EP3437955B1 - Train disembarking passenger number prediction system, congestion visualization and evaluation system, and riding capacity calculation system - Google Patents

Train disembarking passenger number prediction system, congestion visualization and evaluation system, and riding capacity calculation system Download PDF

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Publication number
EP3437955B1
EP3437955B1 EP17773617.0A EP17773617A EP3437955B1 EP 3437955 B1 EP3437955 B1 EP 3437955B1 EP 17773617 A EP17773617 A EP 17773617A EP 3437955 B1 EP3437955 B1 EP 3437955B1
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Prior art keywords
train
alighting
person count
count
interval
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German (de)
English (en)
French (fr)
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EP3437955A1 (en
EP3437955A4 (en
Inventor
Rui NING
Manabu Katou
Masayasu Fujiwara
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Hitachi Ltd
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Hitachi Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/60—Testing or simulation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/10—Operations, e.g. scheduling or time tables
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/40—Handling position reports or trackside vehicle data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION 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
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry

Definitions

  • the present invention relates to a system that provides visualization and prediction information on a congestion situation.
  • PTL 1 discloses a vehicle congestion rate prediction system that includes a counting device, which receives data including alighting stations read by an automatic ticket checker from tickets passing through the automatic ticket checker on an entrance side of each station and counts the number of persons alighting at each alighting station; and means for predicting a vehicle on which a user passing through the automatic ticket checker rides by referring to a storage device, which stores statistical data in which an alighting station of a ticket is associated with each ride ratio of users, who have tickets designating the alighting station, riding on each vehicle, and calculating the number of persons riding on each vehicle and the number of persons alighting from each vehicle based on the prediction.
  • An object of the present invention is to make it possible to predict the number of alighting persons from a train using information that can be acquired at a single station.
  • a train alighting person count prediction system according to claim 1 is provided.
  • FIG. 1 is a diagram illustrating an example of a configuration of a train alighting person count prediction device of the present invention.
  • the train alighting person count prediction device is a device that timely predicts the number of persons alighting from a train at a railway station, and includes a measurement unit 100, an arithmetic unit 200, a recording unit 300, and an output unit 400.
  • the measurement unit 100, the arithmetic unit 200, the recording unit 300, and the output unit 400 can communicate with each other and operate on one or a plurality of interconnected computers.
  • the measurement unit 100 includes a person count measurement unit 101 that measures a passer-by count inside a station and a train departure/arrival detection unit 102 that detects departure and arrival of a train in the station.
  • the arithmetic unit 200 includes: an alighting person count calculation unit 201 that estimates a past train alighting person count; a train interval calculation unit 202 that calculates an interval between arrival times of a target train and a train which has arrived immediately previously on the same track; a prediction model creation unit 203 that creates a prediction model of a train alighting person count based on statistical information on a train interval and a alighting person count of the past; and an alighting person count prediction unit 204 that predicts a train alighting person count with an input of a train interval of a train at the time of arrival of the train.
  • the recording unit 300 is a database that holds, as data, person count measurement information 301 which is a detection result of the passer-by count, departure/arrival time information 302 which is departure/arrival time of a train, alighting person count information 303 which is an estimated value of an alighting person count for each train, train interval information 304 which is an arrival interval for each train, and prediction model information 305 which is a prediction model for predicting a train alighting person count based on a train interval.
  • the output unit 400 outputs a result of prediction of the train alighting person count.
  • the person count measurement unit 101 is a sensor device capable of measuring a local passer-by count in the station for each direction of movement, and outputs the passer-by count as the person count measurement information 301 for each time zone and direction.
  • the person count measurement unit 101 is realized, for example, by using a surveillance camera installed in the station as a sensor and measuring the number of persons by image processing.
  • the sensors are installed in stairs, escalators and the like connecting a platform and a ticket gate floor in order to estimate the past train alighting person count.
  • the sensors are installed at the positions of a camera 701 and a camera 702 in FIG. 2 to measure each passer-by count at points 711 and 712.
  • the train departure/arrival detection unit 102 is a sensor device capable of detecting departure and arrival of a train, and detects arrival or departure of a train, records the time thereof, and outputs a result of the detection as the departure/arrival time information 302.
  • the train departure/arrival detection unit 102 is realized, for example, by using a surveillance camera installed on the platform such as the camera 703 in FIG. 2 as a sensor and detecting departure and arrival of a train by image processing.
  • the alighting person count calculation unit 201 receives inputs of the past person count measurement information 301 and the past departure/arrival time information 302 and allocate the measured passer-by count to trains to estimate the number of persons alighting from each train, and outputs the estimated count as the alighting person count information 303.
  • the train interval calculation unit 202 calculates an arrival interval time of a train arriving at the same track and outputs the calculated time as the train interval information 304.
  • the prediction model creation unit 203 Based on data obtained by associating the past alighting person count information 303 with the past train interval information 304, the prediction model creation unit 203 creates a model for predicting the train alighting person count based on the train interval and outputs the created model as the prediction model information 305.
  • the alighting person count prediction unit 204 predicts the number of persons alighting from the train using the prediction model information 305 with the train interval output by the train interval calculation unit 202 as an input, and outputs the predicted count.
  • the person count measurement information 301 is data obtained by recording the measurement result of the person count measurement unit 101, is data constituted by a position ID which specifies a sensor installation position, a measured date, measurement start time and end time, a direction ID which specifies a movement direction of a pedestrian to be measured, and the number of measured persons as illustrated in FIG. 3 , and is held as a database in the recording unit 300.
  • the departure/arrival time information 302 is data obtained by recording the detection result of the train departure/arrival detection unit, is data constituted by a track ID which specifies an arrival track of a target train, a date and time when detecting the train, and a type for distinguishing whether the detected train is of arrival or departure as illustrated in FIG. 4 , and is held as a database in the recording unit 300.
  • the alighting person count information 303 is data obtained by recording the alighting person count for each train, is data constituted by a date when detecting a train, a track ID, an arrival time, and the alighting person count as illustrated in the drawing, and is held as a database in the recording unit 300.
  • the date, the track ID, and the arrival time are information configured to uniquely specify a train, and data in which a train ID is associated with an alighting person count by attaching the train ID for each train may be used.
  • the train interval information 304 is data obtained by recording the train interval with an immediately previous train for each train, is data constituted by a date when detecting a train, a track ID, an arrival time, and a train interval as illustrated in FIG. 6 , and is held as a database in the recording unit 300.
  • the date, the track ID, and the arrival time are information configured to uniquely specify a train, and data in which a train ID is associated with an alighting person count by attaching the train ID for each train may be used.
  • the prediction model information 305 is data obtained by recording the model for predicting the train alighting person count from the train interval and is constituted by a time zone, an attribute, a track ID and a model formula as illustrated in FIG. 7 .
  • the prediction model is recorded as the model formula, but the model is not limited to the formula.
  • the model may be held in the form of a table in which a delay time and an alighting person count are associated for each condition.
  • the processing of the train alighting person count prediction device can be divided into a database creation process and an alighting person count prediction process.
  • Step 4001 will be denoted as S4001.
  • S4001 A passer-by count at a predetermined position in the station is measured using the person count measurement unit 101, and a measurement result is saved as the person count measurement information 301 in the recording unit 300, thereby creating the database of the person count measurement information 301.
  • S4002 A departure or arrival time of a train departing or arriving at the station is detected using the train departure/arrival detection unit 102, and the detection result is saved as the departure/arrival time information 302 in the recording unit 300, thereby creating the database of the departure/arrival time information 302.
  • the passer-by count recorded in the person count measurement information 301 is divided by the train arrival time recorded in the departure/arrival time information 302, a passer-by count from an arrival time of each train to an arrival time of a train arriving subsequently to the corresponding train is allocated to the train to calculate the number of persons alighting from the train in the alighting person count calculation unit 201, and the calculated count is saved as the alighting person count information 303 in the recording unit 300, thereby creating the database of the alighting person count information 303.
  • the train interval calculation unit 202 calculates an interval with respect to an arrival time of a train which has immediately previously arrived on the same track as the train from the departure/arrival time information 302, which has been recorded in the recording unit 300, as a train interval and is saved the train interval information 304 in the recording unit 300, thereby creating a train interval information database.
  • the prediction model creation unit 203 associates the alighting person count information 303 recorded in the recording unit 300 with the train interval information 304 to be classified for each condition such as the track, the time zone, and the like, then a relational expression between a train interval and an alighting person count is calculated for each condition and saved as the prediction model information 305 in the recording unit 300, thereby creating a prediction model information database.
  • the database is updated by repeating the above-described process timely or periodically in accordance with a measurement result of the measurement unit 100. "Periodically” refers to updating, for example, on a daily basis.
  • the train interval calculation unit 202 calculates an arrival interval between the train and a train which has immediately previously arrived on the same track based on the departure/arrival time information 302.
  • the alighting person count prediction unit 204 acquires the prediction model information 305 conforming to a condition at the time of arrival of the train from the recording unit 300, and inputs the train interval to the prediction model to calculate a predicted value of the alighting person count under the condition.
  • the output unit 400 outputs the predicted value of the alighting person count.
  • the predicted value of the alighting person count is output to a known pedestrian simulator device capable of estimating a congestion situation of a predetermined space by simulating movement of pedestrians with the number of pedestrians as an input and visualizing and evaluating the congestion situation, thereby realizing visualization and prediction of the congestion situation in the station.
  • the measurement unit 100, the recording unit 300, and the output unit 400 are realized using a known sensing technique, a known database technique, and a known data transfer technique, respectively, and thus, the description of the processing flows thereof will be omitted.
  • Symbols 1001 to 1006 represent passer-by counts in the respective time zones by extracting the number of passers-by of target track and direction from the person count measurement information 301.
  • Symbols 1011 and 1012 are train arrival times of the target track extracted from the departure/arrival time information 302. As illustrated in FIG. 10 , the alighting person count calculation unit 201 divides the passer-by count by the train arrival time and allocates the passer-by count to the immediately previous train, thereby calculating the number of persons alighting from the immediately previous train.
  • the symbols 1001 to 1003 are the number of persons who has passed by stairs on the platform toward a ticket gate floor between arrival of a train 1011 until arrival of a train 1012, and can be estimated as the number of persons alighting from the train 1011.
  • FIG. 13 is a scatter diagram in which the horizontal axis represents a train interval and the vertical axis represents a train alighting person count.
  • Each of ranges 1101 to 1103 represents dispersion of data distinguished by an attribute, a track, a time zone, and the like.
  • Each of curves 1111 to 1113 is a relational expression of a train interval and a train alighting person count corresponding to the data of the ranges 1101 to 1103.
  • the relational expression is calculated by regression analysis using the train interval as an explanatory variable and the train alighting person count as an objective variable.
  • the prediction model creation unit 203 creates a relational expression for each condition as a prediction model and outputs the created model as the prediction model information 305.
  • S5201 The train interval information 304 and the alighting person count information 303 are associated depending on the date, the track ID, and the arrival time.
  • S5202 The associated data is classified and distinguished in accordance with the condition such as the date, the track ID, the time zone of the arrival time, and the like.
  • a relational expression between a train interval and a train alighting person count is calculated for data of each condition and set as a model formula.
  • the relational expression is calculated by regression analysis using the train interval as an explanatory variable and the train alighting person count as an objective variable.
  • the model formula is output as the prediction model information 305 and saved in the recording unit 300.
  • a method for creating the prediction model in the prediction model creation unit 203 is not limited to the above-described one.
  • the model formula may be created using a relational expression between a delay time and a train alighting person count using each mode or average value of train intervals and train alighting person counts aggregated for each condition as standard train interval and train alighting person count under the condition and using a difference between the input train interval and the standard train interval as the delay time.
  • the model formula may be created using a relational expression between a delay rate, which is a ratio of the delay time relative to a standard delay time, and an alighting person count change rate which is a ratio of the train alighting person count relative to the standard train alighting person count as illustrated in FIG. 15 With such normalization as the ratios, it is not always necessary to create the model formula for every condition (time zone). In addition, it is possible to use a model formula of a station for another station where statistical information is not sufficient.
  • the processing of the alighting person count prediction unit 204 is changed depending on a method of creating a prediction model. For example, when a prediction model is created using a relational expression between a delay rate and a train alighting person count increase rate, the delay rate is calculated from a train interval, a change rate of a train alighting person count is calculated using the relational expression, and the change rate of the train alighting person count and a standard train alighting person count are multiplied to obtain the train alighting person count.
  • the train alighting person count prediction device of the present embodiment it is possible to calculate the train interval from the train arrival time at a stage of detecting the arrival of the train using only the information obtained from the single station and statistically predict the number of persons alighting from the train which has arrived based on the train interval.
  • timely refers to an arrival stage of a train before the alighting customers actually starts alighting.

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EP17773617.0A 2016-03-30 2017-01-31 Train disembarking passenger number prediction system, congestion visualization and evaluation system, and riding capacity calculation system Active EP3437955B1 (en)

Applications Claiming Priority (2)

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JP2016067041 2016-03-30
PCT/JP2017/003257 WO2017169068A1 (ja) 2016-03-30 2017-01-31 列車降車人数予測システム、混雑可視化・評価システム、および乗車可能人数算出システム

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JP6636075B2 (ja) * 2018-03-26 2020-01-29 株式会社エヌ・ティ・ティ・データ 乗客重量均一化支援装置、及び乗客重量均一化支援方法
CN110636210B (zh) * 2019-05-17 2020-07-28 乐清海创智能科技有限公司 无线信号触发方法
GB2585028A (en) * 2019-06-25 2020-12-30 Siemens Mobility Ltd A method and system for deriving train travel information
CN111762238B (zh) * 2020-07-03 2022-03-11 山东交通职业学院 一种列车间隔调整系统及其调整方法
EP4166417A4 (en) 2020-07-13 2023-07-26 Mitsubishi Electric Corporation GUIDANCE SYSTEM AND GUIDANCE METHOD
CN112381260B (zh) * 2020-09-03 2023-11-17 北京交通大学 基于进站比例的城市轨道交通客流管控优化方法
US20230087643A1 (en) * 2021-09-17 2023-03-23 Korea Railroad Research Institute Method and apparatus for determining coupling section in real-time for train platooning
CN115472018B (zh) * 2022-10-28 2023-12-29 广州地铁集团有限公司 一种基于行车分析及客流预测的城轨仿真推演方法

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JPS58180375A (ja) * 1982-04-16 1983-10-21 株式会社日立製作所 列車群制御方式
JP2002037076A (ja) * 2000-07-27 2002-02-06 Kawasaki Heavy Ind Ltd 列車運行模擬方法および装置
JP2004178358A (ja) * 2002-11-28 2004-06-24 Meidensha Corp イベント警備監視方法及びイベント警備監視装置
JP4399283B2 (ja) * 2004-01-30 2010-01-13 三菱電機株式会社 駅混雑度推定システム
JP5518213B2 (ja) * 2010-12-20 2014-06-11 三菱電機株式会社 車両内混雑状況表示システムおよび混雑状況案内方法
JP5969957B2 (ja) * 2013-06-27 2016-08-17 株式会社日立製作所 列車混雑度予測システム、及び列車混雑度予測方法
JP6178226B2 (ja) * 2013-12-04 2017-08-09 株式会社日立製作所 人流誘導システム及び人流誘導方法
JP6393531B2 (ja) * 2014-06-24 2018-09-19 株式会社日立製作所 列車選択支援システム、列車選択支援方法、及び列車選択支援プログラム

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Title
None *

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JP6640988B2 (ja) 2020-02-05
EP3437955A1 (en) 2019-02-06
EP3437955A4 (en) 2020-01-29
WO2017169068A1 (ja) 2017-10-05

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