value.
  • the measure plan evaluation result display screen 320 of FIG. 17 as a measure plan for the countermeasure required congestion of 8:50 to 9:20 of the home 1, a measure plan that restricts one-way only in the direction of exiting the stairs 1, There are proposed countermeasures for restricting one-way only in the direction of exiting the stairs 2 and for restricting one-way only in the direction of exiting the ticket gate 1. These countermeasure plans are prioritized according to the countermeasure plan evaluation values and are displayed in that order.
  • S405 The monitor looks at the display of the countermeasure plan evaluation result and selects the countermeasure plan to be implemented. For example, the countermeasure plan evaluation result to be implemented is selected by selecting the highest ranked record 321 from the countermeasure plan evaluation result display screen 320 shown in FIG.
  • the monitoring staff selects personnel (for example, station staff) who are in charge of implementing the selected countermeasure plan. Or you may select the signage which displays a passenger's guidance guidance. For example, the person-in-charge schedule is displayed as in the person-in-charge setting screen 330 shown in FIG. 17, and the person in charge is selected by selecting the time zone 331.
  • Candidates who implement the countermeasure plan are station staff A and station staff B. However, the station staff B is indicated by hatching that other work is being performed at the time when the countermeasure is taken, and it is understood that the station staff B cannot take charge of implementing the countermeasure.
  • S407 The contents of the countermeasure plan and instructions for implementation are notified to the terminal held by the station staff who implements the countermeasure plan.
  • the passenger guidance may be displayed on the selected signage.
  • the content of the countermeasure to be implemented is displayed as in the countermeasure proposal implementation content instruction screen 340 of FIG.
  • the connection point that is the target of the countermeasure plan to be implemented is the stairs 1, and the time for implementing the countermeasure is 8:30 to 9:20. It is displayed that it is a one-way street limited to the exit direction only.
  • the congestion prediction system reads the predicted number information 210 after the current time from the predicted number information database 111, reads the spatial information 220 and the partial space information 230 from the spatial information database 112, and inputs them to the simulation unit 120.
  • the congestion prediction system predicts the congestion state by the simulation unit 120, and outputs a congestion prediction result.
  • the congestion prediction system inputs the congestion prediction result to the countermeasure-required congestion detection unit 130, and determines whether or not congestion requiring countermeasures has occurred.
  • the countermeasure-necessary congestion detection unit 130 outputs countermeasure-necessary congestion information 270, and the process proceeds to S1004. If the occurrence of congestion requiring countermeasures is not detected, the congestion prediction system returns to S1001, and repeats data reading and congestion prediction.
  • the congestion prediction system extracts, from the countermeasure candidate database 113, the countermeasure candidates 250 whose target partial space is the partial space in which the countermeasure required congestion is detected in the countermeasure required congestion information 270.
  • the congestion prediction system calculates the countermeasure start time for each countermeasure candidate 250 extracted in 1005 using the countermeasure start time calculation unit 140.
  • the congestion prediction system creates a countermeasure plan 280 by combining the countermeasure candidates and the congestion start time.
  • the congestion prediction system inputs the countermeasure plan 280 to the condition change unit 150, and creates the predicted number information 210 and the spatial information 220 under the condition that the countermeasure plan 280 is applied to the countermeasure required congestion.
  • the congestion prediction system inputs the predicted number of people information 210 and the spatial information 220 to which the countermeasure plan 280 is applied to the simulation unit 120, predicts the congestion situation when the countermeasure plan is applied, and predicts the prediction result as the congestion.
  • the result 240 is output.
  • the congestion prediction system inputs the congestion prediction result 240 to the countermeasure plan evaluation unit 170, and calculates the countermeasure plan evaluation result 300.
  • the congestion prediction system determines whether or not all countermeasures have been evaluated. If evaluation of all countermeasures has not been completed, the process returns to S1008 to predict other countermeasures. Process the appraisal. On the other hand, when the evaluation of all countermeasures is completed, the congestion prediction system proceeds to S1011.
  • the congestion prediction system inputs a countermeasure required congestion, a congestion prediction result in which the countermeasure required congestion is detected, and a countermeasure plan for the countermeasure required congestion to the countermeasure priority evaluation unit 160, and the final countermeasure start time and countermeasure priority evaluation. The value is calculated and the countermeasure priority evaluation result 290 is output.
  • the congestion prediction system inputs the countermeasure priority evaluation result 290 and the countermeasure plan evaluation result 300 to the output unit 180, and displays them on the screen.
  • the congestion system determines whether or not the current time has reached the end time designated by the monitor or the departure time of the last train. If the current time has not reached those times, the congestion prediction system returns to S1001. If the current time has reached those times, the congestion prediction system completes the process. ⁇ Effect>
  • the simulation unit 120 predicts congestion based on the predicted number of people information that is sequentially added, and determines whether the output congestion prediction result includes congestion that requires countermeasures.
  • the congestion that requires countermeasures is detected, the congestion that requires the detected countermeasures is evaluated according to the congestion occurrence time, the degree of congestion, and the location of occurrence, and ranked according to the evaluation value and provided to the monitor be able to.
  • a countermeasure plan that can be expected to ease congestion can be prioritized and provided to the observer in consideration of the effect of the congestion relief.
  • the countermeasure plan to be implemented can be selected from the plan. As a result, the monitor can easily determine an appropriate congestion countermeasure plan in a timely manner.
  • the actual congestion situation or the predicted future congestion situation may change abruptly depending on the train operation situation.
  • the monitoring staff can take appropriate measures in a timely manner against the congestion. You can judge the idea.
  • the priority order of countermeasures is calculated by calculating the countermeasure start time at which countermeasures should be implemented at the latest to eliminate the countermeasure congestion. To make the judgment easier. Then, it is possible to assist the monitor in determining the priority for taking countermeasures from the congestion that requires a plurality of countermeasures. For example, when alarms are output that indicate congestion in multiple spaces and times, it is easy to determine which countermeasures should be prioritized if there are restrictions on the number of supervisors and countermeasures cannot be implemented for all alarms at the same time become.
  • a countermeasure plan for congestion that can be expected to be reduced to a threshold value that is the criterion for determining congestion that requires countermeasures is created, and the countermeasure proposal is used to reduce the congestion amount and countermeasures. Can be evaluated according to the time at which they should be implemented, ranked according to the evaluation value, and provided to the observer. The observer can easily implement appropriate countermeasures by selecting from the provided countermeasures. It is possible.
  • the congestion prediction system includes a countermeasure candidate database 113, a simulation unit 120, a countermeasure-necessary congestion detection unit 130, and an output unit 180.
  • the countermeasure candidate database 113 stores information of countermeasure candidates that can be implemented for congestion in a predetermined space (partial space).
  • the simulation unit 120 calculates the transition of the congestion index value at a future time for a predetermined space (partial space).
  • the countermeasure-necessary congestion detection unit 130 detects the countermeasure-necessary congestion that is a congestion that requires countermeasures and that is specified by space and time.
  • the output unit 180 outputs the evaluation result of the countermeasure candidate including whether or not the congestion index value calculated by the simulation of the condition applying the countermeasure candidate applicable to the space where the countermeasure required congestion is detected exceeds the threshold value.
  • a countermeasure candidate applicable to the congestion and an evaluation result thereof are output together with a space and time in which the countermeasure congestion is generated, so that an appropriate countermeasure can be determined in a timely manner against the countermeasure congestion. It becomes easy.
  • the measure plan evaluation unit 170 improves the congestion index value calculated by simulation of the condition in which the countermeasure candidate is implemented from any time between the current time and the detection of the required countermeasure congestion.
  • the degree of improvement for example, the difference between the maximum value of the congestion index value and the threshold value is calculated.
  • the output unit 180 outputs a countermeasure candidate evaluation result including the calculated difference.
  • the difference between the maximum value of the congestion index value when the countermeasure candidate is implemented and the threshold value is used for evaluation of the countermeasure candidate. Therefore, when the countermeasure candidate is implemented, the degree of congestion index value from the state that requires countermeasures It can be evaluated whether it can be improved to a state with a margin.
  • the countermeasure required congestion detection unit 130 can detect a plurality of countermeasure required congestions, and the countermeasure priority evaluation unit 160 calculates an evaluation result for each of the plurality of countermeasure required congestions.
  • the output unit 180 outputs a countermeasure required congestion by giving a rank based on the evaluation result of the countermeasure required congestion, and outputs a countermeasure candidate by giving a rank based on the evaluation result of the countermeasure candidate.
  • the countermeasure start time calculation unit 140 should execute the countermeasure candidate at the latest so that the maximum value of the congestion index value calculated by the simulation of the condition in which the countermeasure candidate is implemented for countermeasure required congestion is less than or equal to the threshold value.
  • the countermeasure start time is calculated.
  • the output unit 180 outputs an evaluation result of countermeasure candidates including the countermeasure start time.
  • the countermeasure start time calculation unit 140 sets the first time when the first curve takes the maximum value within the time when the first curve drawn by the congestion index value calculated by the simulation not applying the countermeasure candidate exceeds the threshold.
  • the time at which the first curve takes an extreme value before the first time is set as the second time, and the countermeasure required congestion is detected from the current time between the first time and the second time.
  • the processing load due to the calculation of the countermeasure start time can be reduced.
  • the output unit 180 outputs a plurality of countermeasure congestions by giving an order based on the countermeasure start time of at least one countermeasure candidate applicable to each countermeasure congestion, and can be applied to the same countermeasure congestion A plurality of countermeasure candidates are given a rank based on the countermeasure start time of each countermeasure candidate and output.
  • the output unit 180 ranks and displays the countermeasure required congestion detected by the countermeasure required congestion detection unit 130, and when one of the countermeasure required congestions is selected, a countermeasure candidate corresponding to the countermeasure required congestion is selected. Are displayed on the screen.
  • an operator such as a train station supervisor can follow the hierarchy of the screen display and can easily select the countermeasure congestion required to implement countermeasures and the countermeasures.
  • the output unit 180 displays countermeasure time information including the countermeasure start time of the countermeasure candidate and candidate countermeasure personnel responsible for implementing the countermeasure candidate, and is in charge of implementation.
  • an instruction to execute the candidate countermeasure is transmitted to the terminal of the countermeasure person.
  • the output unit 180 displays the transition of the evaluation index related to the countermeasure required congestion on the screen along the time axis so that the size of the congestion index value can be identified.
  • evaluation indexes related to countermeasure required congestion for example, there are a congestion index value, a countermeasure required congestion rank (priority), and the like.

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Abstract

Provided is a technology for enabling determination of an appropriate countermeasure against congestion requiring a countermeasure and an appropriate time to perform the appropriate countermeasure, in management of the congestion condition in a predetermined space. This congestion predicting system includes: a countermeasure candidate database storing information about countermeasure candidates which can be performed against congestion in a predetermined space; a simulation unit that calculates future change in a congestion index value for the predetermined space; a countermeasure requiring congestion detecting unit that detects, when the congestion index value is greater than a predetermined threshold, countermeasure requiring congestion which requires a countermeasure and which is specified using a space and a time; and an output unit that outputs an evaluation result of the countermeasure candidate, the result including whether a congestion index value calculated through simulation under a condition where a countermeasure candidate applicable to the space in which the countermeasure requiring congestion was detected is applied is greater than the threshold or not.

Description

混雑予測システムおよび混雑予測方法Congestion prediction system and congestion prediction method
 本発明は、所定の空間の混雑の状況を管理する技術に関する。 The present invention relates to a technique for managing the congestion state of a predetermined space.
 鉄道駅にはホームやコンコースなど旅客が出入りしたり、中を移動する様々な空間(以下「部分空間」と呼ぶこともある)がある。そのような鉄道駅の空間では、通勤時間帯などの日常的な混雑の発生に加えて、鉄道の輸送障害やイベントの影響を受けて混雑が増大することがしばしば発生する。混雑の増大によって、旅客が列車に乗降するのに要する時間が増大して列車の運行に遅延が発生したり、ホームから旅客が転落する等の群集事故が発生したりといったことが懸念される。 There are various spaces (hereinafter sometimes referred to as “partial spaces”) where passengers come in and out of the railway station and move through the train station. In such a space of a railway station, in addition to the occurrence of daily congestion such as commuting hours, congestion often occurs due to the influence of railway transportation failures and events. Due to the increase in congestion, there is a concern that the time required for passengers to get on and off the train will increase, resulting in a delay in train operation, and a crowd accident such as a passenger falling from the platform.
 鉄道駅の混雑による列車遅延や群集事故を防止するためには、鉄道駅の空間における旅客の将来の混雑を予測し、列車遅延や群集事故に至る前に適切な対処を行うことが重要である。 In order to prevent train delays and crowd accidents due to congestion at railway stations, it is important to predict the future congestion of passengers in the space of railway stations and take appropriate measures before train delays and crowd accidents. .
 特許文献1では、カメラを使って、警備対象区域への流入人数と警備対象区域からの流出人数とを計測し、流出入人数から警備対象区域に居る旅客の人数あるいは密度を予測する機能と、警備対象区域の混雑(人出)について危険警報値を予め設定し、混雑の予測値が危険警報値を超えた場合に危険を知らせる警報を通知する機能と、通行規制を行った場合の混雑状況を予測する機能とを備えたイベント警備監視装置が開示されている。 Patent Document 1 uses a camera to measure the number of people entering and leaving the guarded area, and predicting the number or density of passengers in the guarded area from the number of entering and leaving, Congestion status in the case of traffic alerts and a function to notify danger when a danger warning value is set in advance for congestion (population) in the security target area and the predicted value of congestion exceeds the danger warning value An event security monitoring device having a function of predicting the above is disclosed.
特開2004-178358号公報JP 2004-178358 A
 しかし、特許文献1に記載されたイベント警備監視装置に、通行規制を行った場合の混雑状況を予測する機能はあるが、その通行規制の良し悪しは評価されない。そのため、監視員は混雑の警報が出力されたとき、どのような対策を実施するのが適切か自分で判断する必要がある。 However, although the event guard monitoring device described in Patent Document 1 has a function of predicting the congestion situation when the traffic regulation is performed, the quality of the traffic regulation is not evaluated. Therefore, it is necessary for the supervisor to determine by himself what measures should be taken when a congestion warning is output.
 本発明の目的は、所定の空間の混雑状況の管理において、対策を要する混雑に対して、適切な対策とその適切な実施時間を判断することを可能にする技術を提供することである。 An object of the present invention is to provide a technique that makes it possible to determine an appropriate countermeasure and an appropriate implementation time for congestion requiring countermeasures in managing the congestion status of a predetermined space.
 本発明の一つの実施態様に従う混雑予測システムは、所定の空間の混雑に対して実施可能な対策候補の情報を格納した対策候補データベースと、所定の空間について将来の時間における混雑指標値の遷移を算出するシミュレーション部と、前記混雑指標値が所定の閾値を超える場合、対策を要する混雑であり空間および時間で特定される要対策混雑を検知する要対策混雑検知部と、前記要対策混雑が検知された空間に適用可能な対策候補を適用した条件のシミュレーションで算出される混雑指標値が前記閾値を超えるか否かを含む前記対策候補の評価結果を出力する出力部と、を有する。 A congestion prediction system according to an embodiment of the present invention includes a countermeasure candidate database storing information on countermeasure candidates that can be implemented for congestion in a predetermined space, and a transition of congestion index values at a future time for the predetermined space. When the congestion index value exceeds a predetermined threshold value, a simulation unit to calculate, a countermeasure-necessary congestion detection unit for detecting a countermeasure-necessary congestion which is a congestion requiring countermeasures and specified by space and time, and the countermeasure-necessary congestion is detected An output unit that outputs an evaluation result of the countermeasure candidate including whether or not a congestion index value calculated by a simulation of a condition that applies a countermeasure candidate applicable to the space exceeds the threshold value.
 本発明によれば、要対策混雑が発生する空間および時間と共に、その混雑に適用可能な対策候補とその評価結果を出力するので、要対策混雑に対して適切な対策を判断するのが容易になる。 According to the present invention, the countermeasure candidates applicable to the congestion and the evaluation result are output together with the space and time in which the countermeasure countermeasure congestion occurs, so that it is easy to determine an appropriate countermeasure against the countermeasure congestion. Become.
本実施形態による混雑予測システムの構成例を示す図である。It is a figure which shows the structural example of the congestion prediction system by this embodiment. 予測人数情報データベース111に記録されている予測人数情報210の一例を示す図である。It is a figure which shows an example of the predicted number information 210 recorded on the predicted number information database. 空間情報データベース112に記録されている空間情報220の一例を表す図である。It is a figure showing an example of the spatial information 220 recorded on the spatial information database. 空間情報データベース112に記録されている部分空間情報230の一例を示す図である。It is a figure which shows an example of the partial space information 230 recorded on the spatial information database. 図4の部分空間情報230に含まれる各部分空間の範囲を平面に示した図である。It is the figure which showed the range of each partial space contained in the partial space information 230 of FIG. 4 on the plane. シミュレーションによって算出される混雑予測結果240の一例を表す図である。It is a figure showing an example of the congestion prediction result 240 calculated by simulation. 対策候補データベース113に記録されている対策候補250の一例を表す図である。It is a figure showing an example of the countermeasure candidate 250 recorded on the countermeasure candidate database 113. FIG. 要対策混雑検知部130が要対策混雑を検知した場合に出力するデータである要対策混雑情報270の一例を示す図である。It is a figure which shows an example of the countermeasure required congestion information 270 which is data output when the countermeasure required congestion detection part 130 detects the countermeasure required congestion. 要対策混雑への対策候補250と対策開始時刻を組み合わせた対策候補のデータである。This is data of candidate countermeasures combining the candidate countermeasures 250 for countermeasure congestion required and the countermeasure start time. 要対策混雑に対して対策を実施すべき優先度を評価し、最終対策開始時刻と対策優先度評価値を付加したデータである対策優先度評価結果290を示す図である。It is a figure which shows the countermeasure priority evaluation result 290 which is data which evaluated the priority which should implement a countermeasure with respect to countermeasure required congestion, and added the last countermeasure start time and the countermeasure priority evaluation value. 図9に示した対策案280に混雑緩和評価値および対策案評価値を付加したデータである対策案評価結果300を示す図である。It is a figure which shows the countermeasure plan evaluation result 300 which is the data which added the congestion mitigation evaluation value and the countermeasure plan evaluation value to the countermeasure plan 280 shown in FIG. 対策開始時刻算出部140の処理例を説明するための図である。FIG. 10 is a diagram for explaining a processing example of a countermeasure start time calculation unit 140. 対策開始時刻算出部140の処理例を示すフローチャートである。5 is a flowchart illustrating a processing example of a countermeasure start time calculation unit 140. 対策優先度評価部160の処理例を示すフローチャートである。10 is a flowchart illustrating a processing example of a countermeasure priority evaluation unit 160. 対策案評価部170の処理例を示すフローチャートである。10 is a flowchart illustrating a processing example of a countermeasure plan evaluation unit 170. 出力部180の処理例を示すフローチャートである。6 is a flowchart illustrating a processing example of an output unit 180. 出力部180による画面表示の例を示す図である。6 is a diagram illustrating an example of screen display by the output unit 180. FIG. システム全体の処理例を示すフローチャートである。It is a flowchart which shows the example of a process of the whole system.
 以下、本発明の実施形態による混雑予測システムについて図面を用いて説明する。
<構成>
Hereinafter, a congestion prediction system according to an embodiment of the present invention will be described with reference to the drawings.
<Configuration>
 図1は、本実施形態による混雑予測システムの構成例を示す図である。混雑予測システムは、鉄道駅の空間における旅客の混雑状況を監視し、必要に応じて監視員による対策の実施を支援するコンピュータシステムである。混雑予測システムは1つのコンピュータまたは相互に接続された複数のコンピュータで構成される。 FIG. 1 is a diagram illustrating a configuration example of a congestion prediction system according to the present embodiment. The congestion prediction system is a computer system that monitors passenger congestion in the space of a railway station and supports the implementation of countermeasures by a supervisor as necessary. The congestion prediction system includes one computer or a plurality of computers connected to each other.
 混雑予測システムは、予測人数情報データベース111、空間情報データベース112、対策候補データベース113、シミュレーション部120、要対策混雑検知部130、対策開始時刻算出部140、条件変更部150、対策優先度評価部160、対策案評価部170、および出力部180を有している。混雑予測システムは、図2に示す予測人数情報210、図3に示す空間情報220、図4に示す部分空間情報230、図6に示す混雑予測結果240、図7に示す対策候補250、図8に示す要対策混雑情報270、図9に示す対策案280、図10に示す対策優先度評価結果290、図11に示す対策案評価結果300をデータとして用いて処理を実行する。 The congestion prediction system includes a predicted number-of-persons information database 111, a spatial information database 112, a countermeasure candidate database 113, a simulation unit 120, a countermeasure required congestion detection unit 130, a countermeasure start time calculation unit 140, a condition change unit 150, and a countermeasure priority evaluation unit 160. The countermeasure plan evaluation unit 170 and the output unit 180 are provided. The congestion prediction system includes predicted number information 210 shown in FIG. 2, spatial information 220 shown in FIG. 3, partial space information 230 shown in FIG. 4, congestion prediction result 240 shown in FIG. 6, countermeasure candidate 250 shown in FIG. The processing is executed using the countermeasure countermeasure congestion information 270 shown in FIG. 9, the countermeasure proposal 280 shown in FIG. 9, the countermeasure priority evaluation result 290 shown in FIG. 10, and the countermeasure proposal evaluation result 300 shown in FIG. 11 as data.
 混雑予測システムは、予測人数情報210を記録した予測人数情報データベース111と、空間情報220および部分空間情報230を記録した空間情報データベース112と、対策候補250を記録した対策候補データベース113をデータベースとして有している。予測人数情報210は、鉄道駅内での時間帯毎の旅客の移動の様子を示すデータである。 The congestion prediction system has a predicted number information database 111 in which predicted number information 210 is recorded, a spatial information database 112 in which spatial information 220 and partial space information 230 are recorded, and a countermeasure candidate database 113 in which countermeasure candidates 250 are recorded as databases. is doing. The predicted number-of-persons information 210 is data indicating the state of passenger movement in each time zone within the railway station.
 シミュレーション部120は、予測人数情報210と空間情報220を入力として、空間情報220が表す空間内で、予測人数情報210に示されているように旅客が移動したときの空間内の各部分空間の混雑状況を予測し、予測結果を混雑予測結果240として出力する。混雑予測結果240は、各時刻における各部分空間における混雑の程度(混雑指標値)を示すテーブルである。 The simulation unit 120 receives the predicted number of people information 210 and the spatial information 220 as inputs, and in the space represented by the spatial information 220, as shown in the predicted number of people information 210, each partial space in the space when the passenger moves. The congestion situation is predicted, and the prediction result is output as the congestion prediction result 240. The congestion prediction result 240 is a table indicating the degree of congestion (congestion index value) in each partial space at each time.
 要対策混雑検知部130は、混雑予測結果240を入力として、混雑予測結果240が示す混雑指標値が予め定めた閾値を超えるか否かを判定する。混雑指標値が閾値を超えることを検知すると、要対策混雑検知部130は、混雑指標値が閾値を超える時間および部分空間の情報により、対策を要する混雑である要対策混雑を特定する要対策混雑情報270を出力する。要対策混雑を特定する時間が予測混雑時間であり、部分空間が検知部分空間名で示される。 The countermeasure required congestion detection unit 130 receives the congestion prediction result 240 and determines whether or not the congestion index value indicated by the congestion prediction result 240 exceeds a predetermined threshold. When it is detected that the congestion index value exceeds the threshold, the countermeasure required congestion detection unit 130 identifies the countermeasure required congestion that is a congestion requiring countermeasure based on the time and the partial space information when the congestion index value exceeds the threshold. Information 270 is output. The time to identify countermeasure congestion is the predicted congestion time, and the subspace is indicated by the detection subspace name.
 対策開始時刻算出部140は、要対策混雑情報270の検知部分空間名を対象部分空間名とする対策候補250を入力として、混雑指標値が閾値を超えないように、その対策候補250の実施を遅くとも開始すべき時刻である対策開始時刻を出力する。対策候補は、要対策混雑に対して実施する対策の候補である。 The countermeasure start time calculation unit 140 receives the countermeasure candidate 250 having the detected partial space name of the countermeasure necessary congestion information 270 as the target partial space name, and executes the countermeasure candidate 250 so that the congestion index value does not exceed the threshold value. The countermeasure start time that is the time to start at the latest is output. The candidate for countermeasure is a candidate for countermeasure to be implemented for countermeasure congestion.
 条件変更部150は、要対策混雑に対する対策として対策案280を適用した場合の予測人数情報210および空間情報220を出力する。対策案280は、対策候補250と、その対策候補250の適用を開始する時刻である対策開始時刻とで構成される。対策候補250を対策開始時刻に適用を開始すると、その後の各部分空間内の旅客の移動は変化する。 The condition changing unit 150 outputs the predicted number information 210 and the spatial information 220 when the countermeasure plan 280 is applied as a countermeasure against the countermeasure congestion. The countermeasure plan 280 includes a countermeasure candidate 250 and a countermeasure start time that is a time at which application of the countermeasure candidate 250 is started. When application of the countermeasure candidate 250 is started at the countermeasure start time, the subsequent movement of the passenger in each partial space changes.
 対策優先度評価部160は、各要対策混雑の優先度を評価し、その評価結果を対策優先度評価結果290として出力する。本実施形態では、要対策混雑は、その部分空間における混雑の影響の度合い、対策を要する状態を回避するために対策候補を実施すべき時刻までの猶予時間などから評価される。 The countermeasure priority evaluation unit 160 evaluates the priority of each countermeasure countermeasure congestion and outputs the evaluation result as a countermeasure priority evaluation result 290. In the present embodiment, countermeasure required congestion is evaluated from the degree of influence of congestion in the partial space, a grace time until a time when a countermeasure candidate should be executed in order to avoid a state requiring countermeasures, and the like.
 対策案評価部170は、条件変更部150で変更された予測人数情報210および空間情報220を入力としてシミュレーション部120で算出される、対策案280を適用したとした場合の混雑予測結果240を用い、対策案280を評価し、評価結果を対策案評価結果300として出力する。 The measure plan evaluation unit 170 uses the congestion prediction result 240 when the measure plan 280 is applied, which is calculated by the simulation unit 120 with the predicted number of people information 210 and the spatial information 220 changed by the condition change unit 150 as inputs. The measure plan 280 is evaluated, and the evaluation result is output as the measure plan evaluation result 300.
 出力部180は、対策優先度評価結果290と対策案評価結果300を入力として、対策優先度評価結果290と対策案評価結果300を対策を実施すべき要員(例えば誘導員)が所持するコンピュータ端末に表示する。
<機能>
The output unit 180 receives the countermeasure priority evaluation result 290 and the countermeasure plan evaluation result 300 as input, and the computer terminal possessed by the personnel (for example, a guide) who should implement the countermeasure priority evaluation result 290 and the countermeasure plan evaluation result 300 To display.
<Function>
 続いて、混雑予測システムの各部の機能について、より詳しく個別に説明する。 Subsequently, the functions of each part of the congestion prediction system will be described in more detail individually.
 予測人数情報データベース111は、予測人数情報210を記録するデータベースであり、記録、検索、および読出の機能を有する。予測人数情報データベース111に保存される予測人数情報210は、予測値である。予測人数情報210の予測値は、例えば、改札機の通過人数の記録データを入力として、公知の路線シミュレーションを用いて逐次算出し、予測人数情報データベース111に逐次追加保存すればよい。 The predicted number information database 111 is a database that records the predicted number information 210, and has functions of recording, searching, and reading. The predicted number information 210 stored in the predicted number information database 111 is a predicted value. The predicted value of the predicted number of people information 210 may be sequentially calculated using, for example, a well-known route simulation, with the record data of the number of people passing through the ticket gates as input, and additionally stored in the predicted number of people information database 111.
 空間情報データベース112は、空間情報220および部分空間情報230を記録するデータベースであり、記録、検索、および読出の機能を有する。空間情報220および部分空間情報230は、混雑予測を行う対象の駅ごとに予め作成される。空間情報220は、鉄道駅の空間内を格子状に区切り、各格子に各位置の機能を割り付けた地図データである。部分空間情報230は、全体の空間に含まれる所定範囲に定義された部分空間について、その範囲および属性を付与した情報である。 The spatial information database 112 is a database that records the spatial information 220 and the partial spatial information 230, and has recording, searching, and reading functions. The spatial information 220 and the partial space information 230 are created in advance for each target station for which congestion prediction is performed. The spatial information 220 is map data in which the space of the railway station is divided into a grid pattern and the function of each position is assigned to each grid. The partial space information 230 is information in which a range and attributes are assigned to a partial space defined in a predetermined range included in the entire space.
 対策候補データベース113は、対策候補250を記録するデータベースであり、記録、検索、および読出の機能を有する。対策候補250は、部分空間毎にその混雑に対して適用可能な対策の候補の一覧データである。対策候補250は、混雑予測を行う対象の駅ごとに予め作成する。 The countermeasure candidate database 113 is a database that records the countermeasure candidates 250 and has recording, searching, and reading functions. The countermeasure candidate 250 is list data of candidate countermeasures applicable to the congestion for each partial space. The countermeasure candidate 250 is created in advance for each target station for which congestion prediction is to be performed.
 シミュレーション部120は、予測人数情報210と空間情報220と部分空間情報230を入力として、空間情報220で表される空間に、予測人数情報210に従って旅客の移動を発生させたときのその空間内での混雑状況を公知の歩行者シミュレーション装置を用いて予測し、各部分空間の混雑指標値の時系列の遷移である混雑予測結果240を出力する。混雑指標は、例えば空間内の滞在人数、群集密度、動線密度を用いる。本実施形態では、歩行者シミュレーション装置の一例として公知のセルオートマトンを用いるものとする。 The simulation unit 120 receives the predicted number of people information 210, the spatial information 220, and the partial space information 230 as input, and in the space when the passenger is moved in the space represented by the spatial information 220 according to the predicted number of people information 210. Is predicted using a known pedestrian simulation device, and a congestion prediction result 240 that is a time-series transition of the congestion index value of each partial space is output. As the congestion index, for example, the number of people staying in the space, the crowd density, and the flow line density are used. In this embodiment, a known cellular automaton is used as an example of a pedestrian simulation apparatus.
 要対策混雑検知部130は、シミュレーション部120の出力する混雑予測結果240を入力として、各部分空間に対して、混雑予測結果240に、対策を要するか否かを判定するための閾値を超える混雑を示すデータが存在するか否かを判定し、閾値を超えるデータが存在する場合には、その部分空間と時間の情報を要対策混雑情報270として出力する。閾値は、例えば、用いている混雑指標において、群集事故のリスクが所定値以上に高いとされる指標値、あるいは監視者が予め入力した指標値を用いる。 The countermeasure-necessary congestion detection unit 130 receives the congestion prediction result 240 output from the simulation unit 120 as an input, and the congestion prediction result 240 for each partial space exceeds the threshold for determining whether a countermeasure is required. If there is data exceeding the threshold value, information on the partial space and time is output as the countermeasure required congestion information 270. As the threshold value, for example, an index value that indicates that the risk of crowd accident is higher than a predetermined value in the congestion index that is used, or an index value that is input in advance by a monitor is used.
 対策開始時刻算出部140は、要対策混雑検知部130が要対策混雑情報270を出力したときに、要対策混雑が検知された部分空間の混雑予測結果240を第1の混雑予測結果とし、対策候補を現時刻から要対策混雑が検知される時刻までの範囲内の任意の時刻を仮の対策開始時刻とした仮の対策案280を作成して条件変更部150に入力し、シミュレーション部120で算出される要対策混雑が検知された部分空間の混雑予測結果240を第2の混雑予測結果として、第1の混雑予測結果と第2の混雑予測結果を用いて、対策候補を実施して混雑指標値が閾値を超えないために、遅くとも混雑条件を実施すべき時刻である対策開始時刻を算出して出力する。 The countermeasure start time calculation unit 140 uses the congestion prediction result 240 of the partial space in which the countermeasure required congestion is detected as the first congestion prediction result when the countermeasure required congestion detection unit 130 outputs the countermeasure required congestion information 270. A temporary countermeasure plan 280 is created with the candidate as an arbitrary time within a range from the current time to the time when countermeasure congestion is detected, and is input to the condition changing unit 150. The simulation unit 120 Using the first congestion prediction result and the second congestion prediction result as the second congestion prediction result, the congestion prediction result 240 of the subspace in which the countermeasure required congestion is calculated is used as a second congestion prediction result, and the countermeasure candidates are congested. Since the index value does not exceed the threshold value, the countermeasure start time that is the time at which the congestion condition should be implemented is calculated and output at the latest.
 条件変更部150は、対策案280を入力として、対策案280を基に予測人数情報210と空間情報220の少なくとも一方に変更を加え、変更を加えた予測人数情報210および空間情報220を出力する。要対策混雑に対して対策開始時刻に対策候補を適用することを想定し、例えば、改札機の方向を双方向から一方通行(出)に変更するという対策案280が入力されたとき、空間情報220に対して、対策開始時刻に改札機を双方向から一方通行(出)に変更を加えた空間情報220を出力する。この変更された空間情報220と予測人数情報210をシミュレーション部120に入力することで、対策案280を適用した場合の混雑予測を行い、そのときの混雑予測結果240を得ることができる。 The condition changing unit 150 receives the countermeasure plan 280 as an input, changes at least one of the predicted number of people information 210 and the spatial information 220 based on the countermeasure plan 280, and outputs the predicted number of people information 210 and the spatial information 220 with the changes. . Assuming that countermeasure candidates are applied at the countermeasure start time for countermeasure countermeasure congestion, for example, when a countermeasure proposal 280 for changing the direction of the ticket gate from bidirectional to one-way (out) is input, spatial information For 220, the space information 220 in which the ticket gate is changed from bidirectional to one-way (out) at the countermeasure start time is output. By inputting the changed spatial information 220 and the predicted number of people information 210 to the simulation unit 120, it is possible to perform congestion prediction when the countermeasure plan 280 is applied, and to obtain the congestion prediction result 240 at that time.
 対策優先度評価部160は、要対策混雑検知部130で要対策混雑が検知されたとき、要対策混雑情報270を入力として、要対策混雑が生じた部分空間の混雑予測結果、その部分空間に対する対策候補および対策開始時刻、その部分空間の優先度を用いて、対策優先度評価値を算出し、算出結果を対策優先度評価結果290として出力する。 The countermeasure priority evaluation unit 160 receives the countermeasure required congestion information 270 when the countermeasure required congestion detection unit 130 detects the countermeasure required congestion, and the congestion prediction result of the partial space where the countermeasure required congestion has occurred, The measure priority evaluation value is calculated using the measure candidate, the measure start time, and the priority of the subspace, and the calculated result is output as the measure priority evaluation result 290.
 対策案評価部170は、シミュレーション部120において対策候補と対策開始時刻で構成される対策案280を適用した場合の混雑予測結果を入力として、対策候補を適用した場合の評価値を算出し、算出結果を対策案評価結果300として出力する。 The measure plan evaluation unit 170 calculates the evaluation value when the measure candidate is applied, using the congestion prediction result when the measure plan 280 composed of the measure candidate and the measure start time is applied in the simulation unit 120 as an input. The result is output as a measure proposal evaluation result 300.
 出力部180は、対策優先度評価結果および対策案評価結果を出力して画面に表示する機能を有する。表示は例えば、監視員である駅員が保持しているコンピュータ、または旅客への情報提供を目的に駅構内のデジタルサイネージに対して行う。対策優先度評価結果は、対策優先度評価値に基づいて優先順位付けして表示される。対策評価結果は、対策案評価結果の対策案評価値に基づいて優先順位付けして表示される。優先順位付けして表示するとは、例えば、評価値に基づく順番に整列させて表示する、あるいは表示する大きさ、色、アイコンなどのデザインを評価値により変更することを言う。 The output unit 180 has a function of outputting the countermeasure priority evaluation result and the countermeasure plan evaluation result and displaying them on the screen. The display is performed, for example, on a digital signage in the station premises for the purpose of providing information to passengers or computers held by station staff who are monitoring staff. The countermeasure priority evaluation results are displayed with priorities based on the countermeasure priority evaluation values. The countermeasure evaluation results are displayed with priorities based on the countermeasure proposal evaluation values of the countermeasure proposal evaluation results. Displaying with priorities means, for example, arranging and displaying in order based on evaluation values, or changing the design such as size, color, and icon to be displayed according to the evaluation values.
 以上に示した本実施形態の混雑予測システムの各部の機能は、演算装置、制御装置、記憶装置、および入出力装置を有するコンピュータとそのコンピュータ上で動作するソフトウェアとで実現される。また、混雑予測システムは複数の構成要素から成り立つ構成であってもよく、その場合、各構成要素は、相互にバスあるいはネットワークを介して接続し、相互にデータ通信を行うことが可能である。
<データの説明>
The function of each part of the congestion prediction system of the present embodiment described above is realized by a computer having an arithmetic device, a control device, a storage device, and an input / output device, and software operating on the computer. In addition, the congestion prediction system may be configured by a plurality of components. In this case, the components can be connected to each other via a bus or a network and can perform data communication with each other.
<Explanation of data>
 続いて、混雑予測システムで用いる各種データについて説明する。 Subsequently, various data used in the congestion prediction system will be described.
 図2は、予測人数情報データベース111に記録されている予測人数情報210の一例を示す図である。予測人数情報210は、出発地と目的地の組み合わせごとに、その間を移動する旅客数を時間別に記録したデータである。駅構内においては、駅の出入口およびホーム(列車)が出発地および目的地である。出発地がホーム(列車)である場合、列車の到着時刻を開始時刻とし、列車の出発時刻を終了時刻とする。 FIG. 2 is a diagram showing an example of the predicted number of people information 210 recorded in the predicted number of people information database 111. The predicted number of people information 210 is data in which the number of passengers moving between the departure point and the destination is recorded by time. In the station yard, the station entrance and platform (train) are the departure point and destination. When the departure place is a home (train), the arrival time of the train is set as the start time, and the departure time of the train is set as the end time.
 例えば、図2では、出入口1を出発地として、時刻7:00から時刻7:10の間に、ホーム1を目的地として移動する人数が10人である。また、ホーム1を出発地として、時刻7:01から時刻7:02の間に、ホーム2を目的地として移動する人数が30人である。これは時刻7:01にホーム1に到着し、時刻7:02に出発する列車1から降車する旅客のうち30人がホーム2を目的地として移動することを意味する。 For example, in FIG. 2, the number of people who move from the doorway 1 to the starting point and from the time 7:00 to the time 7:10 with the home 1 as the destination is ten. In addition, the number of people who move from home 7 as the destination and from home 7 as the destination between time 7:01 and time 7:02 is 30. This means that 30 passengers who arrive at the home 1 at the time 7:01 and get off from the train 1 leaving at the time 7:02 travel with the home 2 as the destination.
 図3は、空間情報データベース112に記録されている空間情報220の一例を表す図である。空間情報220は、駅の構造および設備の情報を記録するデータであり、駅の構造を元に予め作成しておく。本実施形態では、公知のセルオートマトンを用いた歩行者シミュレーションで用いられる、空間を格子状に分割した格子空間を用いて空間情報200を表している。 FIG. 3 is a diagram illustrating an example of the spatial information 220 recorded in the spatial information database 112. Spatial information 220 is data for recording station structure and facility information, and is created in advance based on the station structure. In this embodiment, the spatial information 200 is represented using a lattice space obtained by dividing a space into a lattice shape, which is used in a pedestrian simulation using a known cellular automaton.
 格子空間は、例えば、その属する部分空間により、通路格子、壁格子、階段格子、改札機格子、出入口・乗車位置格子のような単位格子で構成されている。各格子には、その属性として、例えば、通行の可否、通行可能な速度、通行可能な方向、通行に要する距離コスト、全体の空間への歩行者の流出入の可否の情報が与えられている。図3の例は、改札口が1つ、ホームが2つある駅の構造を、単位格子を用いた空間として表した例である。 The lattice space is composed of unit lattices such as a passage lattice, a wall lattice, a stair lattice, a ticket gate lattice, an entrance / exit position lattice depending on a partial space to which the lattice space belongs. For each grid, for example, information on whether or not it is possible to pass, speed that can pass, direction that can pass, distance cost required for passing, and whether or not pedestrians can enter and leave the entire space is given. . The example of FIG. 3 is an example in which the structure of a station having one ticket gate and two platforms is represented as a space using a unit grid.
 図4は、空間情報データベース112に記録されている部分空間情報230の一例を示す図である。部分空間情報230は、要対策混雑の検知を行う単位である部分空間のデータである。図5は、図4の部分空間情報230に含まれる各部分空間の範囲を平面に示した図である。 FIG. 4 is a diagram illustrating an example of the partial space information 230 recorded in the spatial information database 112. The partial space information 230 is data of a partial space that is a unit for detecting the countermeasure required congestion. FIG. 5 is a diagram showing a range of each partial space included in the partial space information 230 of FIG. 4 on a plane.
 まず、部分空間について図4および図5を用いて説明する。図4には、図3の空間情報を基に作成した部分空間情報230が示されている。部分空間は、通行量の規制や方向の制限が実施可能な地点や経路の分岐が生じる地点で空間を分離することによりできた個々の空間である。例えば、図5に示す範囲A001~A004はそれぞれ部分空間であり、地点A011~A014(階段)およびA021(改札機)によって分離されている。部分空間としては、要対策混雑の検知を行う単位とすることができる範囲を設定すればよく、図4および図5の例より細かく設定してもよい。例えば、部分空間名「ホーム1」を複数の部分空間に分割し、より細かい単位で部分空間の範囲を設定してもよい。 First, the partial space will be described with reference to FIG. 4 and FIG. FIG. 4 shows partial space information 230 created based on the spatial information of FIG. A partial space is an individual space created by separating a space at a point where traffic restriction or direction restriction can be performed or where a branch of a route occurs. For example, ranges A001 to A004 shown in FIG. 5 are partial spaces, and are separated by points A011 to A014 (stairs) and A021 (ticket gates). As the partial space, a range that can be set as a unit for detecting the countermeasure congestion is set, and may be set more finely than the examples in FIGS. For example, the partial space name “home 1” may be divided into a plurality of partial spaces, and the range of the partial space may be set in finer units.
 続いて、図4に示した部分空間情報230の内容について説明する。部分空間情報230には、部分空間名、範囲、部分空間優先度、接続地点、および接続部分空間名が対応づけて記録されている。 Subsequently, the contents of the partial space information 230 shown in FIG. 4 will be described. In the partial space information 230, a partial space name, a range, a partial space priority, a connection point, and a connected partial space name are recorded in association with each other.
 部分空間名は、部分空間の名称であり、1つの部分空間について1つの部分空間名が1対1で対応する。 The partial space name is a name of the partial space, and one partial space name corresponds one-to-one with respect to one partial space.
 範囲は、部分空間の範囲を示し、本実施形態においては、部分空間を構成する格子の集合であり、例えば、部分空間を構成する格子の配列として表わされる。図4に記載されている範囲は、図5に示した範囲A001~A004のそれぞれに対応する。 The range indicates the range of the subspace, and in the present embodiment, the range is a set of lattices constituting the partial space, and is represented as, for example, an array of lattices constituting the partial space. The ranges described in FIG. 4 correspond to the ranges A001 to A004 shown in FIG.
 部分空間優先度は、複数の部分空間について要対策混雑が検知されたとき対策を実施する優先度を判定するときに用いるために予め設定された評価値である。例えば、ホーム上での混雑は、線路への転落など、コンコースと比較して危険な事故が発生しやすい。そのため、ホームでの混雑はコンコースでの混雑よりも高い優先度が設定されている。 The partial space priority is an evaluation value set in advance for use in determining the priority for implementing a countermeasure when a countermeasure required congestion is detected for a plurality of partial spaces. For example, congestion on the platform is likely to cause dangerous accidents compared to concourses, such as falling to a track. Therefore, higher priority is set for congestion at home than for concourse.
 接続地点は、部分空間が他の部分空間と接続される地点である。例えば、ホーム1(範囲A001)は、階段1(地点A011)および階段2(地点A012)を接続地点として、他の部分空間と接続される。接続地点は、部分空間と同様に、格子の集合であり、例えば接続地点を表す格子の配列として表わされる。 A connection point is a point where a partial space is connected to another partial space. For example, the home 1 (range A001) is connected to another partial space using the staircase 1 (point A011) and the staircase 2 (point A012) as connection points. Similar to the partial space, the connection point is a set of lattices, and is represented, for example, as an array of lattices representing the connection points.
 接続部分空間名は、部分空間が接続地点を介して接続する他の部分空間の部分空間名を記録する。例えば、ホーム1(範囲A001)は、階段1(地点A011)および階段2(地点A012)を介してコンコース改札内(範囲A003)と接続される。 The connection subspace name records the subspace name of another subspace to which the subspace is connected via the connection point. For example, home 1 (range A001) is connected to the inside of the concourse ticket gate (range A003) via stairs 1 (point A011) and stairs 2 (point A012).
 図6は、シミュレーションによって算出される混雑予測結果240の一例を表す図である。混雑予測結果240は、各部分空間の混雑指標の時系列の予測値で構成されたデータである。混雑指標としては、例えば、部分空間内の滞在人数、群集密度、あるいは動線密度を用いることができる。 FIG. 6 is a diagram illustrating an example of the congestion prediction result 240 calculated by simulation. The congestion prediction result 240 is data composed of time-series predicted values of the congestion index of each partial space. As the congestion index, for example, the number of people staying in the partial space, the crowd density, or the flow line density can be used.
 図7は、対策候補データベース113に記録されている対策候補250の一例を表す図である。対策候補250は、駅などの空間ごとに実施可能な混雑に対する対策を表すデータである。対象部分空間名は、対策を実施する対象となる部分空間を示す。対象地点は、部分空間情報230の接続地点に対応する地点である。対象地点の状態を変化させることで、混雑への対策を実施することができる。対策状態とは、対象地点がとり得る状態を表す。とり得る状態とは、改札機の通行方向のように機械の取りうる状態と、階段の通行方向規制のように駅員が交通整理を行うことによって生じる状態の双方を含む。 FIG. 7 is a diagram illustrating an example of the countermeasure candidate 250 recorded in the countermeasure candidate database 113. The countermeasure candidate 250 is data representing countermeasures against congestion that can be implemented for each space such as a station. The target subspace name indicates a subspace to be subjected to countermeasures. The target point is a point corresponding to the connection point of the partial space information 230. By changing the state of the target point, measures against congestion can be implemented. The countermeasure state represents a state that the target point can take. The state that can be taken includes both a state that the machine can take such as the direction of traffic of the ticket gate and a state that occurs when the station staff performs traffic control such as regulation of the direction of passage of stairs.
 図8は、要対策混雑検知部130が要対策混雑を検知した場合に出力するデータである要対策混雑情報270の一例を示す図である。検知部分空間名は、要対策混雑が発生すると検知された部分空間の名称である。予測混雑時間は、要対策混雑が発生する時間帯である。最大混雑は、予測された要対策混雑における混雑指標の最大値である。 FIG. 8 is a diagram illustrating an example of countermeasure required congestion information 270 that is data output when the countermeasure required congestion detection unit 130 detects countermeasure required congestion. The detection subspace name is a name of the subspace detected when the countermeasure required congestion occurs. The predicted congestion time is a time zone in which the countermeasure required congestion occurs. The maximum congestion is the maximum value of the congestion index in the predicted countermeasure congestion.
 図9は、要対策混雑への対策候補250と対策開始時刻を組み合わせた対策候補のデータである。図9には、要対策混雑が検知された部分空間がホーム1である場合が例示されている。対策候補250の対策を適用したという条件でのシミュレーションで得られる混雑指標値が閾値を超えないために、遅くとも対策候補を実行すべき時刻である対策開始時刻を含むデータである。 FIG. 9 shows countermeasure candidate data combining the countermeasure candidate 250 for countermeasure congestion required and the countermeasure start time. FIG. 9 illustrates the case where the partial space where the countermeasure required congestion is detected is the home 1. Since the congestion index value obtained by the simulation under the condition that the countermeasure of the countermeasure candidate 250 is applied does not exceed the threshold, the data includes the countermeasure start time that is the time when the countermeasure candidate should be executed at the latest.
 図10は、要対策混雑に対して対策を実施すべき優先度を評価し、最終対策開始時刻と対策優先度評価値を付加したデータである対策優先度評価結果290を示す図である。 FIG. 10 is a diagram showing a countermeasure priority evaluation result 290 that is data obtained by evaluating the priority at which countermeasures should be taken against the countermeasure congestion required and adding the final countermeasure start time and the countermeasure priority evaluation value.
 対策優先度評価結果290は、要対策混雑に対して、対策を実施すべき優先度を評価し、最終対策開始時刻と対策優先度評価値を付加したデータである。最終対策開始時刻とは、検知部分空間名を対象部分空間名とする対策案のうち、最も遅い対策開始時刻を表す。対策優先度評価値とは、予測混雑時間、最大混雑、および最終対策開始時刻を基に、対策優先度評価部160で算出される評価値である。なお、本実施形態では最大混雑を要対策混雑の評価に用いる例を示すが、これに限定されることはない。最大混雑の代わりに、混雑指標の平均値など混雑の程度を示す他の指標を用いてもよい。 The countermeasure priority evaluation result 290 is data obtained by evaluating the priority at which countermeasures should be taken for countermeasure countermeasure congestion, and adding the final countermeasure start time and the countermeasure priority evaluation value. The final countermeasure start time represents the latest countermeasure start time among the countermeasure proposals using the detection subspace name as the target subspace name. The countermeasure priority evaluation value is an evaluation value calculated by the countermeasure priority evaluation unit 160 based on the predicted congestion time, the maximum congestion, and the final countermeasure start time. In the present embodiment, an example is shown in which the maximum congestion is used for evaluation of countermeasure required congestion, but the present invention is not limited to this. Instead of the maximum congestion, another index indicating the degree of congestion such as an average value of the congestion index may be used.
 図11は、図9に示した対策案280に混雑緩和評価値および対策案評価値を付加したデータである対策案評価結果300を示す図である。混雑緩和評価値とは、対策案280を適用したという条件でのシミュレーションにより算出される混雑指標値と閾値との差分から計算される、対策案280を実施した場合の混雑緩和効果の評価値である。対策案評価値は、現時刻から対策開始時刻までの猶予時間の長さと混雑緩和評価値とから計算される対策案280の評価値である。
<処理>
FIG. 11 is a diagram illustrating a countermeasure plan evaluation result 300 that is data obtained by adding a congestion mitigation evaluation value and a countermeasure plan evaluation value to the countermeasure plan 280 illustrated in FIG. 9. The congestion alleviation evaluation value is an evaluation value of the congestion mitigation effect when the countermeasure plan 280 is calculated, which is calculated from the difference between the congestion index value calculated by simulation under the condition that the countermeasure plan 280 is applied and the threshold value. is there. The measure plan evaluation value is an evaluation value of the measure plan 280 calculated from the length of the grace time from the current time to the measure start time and the congestion alleviation evaluation value.
<Processing>
 続いて各部の処理例について説明する。 Next, processing examples of each part will be described.
 まず、図12および図13を用いて対策開始時刻算出部140の処理例について説明する。 First, a processing example of the countermeasure start time calculation unit 140 will be described with reference to FIGS. 12 and 13.
 図12は、対策開始時刻算出部140の処理例を説明するための図である。図12には、要対策混雑が検知された部分空間の混雑指標の時間遷移を示す第1の混雑予測結果と、仮の対策案として、現在時刻から要対策混雑が検知される時刻までの範囲の任意の時刻に、例えばできるだけ早期に対策候補を適用したとした条件のシミュレーションにより算出した混雑指標の時間遷移を示す第2の混雑予測結果とがグラフに示されている。 FIG. 12 is a diagram for explaining a processing example of the countermeasure start time calculation unit 140. FIG. 12 shows the first congestion prediction result indicating the time transition of the congestion index of the partial space where the countermeasure required congestion is detected, and the range from the current time to the time when the countermeasure required congestion is detected as a temporary countermeasure plan. The graph shows a second congestion prediction result indicating a time transition of the congestion index calculated by simulation under a condition that the countermeasure candidate is applied as early as possible, for example, at an arbitrary time.
 図13は、対策開始時刻算出部140の処理例を示すフローチャートである。以下、図13の各ステップを参照して対策開始時刻算出部140の処理例について説明する。 FIG. 13 is a flowchart illustrating a processing example of the countermeasure start time calculation unit 140. Hereinafter, a processing example of the countermeasure start time calculation unit 140 will be described with reference to each step of FIG.
 S101:まず、要対策混雑検知部130で検知された要対策混雑に着目し、要対策混雑が検知された混雑予測結果のうち、要対策混雑が検知された部分空間の混雑予測結果を第1の混雑予測結果とし、第1の混雑予測結果と対策候補を入力する。ここで着目した要対策混雑が対策候補の対策開始時刻を算出する対象である。 S101: First, paying attention to the countermeasure required congestion detected by the countermeasure required congestion detection unit 130, the congestion prediction result of the partial space in which the countermeasure required congestion is detected among the congestion prediction results in which the countermeasure required congestion is detected is the first. The first congestion prediction result and the countermeasure candidate are input as the congestion prediction result. The countermeasure required congestion focused here is an object for calculating the countermeasure start time of the countermeasure candidate.
 S102:現時刻から要対策混雑が検知される時刻までの範囲内の任意の時刻を仮の対策開始時刻とし、仮の対策開始時刻を対策候補に付加することにより、仮の対策案を作成する。 S102: A temporary countermeasure plan is created by setting an arbitrary time within the range from the current time to the time when countermeasure required congestion is detected as a temporary countermeasure start time and adding the temporary countermeasure start time to the candidate for countermeasure. .
 S103:仮の対策案を条件変更部150に入力することにより、仮の対策案を適用した場合の混雑指標をシミュレーション部120に算出させる。シミュレーション部120で算出される、対象としている要対策混雑が検知された部分空間の混雑予測結果を第2の混雑予測結果とする。 S103: By inputting the provisional countermeasure plan to the condition changing unit 150, the simulation unit 120 is caused to calculate the congestion index when the provisional countermeasure plan is applied. The congestion prediction result of the partial space in which the target countermeasure required congestion calculated by the simulation unit 120 is detected is set as the second congestion prediction result.
 S104:第1の混雑予測結果を参照し、混雑指標が閾値を超える時間範囲ごとに混雑指標の最大値を算出し、その最大値をとる時刻を時刻tとする。 S104: Referring to the first congestion prediction result, the maximum value of the congestion index is calculated for each time range in which the congestion index exceeds the threshold, and the time when the maximum value is taken is set as time t.
 S105:第1の混雑予測結果を平滑化する。平滑化は、例えば、移動平均法を用いて行なうことができる。 S105: Smooth the first congestion prediction result. Smoothing can be performed using, for example, a moving average method.
 S106:平滑化した第1の混雑予測結果の最大値の直前の極値を算出し、その極値をとる時刻を時刻sとする。 S106: The extreme value immediately before the maximum value of the smoothed first congestion prediction result is calculated, and the time when the extreme value is taken is defined as time s.
 S107:時刻sから時刻tの間の第2の混雑予測結果の混雑指標の最大値と最小値を算出し、最大値および最小値を通る直線の傾きを算出する。 S107: The maximum value and the minimum value of the congestion index of the second congestion prediction result between time s and time t are calculated, and the slope of the straight line passing through the maximum value and the minimum value is calculated.
 S108:S108で算出した傾きを有し、時刻tに混雑指標が閾値と一致する直線を算出する。 S108: A straight line having the slope calculated in S108 and having a congestion index that matches the threshold at time t is calculated.
 S109:S108で算出した直線と第1の混雑予測結果の曲線とが時刻t以前に交わる点を算出し、その点の時刻を対策開始時刻とする。 S109: A point where the straight line calculated in S108 and the curve of the first congestion prediction result intersect before time t is calculated, and the time at that point is set as the countermeasure start time.
 以上のように対策開始時刻を算出する処理は、時間を移動しながらシミュレーションを繰り返し、できるだけ遅らせた対策開始時刻を探索する処理よりも、少ない計算量で対策開始時刻を算出することができる。 As described above, the process of calculating the countermeasure start time can calculate the countermeasure start time with a smaller amount of calculation than the process of repeating the simulation while moving the time and searching for the countermeasure start time delayed as much as possible.
 続いて、図14のフローチャートを用いて対策優先度評価部160の処理例を説明する。 Subsequently, a processing example of the countermeasure priority evaluation unit 160 will be described using the flowchart of FIG.
 S201:要対策混雑検知部130で検知された要対策混雑と、その要対策混雑を含む混雑予測結果と、その要対策混雑が検知された部分空間に適用可能な対策案とについての情報を入力する。ここで情報が入力される要対策混雑が対策優先度を評価する対象となる。その要対策混雑において、混雑指標が閾値を超えた時刻から閾値以下となった時刻までの時間を予測混雑時間とする。 S201: Input information about the countermeasure required congestion detected by the countermeasure required congestion detection unit 130, the congestion prediction result including the countermeasure required congestion, and the countermeasure proposal applicable to the partial space where the countermeasure required congestion is detected. To do. The countermeasure countermeasure congestion to which information is input is a target for evaluating the countermeasure priority. In the countermeasure required congestion, the time from the time when the congestion index exceeds the threshold to the time when the congestion index falls below the threshold is set as the predicted congestion time.
 S202:その要対策混雑が検知された部分空間の部分空間優先度を空間情報データベース112から取得する。 S202: The subspace priority of the subspace where the countermeasure required congestion is detected is acquired from the spatial information database 112.
 S203:その要対策混雑における混雑指標の最大値と閾値との差分を算出する。 S203: The difference between the maximum value of the congestion index and the threshold value in the countermeasure required congestion is calculated.
 S204:その要対策混雑が検知された部分空間に適用できる全ての対策案を抽出する。対策案には対策候補と対策開始時刻とが含まれている。 S204: Extract all countermeasures that can be applied to the subspace where the countermeasures required congestion is detected. The countermeasure plan includes a countermeasure candidate and a countermeasure start time.
 S205:抽出された全ての対策案の対策開始時刻のうち、最も遅い時刻を最終対策開始時刻とする。 S205: Of the countermeasure start times of all the extracted countermeasure plans, the latest time is set as the final countermeasure start time.
 S206:その要対策混雑について、予測混雑時間の長さ、S202で抽出した部分空間優先度、S203で算出した最大混雑と閾値の差、S206で算出した最終対策開始時刻を評価対象値とし、それぞれの評価対象値に予め定めた任意の重みを乗じて、足し合わせることにより、その要対策混雑対策優先度評価値を算出する。なお、最大混雑と閾値との差分は混雑の程度を示す指標の一例であり、混雑の程度を表わす他の指標を代わりに用いてもよい。 S206: With regard to the countermeasure congestion required, the length of the predicted congestion time, the subspace priority extracted in S202, the difference between the maximum congestion calculated in S203 and the threshold, and the final countermeasure start time calculated in S206 are set as evaluation target values. By multiplying the evaluation target value by a predetermined arbitrary weight and adding them together, the countermeasure required congestion countermeasure priority evaluation value is calculated. The difference between the maximum congestion and the threshold value is an example of an index indicating the degree of congestion, and another index indicating the degree of congestion may be used instead.
 S207:要対策混雑情報270と最終対策開始時刻と対策優先度評価値とを対策優先度評価結果290として出力する。なお、ここでは、要対策混雑について対策実施の優先度の総合評価として要対策混雑対策優先度を算出し、表示する例を示したが、これに限定されるものではない。他の例として、予測混雑時間の長さ、S202で抽出した部分空間優先度、S203で算出した最大混雑と閾値の差、およびS206で算出した最終対策開始時刻の一部または全部を個別に監視員に提示し、どの要対策混雑を優先するか判断させることにしてもよい。 S207: The countermeasure required congestion information 270, the final countermeasure start time, and the countermeasure priority evaluation value are output as the countermeasure priority evaluation result 290. In this example, the countermeasure countermeasure congestion countermeasure priority is calculated and displayed as a comprehensive evaluation of countermeasure implementation priority for countermeasure countermeasure congestion. However, the present invention is not limited to this. As another example, the length of the predicted congestion time, the subspace priority extracted in S202, the difference between the maximum congestion and the threshold calculated in S203, and part or all of the final countermeasure start time calculated in S206 are individually monitored. This may be presented to a member to determine which countermeasure congestion is prioritized.
 続いて、図15のフローチャートを用いて対策案評価部170の処理例について説明する。 Subsequently, a processing example of the measure plan evaluation unit 170 will be described using the flowchart of FIG.
 S301:対策案を要対策混雑に適用したとする条件でのシミュレーション部120によるシミュレーションで算出される混雑指標の時間遷移を示す混雑予測結果を入力する。 S301: The congestion prediction result indicating the time transition of the congestion index calculated by the simulation by the simulation unit 120 under the condition that the countermeasure plan is applied to the countermeasure required congestion is input.
 S302:適用した対策案の対策開始時刻と現在時刻との時刻差を対策猶予時間とする。 S302: The time difference between the countermeasure start time of the applied countermeasure proposal and the current time is set as the countermeasure grace time.
 S303:現在時刻から要対策混雑が検知されるまでの間の任意の時刻から対策候補を実施した条件のシミュレーションにより算出される混雑指標値の最大値と閾値と差を算出し、算出結果を混雑緩和評価値とする。なお、混雑指標値の最大値と閾値との差分は混雑指標値の改善の程度を示す指標の一例であり、混雑改善の程度を表わす他の指標を代わりに用いてもよい。 S303: Calculate the difference between the maximum value and threshold value of the congestion index value calculated by the simulation of the condition for implementing the countermeasure candidate from any time between the current time and the detection of countermeasure required congestion. Use the relaxation evaluation value. Note that the difference between the maximum value of the congestion index value and the threshold value is an example of an index indicating the degree of improvement in the congestion index value, and another index indicating the degree of congestion improvement may be used instead.
 S304:その対策案の対策猶予時間と混雑緩和評価値を評価対象値とし、それぞれの評価対象値に任意の重みを乗じて、足し合わせ、その対策案の対策案評価値を算出する。 S304: The countermeasure postponement time and the congestion mitigation evaluation value of the countermeasure plan are set as evaluation target values, the respective evaluation target values are multiplied by arbitrary weights, added together, and the countermeasure plan evaluation value of the countermeasure plan is calculated.
 S305:その対策案に混雑緩和評価値と対策案評価値を関連づけて対策案評価結果とし、対策案評価結果300を出力する。なお、ここでは、対策案についての総合評価として対策案評価値を算出し、表示する例を示したが、これに限定されるものではない。他の例として、対策猶予時間と混雑緩和評価値の両方または一方を個別に監視員に提示し、どの対策案を採用するか判断させることにしてもよい。 S305: The countermeasure proposal evaluation result 300 is output by associating the congestion mitigation evaluation value and the countermeasure proposal evaluation value with the countermeasure proposal as a countermeasure proposal evaluation result. In addition, although the example which calculates and displays a countermeasure plan evaluation value as comprehensive evaluation about a countermeasure plan was shown here, it is not limited to this. As another example, both or one of the countermeasure postponement time and the congestion alleviation evaluation value may be individually presented to a monitor to determine which countermeasure plan to adopt.
 続いて、図16および図17を用いて出力部180の処理例について説明する。 Subsequently, a processing example of the output unit 180 will be described with reference to FIGS. 16 and 17.
 図16は、出力部180の処理例を示すフローチャートである。図17は、出力部180による画面表示の例を示す図である。 FIG. 16 is a flowchart illustrating a processing example of the output unit 180. FIG. 17 is a diagram illustrating an example of screen display by the output unit 180.
 S401:対策優先度評価結果290と対策案評価結果300を入力する。 S401: The countermeasure priority evaluation result 290 and the countermeasure plan evaluation result 300 are input.
 S402:対策優先度評価結果290を、駅の混雑状態を管理する監視員(例えば、駅員)の保持するコンピュータ端末の画面に表示する。対策優先度評価結果290に含まれる要対策混雑を対策優先度評価値が高い順に優先順位付けして表示する。 S402: The countermeasure priority evaluation result 290 is displayed on the screen of a computer terminal held by a monitor (for example, station staff) managing the congestion state of the station. The countermeasure priority congestion included in the countermeasure priority evaluation result 290 is prioritized and displayed in descending order of countermeasure priority evaluation values.
 例えば、図17の対策優先度評価結果表示画面310に示すように、対策優先度評価結果290の要対策混雑について検知部分空間名と予測混雑時間と対策優先度評価値を表示する。図17の例のように、部分空間毎の予測混雑時間を横棒グラフにし、予測混雑時間を示す帯状表示の色あるいは色の濃淡により対策優先度評価値の大小を表わすことができる。これにより、色あるいは色の濃淡で対策優先度の優先順位付けを容易に把握することが可能になる。図17の対策優先度評価結果表示画面310には、要対策混雑が起きる部分空間として、ホーム1、ホーム2、およびコンコース改札内が挙げられている。各部分空間に要対策混雑が起こる時間は、横棒グラフのハッチングで示されている。各要対策混雑の対策優先度の大小はハッチングの濃淡で表現されており、色の濃い方が対策優先度が高いことを意味している。 For example, as shown in the countermeasure priority evaluation result display screen 310 of FIG. 17, the detected subspace name, the estimated congestion time, and the countermeasure priority evaluation value are displayed for the countermeasure priority congestion of the countermeasure priority evaluation result 290. As shown in the example of FIG. 17, the predicted congestion time for each partial space can be represented by a horizontal bar graph, and the measure priority evaluation value can be represented by the color of the band-like display indicating the estimated congestion time or the shade of the color. As a result, it is possible to easily grasp the priority order of countermeasure priority by color or color shading. The countermeasure priority evaluation result display screen 310 of FIG. 17 lists home 1, home 2, and the inside of the concourse ticket gate as partial spaces where countermeasures need to be congested. The time required for countermeasures in each subspace is indicated by hatching in the horizontal bar graph. The level of countermeasure priority for each countermeasure congestion is expressed by shades of hatching, and the darker color means that the countermeasure priority is higher.
 あるいは、他の例として、図10に示したように、対策優先度評価結果290を表形式で表示してもよい。その場合、対策優先度評価値に基づいてソートすれば、優先順位付けを表現することができる。ソートの他の例として、要対策混雑を、最大混雑(混雑指標の最大値)あるいは最終対策開始時刻に基づいてソートしてもよい。あるいは、監視員の操作でソートに用いる評価値を変更できるようにしてもよい。 Alternatively, as another example, as shown in FIG. 10, the countermeasure priority evaluation result 290 may be displayed in a table format. In that case, prioritization can be expressed by sorting based on the measure priority evaluation value. As another example of the sort, the countermeasure required congestion may be sorted based on the maximum congestion (the maximum value of the congestion index) or the last countermeasure start time. Or you may enable it to change the evaluation value used for a sort by operation of a monitoring person.
 S403:監視員は、対策優先度評価結果の表示を見て、対策を実施する要対策混雑を選択する。例えば、図17に示す対策優先度評価結果表示画面310で、監視員がホーム1の要対策混雑を表示した表示311を選択する。 S403: The monitor looks at the display of the countermeasure priority evaluation result, and selects countermeasure congestion requiring countermeasures. For example, on the countermeasure priority evaluation result display screen 310 shown in FIG. 17, the monitor selects the display 311 displaying the countermeasure required congestion of the home 1.
 S404:選択された要対策混雑に対応する対策案評価結果を、監視員の保持するコンピュータ端末に表示する。要対策混雑に複数の対策案が適用可能であれば、複数の対策案の対策案評価結果を、対策案評価値が高い順に優先順位付けして表示してもよい。他の例として、対策開始時刻や混雑緩和評価値に基づいた優先順位を付けてもよい。あるいは、監視員の操作で優先順位付けに用いる評価値を変更できるようにしてもよい。 S404: The countermeasure plan evaluation result corresponding to the selected countermeasure required congestion is displayed on the computer terminal held by the supervisor. If a plurality of countermeasure proposals can be applied to the countermeasure required congestion, the countermeasure proposal evaluation results of the plurality of countermeasure proposals may be prioritized and displayed in descending order of the countermeasure proposal evaluation values. As another example, a priority order based on a countermeasure start time or a congestion mitigation evaluation value may be attached. Or you may enable it to change the evaluation value used for prioritization by operation of a monitoring person.
 また、対策度評価結果の最大混雑が、要対策混雑を検知するための閾値を超えているか否かを区別できるような表示を行ってもよい。例えば、最大混雑が閾値を超えているか否かで、要対策混雑の対策案評価結果を異なる表示としてもよい。例えば、表示色、アイコンの有無、あるいはアイコンの種類によって区別してもよい。また、対策案評価結果の最大混雑が閾値を超えない対策案のみを表示することにしてもよい。 In addition, display may be performed so that it is possible to distinguish whether or not the maximum congestion of the countermeasure degree evaluation result exceeds a threshold for detecting the countermeasure congestion required. For example, the countermeasure plan evaluation result of countermeasure required congestion may be displayed differently depending on whether or not the maximum congestion exceeds a threshold value. For example, you may distinguish by display color, the presence or absence of an icon, or the kind of icon. Alternatively, only countermeasures whose maximum congestion of countermeasure proposal evaluation results does not exceed the threshold may be displayed.
 対策案評価結果の表示は、例えば、図17に示す対策案評価結果表示画面320のように、対策優先度評価結果表示画面310で選択された要対策混雑に対応する対策案を一覧にし、対策案評価値に基づいて順位付けして表示する。図17の対策案評価結果表示画面320には、ホーム1の8:50~9:20の要対策混雑に対する対策案としては、階段1を出る方向のみの一方通行に制限するという対策案と、階段2を出る方向のみの一方通行に制限するという対策案と、改札機1を出る方向のみの一方通行に制限するという対策案が示されている。これらの対策案は、対策案評価値で優先順位付けされ、その順序に表示されている。 For example, the countermeasure plan evaluation result is displayed as a list of countermeasure plans corresponding to the countermeasure required congestion selected on the countermeasure priority evaluation result display screen 310 as in the countermeasure plan evaluation result display screen 320 shown in FIG. Ranking and displaying based on the proposed evaluation value. In the measure plan evaluation result display screen 320 of FIG. 17, as a measure plan for the countermeasure required congestion of 8:50 to 9:20 of the home 1, a measure plan that restricts one-way only in the direction of exiting the stairs 1, There are proposed countermeasures for restricting one-way only in the direction of exiting the stairs 2 and for restricting one-way only in the direction of exiting the ticket gate 1. These countermeasure plans are prioritized according to the countermeasure plan evaluation values and are displayed in that order.
 S405:監視員は、対策案評価結果の表示を見て、実施する対策案を選択する。例えば、図17に示す対策案評価結果表示画面320から、最も上位に順位付けされたレコード321を選択することにより、実施する対策案評価結果を選択する。 S405: The monitor looks at the display of the countermeasure plan evaluation result and selects the countermeasure plan to be implemented. For example, the countermeasure plan evaluation result to be implemented is selected by selecting the highest ranked record 321 from the countermeasure plan evaluation result display screen 320 shown in FIG.
 S406:監視員は、選択した対策案の実施を担当する要員(例えば駅員)を選択する。あるいは、旅客の誘導案内を表示するサイネージを選択してもよい。例えば、図17に示す担当者設定画面330のように担当者のスケジュールを表示し、時間帯331を選択することによって担当者を選択する。対策案を実施する候補者は駅員Aと駅員Bである。ただし、駅員Bは対策を実施する時間に他の作業が入っていることがハッチングで表示され、対策案の実施を担当することができないことが分かる。 S406: The monitoring staff selects personnel (for example, station staff) who are in charge of implementing the selected countermeasure plan. Or you may select the signage which displays a passenger's guidance guidance. For example, the person-in-charge schedule is displayed as in the person-in-charge setting screen 330 shown in FIG. 17, and the person in charge is selected by selecting the time zone 331. Candidates who implement the countermeasure plan are station staff A and station staff B. However, the station staff B is indicated by hatching that other work is being performed at the time when the countermeasure is taken, and it is understood that the station staff B cannot take charge of implementing the countermeasure.
 S407:その対策案を実施する駅員の保持する端末に対して、対策案の内容と実施の指示を通知する。あるいは選択したサイネージに旅客の誘導案内を表示してもよい。例えば、図17の対策案実施内容指示画面340のように、実施する対策の内容を表示する。図17の対策案実施内容指示画面340には、実施する対策案の対象となる接続地点が階段1であり、対策を実施する時間が8:30~9:20であり、対策の内容が、出る方向のみに限定する一方通行であることが表示されている。 S407: The contents of the countermeasure plan and instructions for implementation are notified to the terminal held by the station staff who implements the countermeasure plan. Alternatively, the passenger guidance may be displayed on the selected signage. For example, the content of the countermeasure to be implemented is displayed as in the countermeasure proposal implementation content instruction screen 340 of FIG. In the countermeasure plan implementation content instruction screen 340 of FIG. 17, the connection point that is the target of the countermeasure plan to be implemented is the stairs 1, and the time for implementing the countermeasure is 8:30 to 9:20. It is displayed that it is a one-way street limited to the exit direction only.
 続いて、図18のフローチャートを用いてシステム全体の処理例について説明する。 Subsequently, a processing example of the entire system will be described with reference to the flowchart of FIG.
 S1001:混雑予測システムは、予測人数情報データベース111から現在時刻以降の予測人数情報210を読み込み、空間情報データベース112から空間情報220および部分空間情報230を読み込み、シミュレーション部120に入力する。 S1001: The congestion prediction system reads the predicted number information 210 after the current time from the predicted number information database 111, reads the spatial information 220 and the partial space information 230 from the spatial information database 112, and inputs them to the simulation unit 120.
S1002:混雑予測システムは次にシミュレーション部120で混雑状況を予測し、混雑予測結果を出力する。 S1002: Next, the congestion prediction system predicts the congestion state by the simulation unit 120, and outputs a congestion prediction result.
 S1003:更に、混雑予測システムは混雑予測結果を要対策混雑検知部130に入力し、対策を要する混雑の発生の有無を判定する。対策を要する混雑の発生が検知された場合、要対策混雑検知部130は要対策混雑情報270を出力し、S1004に進む。対策を要する混雑の発生が検知されなかった場合には、混雑予測システムはS1001に戻り、データの読み込みおよび混雑予測を繰り返す。 S1003: Furthermore, the congestion prediction system inputs the congestion prediction result to the countermeasure-required congestion detection unit 130, and determines whether or not congestion requiring countermeasures has occurred. When occurrence of congestion requiring countermeasures is detected, the countermeasure-necessary congestion detection unit 130 outputs countermeasure-necessary congestion information 270, and the process proceeds to S1004. If the occurrence of congestion requiring countermeasures is not detected, the congestion prediction system returns to S1001, and repeats data reading and congestion prediction.
 S1004:混雑予測システムは、要対策混雑情報270において要対策混雑が検知された部分空間を対象部分空間とする対策候補250を対策候補データベース113から抽出する。 S1004: The congestion prediction system extracts, from the countermeasure candidate database 113, the countermeasure candidates 250 whose target partial space is the partial space in which the countermeasure required congestion is detected in the countermeasure required congestion information 270.
 S1005:更に、混雑予測システムは、1005で抽出した各対策候補250のそれぞれについて、対策開始時刻算出部140を用いて対策開始時刻を算出する。 S1005: Furthermore, the congestion prediction system calculates the countermeasure start time for each countermeasure candidate 250 extracted in 1005 using the countermeasure start time calculation unit 140.
 S1006:混雑予測システムは、対策候補と混雑開始時刻を組み合わせて対策案280を作成する。 S1006: The congestion prediction system creates a countermeasure plan 280 by combining the countermeasure candidates and the congestion start time.
 S1007:次に、混雑予測システムは対策案280を条件変更部150に入力し、要対策混雑に対策案280を適用したという条件の予測人数情報210と空間情報220を作成する。 S1007: Next, the congestion prediction system inputs the countermeasure plan 280 to the condition change unit 150, and creates the predicted number information 210 and the spatial information 220 under the condition that the countermeasure plan 280 is applied to the countermeasure required congestion.
 S1008:さらに、混雑予測システムは、対策案280を適用した予測人数情報210と空間情報220をシミュレーション部120に入力し、対策案を適用した場合の混雑状況の予測を行い、予測結果を混雑予測結果240として出力する。 S1008: Furthermore, the congestion prediction system inputs the predicted number of people information 210 and the spatial information 220 to which the countermeasure plan 280 is applied to the simulation unit 120, predicts the congestion situation when the countermeasure plan is applied, and predicts the prediction result as the congestion. The result 240 is output.
 S1009:混雑予測システムは混雑予測結果240を対策案評価部170に入力し、対策案評価結果300を算出する。 S1009: The congestion prediction system inputs the congestion prediction result 240 to the countermeasure plan evaluation unit 170, and calculates the countermeasure plan evaluation result 300.
 S1010:続いて、混雑予測システムは全ての対策案を評価したか否かを判定し、全ての対策案の評価が完了してない場合は、S1008に戻り、他の対策案に対して予測おおび評価の処理を行う。一方、全ての対策案の評価が完了した場合、混雑予測システムはS1011に進む。 S1010: Subsequently, the congestion prediction system determines whether or not all countermeasures have been evaluated. If evaluation of all countermeasures has not been completed, the process returns to S1008 to predict other countermeasures. Process the appraisal. On the other hand, when the evaluation of all countermeasures is completed, the congestion prediction system proceeds to S1011.
 S1011:混雑予測システムは、要対策混雑とその要対策混雑が検知された混雑予測結果とその要対策混雑に対する対策案を対策優先度評価部160に入力し、最終対策開始時刻および対策優先度評価値を算出し、対策優先度評価結果290を出力する。 S1011: The congestion prediction system inputs a countermeasure required congestion, a congestion prediction result in which the countermeasure required congestion is detected, and a countermeasure plan for the countermeasure required congestion to the countermeasure priority evaluation unit 160, and the final countermeasure start time and countermeasure priority evaluation. The value is calculated and the countermeasure priority evaluation result 290 is output.
 S1012:混雑予測システムは、対策優先度評価結果290と対策案評価結果300を出力部180に入力し、画面への表示を行う。 S1012: The congestion prediction system inputs the countermeasure priority evaluation result 290 and the countermeasure plan evaluation result 300 to the output unit 180, and displays them on the screen.
 S1013:混雑システムは、現在時刻が、監視員が指定した終了時刻あるいは最終列車の発車時刻に達したか否かを判定する。現在時刻がそれらの時刻に到達していない場合、混雑予測システムはS1001に戻る。現在時刻がそれらの時刻に達している場合、混雑予測システムは処理を完了する。
<効果>
S1013: The congestion system determines whether or not the current time has reached the end time designated by the monitor or the departure time of the last train. If the current time has not reached those times, the congestion prediction system returns to S1001. If the current time has reached those times, the congestion prediction system completes the process.
<Effect>
 本実施形態の混雑予測システムによれば、逐次に追加される予測人数情報を基に、シミュレーション部120で混雑を予測し、出力した混雑予測結果が対策を要する混雑を含むか否かを判定し、対策を要する混雑が検知されたときに、検知された対策を要する混雑を、混雑の発生時間、混雑の程度、発生場所に応じて評価し、評価値で順位付けして監視員に提供することができる。 According to the congestion prediction system of the present embodiment, the simulation unit 120 predicts congestion based on the predicted number of people information that is sequentially added, and determines whether the output congestion prediction result includes congestion that requires countermeasures. When the congestion that requires countermeasures is detected, the congestion that requires the detected countermeasures is evaluated according to the congestion occurrence time, the degree of congestion, and the location of occurrence, and ranked according to the evaluation value and provided to the monitor be able to.
 混雑の発生が検知されたときに、混雑緩和が期待できる対策案を、混雑緩和の効果を考慮して優先順位付けして監視員に提供することができ、監視員は提供された混雑の対策案から実施する対策案を選択することができる。これにより、監視員は容易に適時に適切な混雑の対策案を判断することができる。 When the occurrence of congestion is detected, a countermeasure plan that can be expected to ease congestion can be prioritized and provided to the observer in consideration of the effect of the congestion relief. The countermeasure plan to be implemented can be selected from the plan. As a result, the monitor can easily determine an appropriate congestion countermeasure plan in a timely manner.
 鉄道駅では列車運行状況によって実際の混雑の状況あるいは予測される将来の混雑の状況が急激に変化することがあるが、本実施形態によれば、混雑に対して監視員が適時に適切な対策案を判断することができる。 In a railway station, the actual congestion situation or the predicted future congestion situation may change abruptly depending on the train operation situation. According to this embodiment, the monitoring staff can take appropriate measures in a timely manner against the congestion. You can judge the idea.
 また、本実施形態によれば、複数の要対策混雑が検知なされたときに、要対策混雑を解消するために遅くとも対策案を実施すべき対策開始時刻を算出することにより、対策を行う優先順位の判断を容易にする。そして、監視員が複数の対策を要する混雑から対策を行う優先度の判断を行う支援をすることができる。例えば、複数の空間および時間の混雑を知らせる警報が出力されたときに、監視員の人員に制限があって同時に全ての警報への対策を実施できない場合にどの対策を優先させるかの判断が容易になる。 Further, according to the present embodiment, when a plurality of countermeasure congestions are detected, the priority order of countermeasures is calculated by calculating the countermeasure start time at which countermeasures should be implemented at the latest to eliminate the countermeasure congestion. To make the judgment easier. Then, it is possible to assist the monitor in determining the priority for taking countermeasures from the congestion that requires a plurality of countermeasures. For example, when alarms are output that indicate congestion in multiple spaces and times, it is easy to determine which countermeasures should be prioritized if there are restrictions on the number of supervisors and countermeasures cannot be implemented for all alarms at the same time become.
 また、対策を要する混雑が検知された場合に、対策を要する混雑の判定基準である閾値以下まで混雑が緩和されると期待できる混雑の対策案を作成し、対策案を混雑の緩和量、対策を実施すべき時刻に応じて評価し、評価値で順位付けして監視員に提供することができ、監視員は提供された対策案から選択することによって、容易に適切な対策案を実施することが可能である。 In addition, when congestion requiring countermeasures is detected, a countermeasure plan for congestion that can be expected to be reduced to a threshold value that is the criterion for determining congestion that requires countermeasures is created, and the countermeasure proposal is used to reduce the congestion amount and countermeasures. Can be evaluated according to the time at which they should be implemented, ranked according to the evaluation value, and provided to the observer. The observer can easily implement appropriate countermeasures by selecting from the provided countermeasures. It is possible.
 以上、説明した本実施形態の一部または全部を以下のように整理することもできる。 A part or all of the above-described embodiment can be organized as follows.
 混雑予測システムは、対策候補データベース113と、シミュレーション部120と、要対策混雑検知部130と、出力部180と、を有している。対策候補データベース113は、所定の空間(部分空間)の混雑に対して実施可能な対策候補の情報を格納している。シミュレーション部120は、所定の空間(部分空間)について将来の時間における混雑指標値の遷移を算出する。要対策混雑検知部130は、混雑指標値が所定の閾値を超える場合、対策を要する混雑であり空間および時間で特定される混雑である要対策混雑を検知する。出力部180は、要対策混雑が検知された空間に適用可能な対策候補を適用した条件のシミュレーションで算出される混雑指標値が閾値を超えるか否かを含む対策候補の評価結果を出力する。 The congestion prediction system includes a countermeasure candidate database 113, a simulation unit 120, a countermeasure-necessary congestion detection unit 130, and an output unit 180. The countermeasure candidate database 113 stores information of countermeasure candidates that can be implemented for congestion in a predetermined space (partial space). The simulation unit 120 calculates the transition of the congestion index value at a future time for a predetermined space (partial space). When the congestion index value exceeds a predetermined threshold, the countermeasure-necessary congestion detection unit 130 detects the countermeasure-necessary congestion that is a congestion that requires countermeasures and that is specified by space and time. The output unit 180 outputs the evaluation result of the countermeasure candidate including whether or not the congestion index value calculated by the simulation of the condition applying the countermeasure candidate applicable to the space where the countermeasure required congestion is detected exceeds the threshold value.
 本実施形態によれば、要対策混雑が発生する空間および時間と共に、その混雑に適用可能な対策候補とその評価結果が出力されるので、要対策混雑に対して適時に適切な対策を判断するのが容易になる。 According to the present embodiment, a countermeasure candidate applicable to the congestion and an evaluation result thereof are output together with a space and time in which the countermeasure congestion is generated, so that an appropriate countermeasure can be determined in a timely manner against the countermeasure congestion. It becomes easy.
 また、対策案評価部170は、要対策混雑に、現在時刻から要対策混雑が検知されるまでの間の任意の時刻から対策候補を実施した条件のシミュレーションにより算出される混雑指標値の改善の程度である改善度、例えば、その混雑指標値の最大値と閾値との差分を算出する。出力部180は、算出した差分を含む対策候補の評価結果を出力する。 Further, the measure plan evaluation unit 170 improves the congestion index value calculated by simulation of the condition in which the countermeasure candidate is implemented from any time between the current time and the detection of the required countermeasure congestion. The degree of improvement, for example, the difference between the maximum value of the congestion index value and the threshold value is calculated. The output unit 180 outputs a countermeasure candidate evaluation result including the calculated difference.
 これにより、対策候補を実施した場合の混雑指標値の最大値と閾値との差分を対策候補の評価に用いるので、対策候補を実施した場合に、混雑指標値が対策を要する状態からどの程度の余裕を持った状態に改善されうるかを評価することができる。 As a result, the difference between the maximum value of the congestion index value when the countermeasure candidate is implemented and the threshold value is used for evaluation of the countermeasure candidate. Therefore, when the countermeasure candidate is implemented, the degree of congestion index value from the state that requires countermeasures It can be evaluated whether it can be improved to a state with a margin.
 また、要対策混雑検知部130は複数の要対策混雑を検知でき、対策優先度評価部160は、複数の要対策混雑のそれぞれに評価結果を算出する。出力部180は、要対策混雑の評価結果に基づき順位を与えて要対策混雑を出力し、対策候補の評価結果に基づき順位を与えて対策候補を出力する。 Further, the countermeasure required congestion detection unit 130 can detect a plurality of countermeasure required congestions, and the countermeasure priority evaluation unit 160 calculates an evaluation result for each of the plurality of countermeasure required congestions. The output unit 180 outputs a countermeasure required congestion by giving a rank based on the evaluation result of the countermeasure required congestion, and outputs a countermeasure candidate by giving a rank based on the evaluation result of the countermeasure candidate.
 これにより、要対策混雑および対策候補を順位付けることができるので、複数の要対策混雑が発生し、複数の対策候補がある場合でも、どの要対策混雑を優先し、どのような対策を実施するかを判断するのが容易になる。 As a result, it is possible to rank countermeasure congestion and countermeasure candidates, so even if multiple countermeasure congestion occurs and there are multiple countermeasure candidates, which countermeasure congestion is prioritized and what countermeasures are implemented It becomes easy to judge.
 また、対策開始時刻算出部140は、要対策混雑に対して対策候補を実施した条件のシミュレーションにより算出される混雑指標値の最大値が閾値以下となるように遅くとも前記対策候補を実施すべき時刻である対策開始時刻を算出する。出力部180は、対策開始時刻を含む対策候補の評価結果を出力する。 In addition, the countermeasure start time calculation unit 140 should execute the countermeasure candidate at the latest so that the maximum value of the congestion index value calculated by the simulation of the condition in which the countermeasure candidate is implemented for countermeasure required congestion is less than or equal to the threshold value. The countermeasure start time is calculated. The output unit 180 outputs an evaluation result of countermeasure candidates including the countermeasure start time.
 これにより、対策候補の評価結果として対策開始時刻が提示されるので、どの対策候補を実施するかを決定するとき、いつまでに実施すればよいかという時間的余裕も考慮することができる。 This will present the countermeasure start time as the evaluation result of the countermeasure candidate, so when deciding which countermeasure candidate is to be implemented, it is possible to take into account the time allowance of when the countermeasure should be implemented.
 また、対策開始時刻算出部140は、対策候補を適用しないシミュレーションで算出される混雑指標値で描かれる第1の曲線が閾値を超える時間内において第1の曲線が最大値をとる時刻を第1の時刻とし、第1の時刻の以前に第1の曲線が極値をとる時刻を第2の時刻とし、第1の時刻から第2の時刻までの間に、現在時刻から要対策混雑が検知されるまでの間の任意の時刻から対策候補を適用した条件のシミュレーションで算出される混雑指標値で描かれる第2の曲線の最大値と最小値を通る第1の直線の傾きを算出し、その傾きを有し第1の時刻に閾値の値をとる第2の直線を算出し、第2の直線と前記第1の曲線の交点のうち第1の時刻以前に存在する交点の時刻を対策開始時刻とする。 Further, the countermeasure start time calculation unit 140 sets the first time when the first curve takes the maximum value within the time when the first curve drawn by the congestion index value calculated by the simulation not applying the countermeasure candidate exceeds the threshold. The time at which the first curve takes an extreme value before the first time is set as the second time, and the countermeasure required congestion is detected from the current time between the first time and the second time. Calculating the slope of the first straight line passing through the maximum value and the minimum value of the second curve drawn with the congestion index value calculated in the simulation of the condition applying the countermeasure candidate from an arbitrary time until A second straight line having the slope and taking a threshold value at the first time is calculated, and the time of the intersection existing before the first time among the intersections of the second straight line and the first curve is taken as a countermeasure. Start time.
 対策候補を適用しないシミュレーションの結果と対策候補を適用したシミュレーションの結果とを用いた近似的な演算で対策開始時刻を算出するので、対策開始時刻の算出による処理負荷を軽減することができる。 Since the countermeasure start time is calculated by an approximate calculation using the simulation result to which the countermeasure candidate is not applied and the simulation result to which the countermeasure candidate is applied, the processing load due to the calculation of the countermeasure start time can be reduced.
 また、出力部180は、複数の要対策混雑に、その要対策混雑のそれぞれに適用可能な少なくとも1つの対策候補の対策開始時刻に基づいて順位を与えて出力し、同じ要対策混雑に適用可能な複数の対策候補に、その対策候補のそれぞれの対策開始時刻に基づいて順位を与えて出力する。 In addition, the output unit 180 outputs a plurality of countermeasure congestions by giving an order based on the countermeasure start time of at least one countermeasure candidate applicable to each countermeasure congestion, and can be applied to the same countermeasure congestion A plurality of countermeasure candidates are given a rank based on the countermeasure start time of each countermeasure candidate and output.
 したがって、要対策混雑および対策候補の評価において、対策を実施するまでの時間的な余裕を考慮することができる。 Therefore, it is possible to consider the time allowance until countermeasures are taken into account in the congestion of countermeasures required and evaluation of candidate countermeasures.
 また、出力部180は、要対策混雑検知部130が検知した要対策混雑を順位付けして画面に表示し、いずれかの要対策混雑が選択されると、その要対策混雑に対応した対策候補を順位付けして画面に表示する。 Further, the output unit 180 ranks and displays the countermeasure required congestion detected by the countermeasure required congestion detection unit 130, and when one of the countermeasure required congestions is selected, a countermeasure candidate corresponding to the countermeasure required congestion is selected. Are displayed on the screen.
 したがって、鉄道駅の監視員などの操作者が画面表示の階層を辿ることで、対策を実施する要対策混雑およびその対策を容易に選択することができる。 Therefore, an operator such as a train station supervisor can follow the hierarchy of the screen display and can easily select the countermeasure congestion required to implement countermeasures and the countermeasures.
 また、出力部180は、実施する対策候補が選択されると、その対策候補の対策開始時刻を含む対策時間情報とその対策候補の実施を担当する対策要員の候補とを表示し、実施を担当する対策要員が選択されるとその対策要員の端末にその対策候補の実施指示を送信する。 Further, when a countermeasure candidate to be implemented is selected, the output unit 180 displays countermeasure time information including the countermeasure start time of the countermeasure candidate and candidate countermeasure personnel responsible for implementing the countermeasure candidate, and is in charge of implementation. When a countermeasure person to be selected is selected, an instruction to execute the candidate countermeasure is transmitted to the terminal of the countermeasure person.
 したがって、実施する対策の決定後にその対策を実施する要員の選択を支援するので、対策要員の決定が容易になる。 Therefore, since the selection of the personnel who implement the countermeasure after the determination of the countermeasure to be implemented is supported, the determination of the countermeasure personnel becomes easy.
 また、出力部180は、要対策混雑に関連する評価指標の遷移を、その混雑指標値の大小が識別可能なように、時間軸に沿って画面に表示する。要対策混雑に関連する評価指標として、例えば、混雑指標値、要対策混雑の順位(優先度)などがある。 In addition, the output unit 180 displays the transition of the evaluation index related to the countermeasure required congestion on the screen along the time axis so that the size of the congestion index value can be identified. As evaluation indexes related to countermeasure required congestion, for example, there are a congestion index value, a countermeasure required congestion rank (priority), and the like.
 したがって、混雑指標値の遷移が視覚的に分かりやすく画面に表示されるので、将来の混雑の状況を容易に把握することができる。 Therefore, since the transition of the congestion index value is displayed on the screen in a visually easy-to-understand manner, it is possible to easily grasp the future congestion situation.
 上述した本実施形態は、本発明の説明のための例示であり、本発明の範囲をそれらの実施形態にのみ限定する趣旨ではない。当業者は、本発明の要旨を逸脱することなしに、他の様々な態様で本発明を実施することができる。 The above-described embodiments are examples for explaining the present invention, and are not intended to limit the scope of the present invention only to those embodiments. Those skilled in the art can implement the present invention in various other modes without departing from the gist of the present invention.
111…予測人数情報データベース、112…空間情報データベース、113…対策候補データベース、120…シミュレーション部、130…要対策混雑検知部、140…対策開始時刻算出部、150…条件変更部、160…対策優先度評価部、170…対策案評価部、180…出力部、200…空間情報、210…予測人数情報、220…空間情報、230…部分空間情報、240…混雑予測結果、250…対策候補、270…要対策混雑情報、280…対策案、290…対策優先度評価結果、300…対策案評価結果、310…対策優先度評価結果表示画面、311…表示、320…対策案評価結果表示画面、321…レコード、330…担当者設定画面、331…時間帯、340…対策案実施内容指示画面 DESCRIPTION OF SYMBOLS 111 ... Predicted number information database, 112 ... Spatial information database, 113 ... Countermeasure candidate database, 120 ... Simulation part, 130 ... Countermeasure congestion detection part, 140 ... Countermeasure start time calculation part, 150 ... Condition change part, 160 ... Countermeasure priority Degree evaluation unit, 170 ... Countermeasure plan evaluation unit, 180 ... Output unit, 200 ... Spatial information, 210 ... Predicted number information, 220 ... Spatial information, 230 ... Partial spatial information, 240 ... Congestion prediction result, 250 ... Countermeasure candidate, 270 ... Countermeasure congestion information, 280 ... Countermeasure plan, 290 ... Countermeasure priority evaluation result, 300 ... Countermeasure plan evaluation result, 310 ... Countermeasure priority evaluation result display screen, 311 ... Display, 320 ... Countermeasure plan evaluation result display screen, 321 ... Record, 330 ... Person in charge setting screen, 331 ... Time zone, 340 ... Countermeasure plan implementation content instruction screen

Claims (10)

  1.  所定の空間の混雑に対して実施可能な対策候補の情報を格納した対策候補データベースと、
     所定の空間について将来の時間における混雑指標値の遷移を算出するシミュレーション部と、
     前記混雑指標値が所定の閾値を超える場合、対策を要する混雑であり空間および時間で特定される要対策混雑を検知する要対策混雑検知部と、
     前記要対策混雑が検知された空間に適用可能な対策候補を適用した条件のシミュレーションで算出される混雑指標値が前記閾値を超えるか否かを含む前記対策候補の評価結果を出力する出力部と、
    を有する混雑予測システム。
    A countermeasure candidate database storing information of countermeasure candidates that can be implemented for congestion in a predetermined space;
    A simulation unit for calculating a transition of a congestion index value at a future time for a predetermined space;
    When the congestion index value exceeds a predetermined threshold, a countermeasure-necessary congestion detection unit that detects the countermeasure-necessary congestion that is a congestion requiring countermeasures and specified by space and time;
    An output unit for outputting an evaluation result of the countermeasure candidate including whether or not a congestion index value calculated by a simulation of a condition applying a countermeasure candidate applicable to the space in which the countermeasure congestion is detected exceeds the threshold; ,
    Congestion prediction system.
  2.  前記要対策混雑に現在時刻から前記要対策混雑が検知されるまでの間の任意の時刻から前記対策候補を実施した条件のシミュレーションにより算出される混雑指標値の改善の程度である改善度を算出する対策案評価部を更に有し、
     前記出力部は、前記改善度を含む、前記対策候補の評価結果を出力する、
    請求項1に記載の混雑予測システム。
    The degree of improvement, which is the degree of improvement of the congestion index value calculated by simulation of the conditions under which the countermeasure candidates are implemented, is calculated from any time between the current countermeasure time and the time when the countermeasure countermeasure congestion is detected. And a countermeasure plan evaluation section
    The output unit outputs an evaluation result of the countermeasure candidate including the degree of improvement.
    The congestion prediction system according to claim 1.
  3.  前記要対策混雑検知部は複数の前記要対策混雑を検知でき、
     前記複数の要対策混雑のそれぞれに評価結果を算出する対策優先度評価部を更に有し、
     前記出力部は、前記要対策混雑の評価結果に基づき順位を与えて前記要対策混雑を出力し、前記対策候補の評価結果に基づき順位を与えて前記対策候補を出力する、
    請求項2に記載の混雑予測システム。
    The countermeasure countermeasure congestion detection unit can detect a plurality of countermeasure countermeasure congestions,
    A countermeasure priority evaluation unit for calculating an evaluation result for each of the plurality of countermeasure congestions;
    The output unit gives a rank based on the evaluation result of the countermeasure required congestion and outputs the countermeasure required congestion, gives a rank based on the evaluation result of the countermeasure candidate, and outputs the countermeasure candidate.
    The congestion prediction system according to claim 2.
  4.  前記要対策混雑に対して前記対策候補を実施した条件のシミュレーションにより算出される混雑指標値の最大値が前記閾値以下となるように遅くとも前記対策候補を実施すべき時刻である対策開始時刻を算出する対策開始時刻算出部を更に有し、
     前記出力部は、前記対策開始時刻を含む前記対策候補の評価結果を出力する、
    請求項1に記載の混雑予測システム。
    Calculate the countermeasure start time that is the time at which the countermeasure candidate should be implemented at the latest so that the maximum value of the congestion index value calculated by simulation of the conditions for implementing the countermeasure candidate for the countermeasure congestion required is equal to or less than the threshold. A countermeasure start time calculation unit
    The output unit outputs an evaluation result of the countermeasure candidate including the countermeasure start time;
    The congestion prediction system according to claim 1.
  5.  前記対策開始時刻算出部は、対策候補を適用しないシミュレーションで算出される前記混雑指標値で描かれる第1の曲線が前記閾値を超える時間内において前記第1の曲線が最大値をとる時刻を第1の時刻とし、前記第1の時刻の以前に前記第1の曲線が極値をとる時刻を第2の時刻とし、前記第1の時刻から前記第2の時刻までの間に、現在時刻から前記要対策混雑が検知されるまでの間の任意の時刻から前記対策候補を適用した条件のシミュレーションで算出される混雑指標値で描かれる第2の曲線の最大値と最小値を通る第1の直線の傾きを算出し、前記傾きを有し前記第1の時刻に前記閾値の値をとる第2の直線を算出し、前記第2の直線と前記第1の曲線の交点のうち前記第1の時刻以前に存在する交点の時刻を前記対策開始時刻とする、請求項4に記載の混雑予測システム。 The countermeasure start time calculation unit sets a time at which the first curve takes the maximum value within a time when the first curve drawn by the congestion index value calculated by the simulation not applying the countermeasure candidate exceeds the threshold. 1 time, the time when the first curve takes an extreme value before the first time is set as the second time, and from the current time to the second time from the first time to the second time The first that passes through the maximum value and the minimum value of the second curve drawn by the congestion index value calculated by the simulation of the condition applying the countermeasure candidate from any time until the countermeasure congestion is detected. A slope of the straight line is calculated, a second straight line having the slope and taking the threshold value at the first time is calculated, and the first of the intersections of the second straight line and the first curve is calculated. The time of the intersection existing before the time of That, congestion prediction system according to claim 4.
  6.  前記出力部は、複数の要対策混雑に、該要対策混雑のそれぞれに適用可能な少なくとも1つの対策候補の対策開始時刻に基づいて順位を与えて出力し、同じ要対策混雑に適用可能な複数の対策候補に、該対策候補のそれぞれの対策開始時刻に基づいて順位を与えて出力する、
    請求項3に記載の混雑予測システム。
    The output unit outputs a plurality of countermeasure required congestions by giving an order based on the countermeasure start time of at least one countermeasure candidate applicable to each of the countermeasure required congestions, and can be applied to the same countermeasure required congestions. To each of the countermeasure candidates, the rank is given based on the countermeasure start time of each countermeasure candidate, and the result is output.
    The congestion prediction system according to claim 3.
  7.  前記出力部は、前記要対策混雑検知部が検知した要対策混雑を順位付けして画面に表示し、いずれかの要対策混雑が選択されると、該要対策混雑に対応した対策候補を順位付けして画面に表示する、請求項3に記載の混雑予測システム。 The output unit ranks and displays the countermeasure required congestion detected by the countermeasure required congestion detection unit, and when any countermeasure required congestion is selected, the countermeasure candidates corresponding to the countermeasure required congestion are ranked. The congestion prediction system according to claim 3, wherein the congestion prediction system is attached and displayed on a screen.
  8.  前記出力部は、実施する対策候補が選択されると、該対策候補の対策開始時刻を含む対策時間情報と該対策候補の実施を担当する対策要員の候補とを表示し、実施を担当する対策要員が選択されると該対策要員の端末に該対策候補の実施指示を送信する、請求項1に記載の混雑予測システム。 When the countermeasure candidate to be implemented is selected, the output unit displays countermeasure time information including the countermeasure start time of the countermeasure candidate and candidate countermeasure personnel responsible for implementing the countermeasure candidate, and the countermeasure responsible for the implementation. The congestion prediction system according to claim 1, wherein when a person is selected, an instruction to execute the countermeasure candidate is transmitted to the terminal of the countermeasure person.
  9.  前記出力部は、前記要対策混雑に関連する評価指標の遷移を、該混雑指標値の大小が識別可能なように、時間軸に沿って画面に表示する、請求項1に記載の混雑予測システム。 The congestion prediction system according to claim 1, wherein the output unit displays a transition of an evaluation index related to the countermeasure required congestion on a screen along a time axis so that the magnitude of the congestion index value can be identified. .
  10.  シミュレーション手段が、所定の空間について将来の時間における混雑指標値の遷移を算出し、
     要対策混雑検知手段が、前記混雑指標値が所定の閾値を超える場合、対策を要する混雑であり空間および時間で特定される要対策混雑を検知し、
     前記シミュレーション手段が、前記要対策混雑が検知された空間に適用可能な対策候補を適用した条件の混雑指標値の遷移を算出し、
     出力手段が,前記要対策混雑が検知された空間に適用可能な対策候補を適用した条件のシミュレーションで算出された混雑指標値が前記閾値を超えるか否かを含む前記対策候補の評価結果を出力する、
    混雑予測方法。
    The simulation means calculates the transition of the congestion index value at a future time for a predetermined space,
    When the congestion measure detecting means requires the congestion index value to exceed a predetermined threshold, it detects congestion that requires countermeasures and is required congestion that is specified by space and time,
    The simulation means calculates a transition of a congestion index value of a condition applying a countermeasure candidate applicable to the space where the countermeasure required congestion is detected,
    The output means outputs the evaluation result of the countermeasure candidate including whether or not the congestion index value calculated by the simulation of the condition applying the countermeasure candidate applicable to the space where the countermeasure required congestion is detected exceeds the threshold. To
    Congestion prediction method.
PCT/JP2016/059093 2015-09-29 2016-03-23 Congestion predicting system and congestion predicting method WO2017056528A1 (en)

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