JP2015229459A - Program and simulation device - Google Patents

Program and simulation device Download PDF

Info

Publication number
JP2015229459A
JP2015229459A JP2014117566A JP2014117566A JP2015229459A JP 2015229459 A JP2015229459 A JP 2015229459A JP 2014117566 A JP2014117566 A JP 2014117566A JP 2014117566 A JP2014117566 A JP 2014117566A JP 2015229459 A JP2015229459 A JP 2015229459A
Authority
JP
Japan
Prior art keywords
passenger
train
passengers
seating
boarding
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
JP2014117566A
Other languages
Japanese (ja)
Other versions
JP6231946B2 (en
Inventor
武俊 國松
Taketoshi Kunimatsu
武俊 國松
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Railway Technical Research Institute
Original Assignee
Railway Technical Research Institute
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Railway Technical Research Institute filed Critical Railway Technical Research Institute
Priority to JP2014117566A priority Critical patent/JP6231946B2/en
Publication of JP2015229459A publication Critical patent/JP2015229459A/en
Application granted granted Critical
Publication of JP6231946B2 publication Critical patent/JP6231946B2/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Train Traffic Observation, Control, And Security (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

PROBLEM TO BE SOLVED: To achieve passenger flow simulation considering a possibility of seating in a train.SOLUTION: A simulation device 1 is configured so that: in a route search network used for search of a train connecting route of a passenger, an arriving/departure node is classified to a seating/standing boarding of the passenger. In addition, cost of a seating arc is changed according to a corresponding seating probability, and an arc between stations is changed according to a congestion rate between corresponding stations for each seating/standing boarding. In addition, in getting on and off control of the train, first, the passenger who is standing is allowed to seat on a vacant seat which becomes vacant because of getting off of the passenger who seated. Then, according to stand-by time at a station (stay time), a passenger who stays is classified to a priority/general staying passenger, and the passenger who stays is allowed to get on the train so that, the priority staying passenger can seat on the train in priority.

Description

本発明は、旅客流動シミュレーションをコンピュータに実行させるためのプログラム等に関する。   The present invention relates to a program for causing a computer to execute passenger flow simulation.

列車ダイヤの評価や検証のために、列車ダイヤに対する旅客流動シミュレーションが行われている。コンピュータを用いた旅客流動シミュレーションとして、例えば、特許文献１には、シミュレーション時刻を時々刻々と進めながら、各駅における旅客の出現制御や乗降制御、旅客の乗降に伴う遅延制御を含む列車の運行制御、旅客の列車乗継経路の再探索、といった処理を繰り返し行う手法が開示されている。係る手法では、旅客の乗降による列車運行の遅延や、この列車運行の遅延に伴って旅客の列車乗継経路が動的に変化する状況が模擬された、精度の良いシミュレーションが実現されている。   In order to evaluate and verify train schedules, passenger flow simulations for train schedules are performed. As a passenger flow simulation using a computer, for example, Patent Document 1 discloses a train operation control including a passenger appearance control and a boarding / alighting control at each station, a delay control associated with a passenger boarding / exiting, with the simulation time being advanced every moment. A method of repeatedly performing processing such as re-searching for a passenger transit route is disclosed. In such a technique, a highly accurate simulation is realized in which a train operation delay due to passenger getting on and off and a situation in which a passenger's train connection route dynamically changes in accordance with this train operation delay are simulated.

特開２００８−６２７２９号公報JP 2008-62729 A

旅客流動シミュレーションでは、各旅客に出現駅（出発駅）から目的駅に至る列車乗継経路を設定する。出現駅から目的駅に至る経路には多数あるが、これらの多数の経路のうちから選択条件を満たす１つの経路が選択され、列車乗継経路として設定される。このような旅客の列車乗継経路の選択条件として、例えば、上述の特許文献１には、最も早く目的駅に到着できることや、乗り換えが少ないこと、といった条件が開示されている。   In the passenger flow simulation, a train connection route from an appearing station (departure station) to a destination station is set for each passenger. Although there are many routes from the appearance station to the destination station, one route satisfying the selection condition is selected from these many routes and set as a train connection route. As a selection condition for such a passenger's train connection route, for example, the above-mentioned Patent Document 1 discloses a condition that the train station can arrive at the destination station the earliest, and that there are few transfers.

ところで、旅客にとって、着席できるかどうは、乗車行動において重要な要素の一つである。例えば、快速をやり過ごして後続の各駅停車を選択するといったような行動である。しかしながら、これまでは、このような列車の着席可能性を考慮した旅客流動シミュレーションは行われていなかった。   By the way, whether passengers can sit down is one of the important factors in boarding behavior. For example, it is an action such as passing through the high speed and selecting each subsequent station stop. However, until now, passenger flow simulations that considered the possibility of seating on such trains have not been performed.

本発明は、上記事情に鑑みてなされたものであり、その目的とするところは、列車の着席可能性を考慮した旅客流動シミュレーションを実現することである。   The present invention has been made in view of the above circumstances, and an object thereof is to realize a passenger flow simulation in consideration of the possibility of seating on a train.

上記課題を解決するための第１の発明は、
シミュレーション時刻を時々刻々と計時し、出現駅と目的駅とが定められた仮想旅客の当該出現駅への出現制御、前記出現駅から前記目的駅までの乗車列車を特定した所与の列車乗継経路に沿って前記仮想旅客を乗降させる乗降制御、前記仮想旅客の乗降人数に応じた遅延制御を含む所与の列車ダイヤに沿った列車の運行制御、を含む旅客流動シミュレーションをコンピュータに実行させるためのプログラムであって、
前記仮想旅客それぞれについて、乗車中の列車の識別情報、及び、当該乗車の着席／立席の区別を少なくとも含む状況情報を管理する個別旅客状況管理手段、
予め定められた座席数と前記状況情報とを用いて各列車の着席可能性を算出する着席可能性算出手段、
着席乗車と立席乗車それぞれに対応づけられた重み付けと、前記着席可能性とを用いて、前記列車乗継経路の再探索を実行する再探索実行手段、
着席乗客（着席乗車の仮想旅客のこと。以下同じ）が前記乗降制御によって降車した場合に、降車した当該着席乗客の数に応じた数の当該列車の立席乗客（立席乗車の仮想旅客のこと。以下同じ）を着席に変更する継続乗車着席制御手段、
滞留旅客（駅に滞留していた仮想旅客のこと。以下同じ）が前記乗降制御によって乗車した場合に、乗車した当該滞留旅客を、前記継続乗車着席制御手段による変更制御後の当該列車の空席数を用いて、着席及び立席の何れかとする乗車時制御手段、
として前記コンピュータを機能させるためのプログラムである。 The first invention for solving the above-described problems is
Controls the appearance of a virtual passenger whose appearance time and destination station are determined, and the train transfer from the appearance station to the destination station. To cause a computer to execute passenger flow simulation including boarding / alighting control for getting on and off the virtual passenger along a route and train operation control along a given train schedule including delay control according to the number of passengers getting on and off the virtual passenger The program of
For each of the virtual passengers, individual passenger status management means for managing the status information including at least the identification information of the train being boarded and the seating / standing position of the boarding,
Seating possibility calculating means for calculating the seating possibility of each train using a predetermined number of seats and the situation information;
Re-search execution means for re-searching the train connection route using the weighting associated with each of the seated boarding and the standing boarding and the seating possibility;
When seated passengers (referred to as virtual passengers of seated passengers; the same shall apply hereinafter) get off by the above-mentioned boarding / alighting control, the number of seated passengers (the number of virtual passengers of seated passengers) corresponding to the number of seated passengers that have exited The same applies to the following)
When a staying passenger (a virtual passenger staying at a station; the same applies hereinafter) gets on the boarding / alighting control, the number of seats in the train after the staying passenger seating control means changes the staying passenger A boarding time control means to be either seated or standing, using
As a program for causing the computer to function.

また、他の発明として、
シミュレーション時刻を時々刻々と計時し、出現駅と目的駅とが定められた仮想旅客の当該出現駅への出現制御、前記出現駅から前記目的駅までの乗車列車を特定した所与の列車乗継経路に沿って前記仮想旅客を乗降させる乗降制御、前記仮想旅客の乗降人数に応じた遅延制御を含む所与の列車ダイヤに沿った列車の運行制御、を含む旅客流動シミュレーションを実行するシミュレーション装置であって、
前記仮想旅客それぞれについて、乗車中の列車の識別情報、及び、当該乗車の着席／立席の区別を少なくとも含む状況情報を管理する個別旅客状況管理手段と、
予め定められた座席数と前記状況情報とを用いて各列車の着席可能性を算出する着席可能性算出手段と、
着席乗車と立席乗車それぞれに対応づけられた重み付けと、前記着席可能性とを用いて、前記列車乗継経路の再探索を実行する再探索実行手段と、
着席乗客が前記乗降制御によって降車した場合に、降車した当該着席乗客の数に応じた数の当該列車の立席乗客を着席に変更する継続乗車着席制御手段と、
滞留旅客が前記乗降制御によって乗車した場合に、乗車した当該滞留旅客を、前記継続乗車着席制御手段による変更制御後の当該列車の空席数を用いて、着席及び立席の何れかとする乗車時制御手段と、
を備えたシミュレーション装置を構成しても良い。 As another invention,
Controls the appearance of a virtual passenger whose appearance time and destination station are determined, and the train transfer from the appearance station to the destination station. A simulation device for executing passenger flow simulation including boarding / alighting control for getting on and off the virtual passenger along a route and train operation control along a given train schedule including delay control according to the number of passengers getting on and off the virtual passenger There,
For each of the virtual passengers, individual passenger status management means for managing the identification information of the train being boarded and the status information including at least the distinction between seating / standing of the boarding,
Seating possibility calculating means for calculating the seating possibility of each train using a predetermined number of seats and the situation information;
Re-search execution means for re-searching the train connection route using the weighting associated with each of the seated boarding and the standing boarding and the seating possibility;
When a seated passenger gets off by the boarding / alighting control, the continuous boarding seating control means for changing the number of standing passengers of the train corresponding to the number of the seated passengers to the seated seats,
When a staying passenger gets on the boarding / alighting control, the boarding time control that makes the staying passenger either seated or standing using the number of seats of the train after the change control by the continuous boarding seating control means Means,
You may comprise the simulation apparatus provided with.

この第１の発明等によれば、列車の着席可能性を考慮した旅客流動シミュレーションが可能となる。すなわち、着席乗客が降車した場合に、降車した着席乗客数に応じた数の立席乗客を着席に変更したり、滞留旅客が乗車した場合に、乗車した滞留旅客を空席数に応じて着席／立席の何れかとすることで、列車の乗客を着席／立席に区別して管理する。また、着席乗車と立席乗車それぞれに対応付けた重み付けと、列車の着席可能性とを用いて、旅客の列車乗継経路を再探索する。これにより、着席／立席の何れになるかによって列車乗継経路が変化し得る様子を模擬することが可能となる。   According to the first aspect of the invention, a passenger flow simulation considering the seating possibility of a train is possible. In other words, when a seated passenger gets off, the number of standing passengers corresponding to the number of seated passengers who have alighted is changed to seated, or when a stagnant passenger gets on the board, By using one of the standing seats, the passengers of the train are managed separately from the seated / standing seats. Further, the train connection route of the passenger is re-searched using the weighting associated with each of the seated boarding and the standing boarding and the seating possibility of the train. This makes it possible to simulate a situation in which the train connection route can change depending on whether the user is seated or standing.

また、第２の発明として、第１の発明のプログラムであって、
前記再探索実行手段は、列車の着発の度に前記再探索を実行する、
プログラムを構成しても良い。 As a second invention, there is provided a program according to the first invention,
The re-search execution means executes the re-search every time a train arrives.
A program may be configured.

この第２の発明によれば、列車の着発の度に、列車乗継経路の再探索が実行される。これにより、列車運行に遅延が生じた場合や、旅客が乗車予定の列車に着席できないと判断した場合など、状況に応じて旅客の列車乗継経路が動的に変化する様子を模擬することが可能となる。   According to the second aspect of the invention, the train connection route is re-searched every time a train arrives. As a result, it is possible to simulate a situation in which a passenger's train connection route changes dynamically according to the situation, such as when there is a delay in train operation, or when it is determined that the passenger cannot sit on the scheduled train. It becomes possible.

また、第３の発明として、第１又は第２の発明のプログラムであって、
前記着席可能性判定手段は、前記座席数と、前記乗降制御によって降車した着席乗客の数と、当該列車の立席乗客の数と、前記乗降制御によって乗車した滞留旅客の数とを用いて、着席できる可能性の程度を示す指標値として前記着席可能性を算出する、
プログラムを構成しても良い。 A third invention is a program according to the first or second invention,
The seating possibility determination means uses the number of seats, the number of seated passengers who got off by the boarding / alighting control, the number of standing passengers of the train, and the number of staying passengers boarded by the boarding / alighting control, Calculating the seating possibility as an index value indicating the degree of possibility of being seated;
A program may be configured.

この第３の発明によれば、可能性の程度を示す指標値として、着席可能性が算出される。   According to the third aspect, the seating possibility is calculated as an index value indicating the degree of possibility.

また、第４の発明として、第１〜第３の何れかの発明のプログラムであって、
乗車人数に応じた混雑指標値を用いて立席乗車に対応する前記重み付けを可変に算出する手段、
として前記コンピュータを更に機能させるためのプログラムを構成しても良い。 A fourth invention is a program according to any one of the first to third inventions,
Means for variably calculating the weighting corresponding to standing passengers using a congestion index value according to the number of passengers;
A program for further functioning the computer may be configured.

この第４の発明によれば、乗車人数に応じた混雑指標値を用いて、立席乗車に対する重み付けが可変される。一般的に、着席乗車は、立席乗車に比較して混雑の影響をさほど受けない。また、乗車人数が多いほど、混雑の影響が大きくなる。これにより、着席乗車と立席乗車とを区別したより精度の高い旅客行動シミュレーションが可能となる。   According to the fourth aspect of the invention, the weight for standing passengers is varied using the congestion index value corresponding to the number of passengers. In general, a seated ride is less affected by congestion than a standing ride. In addition, the greater the number of passengers, the greater the impact of congestion. As a result, a more accurate passenger behavior simulation can be performed in which seated boarding and standing boarding are distinguished.

また、第５の発明として、第１〜第４の何れかの発明のプログラムであって、
前記乗車時制御手段は、前記乗降制御によって乗車した滞留旅客のうち、優先的に着席とする旅客を、当該滞留旅客の滞留時間を用いて判断する、
プログラムを構成しても良い。 A fifth invention is a program according to any one of the first to fourth inventions,
The boarding time control means determines a passenger to be preferentially seated among the staying passengers boarded by the boarding / alighting control using the staying time of the staying passengers.
A program may be configured.

この第５の発明によれば、乗車した滞留旅客のうち、優先的に着席とする旅客が、当該滞留旅客の滞留時間を用いて判断される。これにより、駅における列車の待ち時間が長いほど、乗車待ちをしていて乗車すれば着席できる可能性が高まるといった状況を模擬することが可能となる。   According to the fifth aspect of the invention, a passenger who is preferentially seated among the staying passengers on board is determined using the staying time of the staying passenger. This makes it possible to simulate a situation where the longer the waiting time of a train at a station, the more likely it is to be seated if the user waits and gets on.

列車ダイヤの一例。An example of a train schedule. 経路探索ネットワークの概要例。Outline example of route search network. 経路探索ネットワークの詳細な構成例。The detailed structural example of a route search network. 列車到着時における継続乗客の着席制御の説明図。Explanatory drawing of the seating control of the continuing passenger at the time of a train arrival. 滞留旅客の乗車制御の説明図。Explanatory drawing of boarding control of a staying passenger. シミュレーション装置の機能構成図。The functional block diagram of a simulation apparatus. 旅客管理データのデータ構成例。Data configuration example of passenger management data. 旅客出現確率テーブルのデータ構成例。The data structural example of a passenger appearance probability table. 滞留旅客データのデータ構成例。Data structure example of stagnant passenger data. 乗車予約旅客データのデータ構成例。Data configuration example of passenger reservation passenger data. 予測着席確率データのデータ構成例。The data structural example of prediction seating probability data. 予測混雑率データのデータ構成例。The data structural example of prediction congestion rate data. 列車ダイヤデータのデータ構成例。Data configuration example of train schedule data. 運用ダイヤデータのデータ構成例。Data configuration example of operation diagram data. 実績ダイヤデータのデータ構成例。Example of data structure of track record data. 列車データのデータ構成例。Data configuration example of train data. 行動属性設定テーブルのデータ構成例。The data structural example of an action attribute setting table. シミュレーション処理のフローチャート。The flowchart of a simulation process. 着時処理のフローチャート。The flowchart of a process at the time of arrival. 発時処理のフローチャート。The flowchart of a departure process. 図２２の続き。Continuation of FIG. 図２１の続き。Continuation of FIG. 経路探索処理のフローチャート。The flowchart of a route search process.

［概要］
旅客流動シミュレーションでは、シミュレーション時刻を時々刻々と進めながら、出現駅及び目的駅が定められた仮想旅客（以下、単に「旅客」という）の出現制御や、目的駅までの乗車列車を特定した列車乗継経路に沿った旅客の乗降制御、各駅の旅客の乗降人数に応じた遅延制御を含む所与の列車ダイヤに沿った列車の運行制御等を行う。 [Overview]
In the passenger flow simulation, the simulation time is advanced from moment to moment, the appearance control of the virtual passenger (hereinafter simply referred to as “passenger”) where the appearance station and the destination station are defined, and the train ride that identifies the passenger train to the destination station. It controls the operation of trains along a given train schedule, including control of passengers getting on and off along the connecting route, and delay control according to the number of passengers at each station.

本実施形態では、このような旅客流動シミュレーションにおいて、旅客の乗車状況として着席／立席を区別し、列車の着席可能性を考慮した旅客の列車乗継経路の探索や、乗降時の旅客の着席制御を行う。旅客の列車乗継経路は、列車の着発のタイミングで再探索される。これにより、例えば遅延によって列車ダイヤが動的に変化する状況において、列車の着席可能性が変化することによって旅客の列車乗継経路も動的に変化する様子を模擬している。   In this embodiment, in such a passenger flow simulation, seating / standing is distinguished as the passenger's boarding situation, the passenger's train connection route search considering the seating possibility of the train, and the passenger's seating when getting on and off Take control. The passenger's train connection route is re-searched at the timing of arrival and departure of the train. Thus, for example, in a situation where the train schedule changes dynamically due to a delay, a situation in which the passenger's train connection route dynamically changes as the seating possibility of the train changes is simulated.

先ず、所与の列車ダイヤに対する列車乗継経路の探索について説明する。図１は、列車ダイヤの一例である。図１に示すように、列車ダイヤは、横軸を時刻ｔ、縦軸を駅として、各列車を列車スジで表している。図１では、Ａ駅からＤ駅に向かう２本の列車（１，２列車）についての列車ダイヤを示している。Ｃ駅では進行方向が同じ２本の列車が同時に停車可能となっており、このＣ駅で１列車を後続の２列車が追い越している。   First, the search for a train connection route for a given train schedule will be described. FIG. 1 is an example of a train diagram. As shown in FIG. 1, the train diagram represents each train as a train line, with the horizontal axis representing time t and the vertical axis representing a station. FIG. 1 shows a train diagram for two trains (1, 2 trains) from A station to D station. At C station, two trains having the same traveling direction can be stopped at the same time, and at this C station, the following two trains overtake one train.

図２は、旅客の列車乗継経路の探索に用いる経路探索ネットワークの概要である。図２は、図１に示した列車ダイヤを表現した経路探索ネットワークを示している。経路探索ネットワークは、列車や旅客に関する事象を表すノードと、遷移可能なノード間を結ぶアークとから構成される。   FIG. 2 is an outline of a route search network used for searching for a passenger transit route. FIG. 2 shows a route search network representing the train diagram shown in FIG. The route search network is composed of nodes representing events related to trains and passengers and arcs connecting between transitionable nodes.

ノードには、列車が駅に到着する事象を表す着ノード１０と、列車が駅から発車する事象を表す発ノード１２と、発ノード１２に対応して設定され、旅客が駅にいて列車を待っている事象を表す滞留ノード１４と、がある。   The nodes are set corresponding to the arrival node 10 representing the event that the train arrives at the station, the originating node 12 representing the event that the train leaves the station, and the departure node 12, and the passenger is at the station and waits for the train. There is a staying node 14 representing an event that is present.

また、ノードには、該当する事象の発生時刻を表す基準時刻が定められる。すなわち、着ノード１０の基準時刻は、該当列車の該当駅での着時刻であり、発ノード１２の基準時刻は、該当列車の該当駅での発時刻であり、滞留ノード１４の基準時刻は、対応する発ノードの基準時刻と同じである。   Further, a reference time representing the occurrence time of the corresponding event is determined for the node. That is, the reference time of the arrival node 10 is the arrival time of the corresponding train at the corresponding station, the reference time of the departure node 12 is the departure time of the relevant train at the corresponding station, and the reference time of the staying node 14 is It is the same as the reference time of the corresponding originating node.

アークは、基準時刻が早いほうのノードから遅いほうのノードに向かう有向アークであり、列車が駅間を走行していることを表す駅間アーク２０と、列車が駅に停車中であることを表す停車アーク２２と、旅客が列車から降車することを表す降車アーク２４と、旅客が列車に乗車することを表す乗車アーク２６と、旅客が駅にいることを表す滞留アーク２８と、がある。   The arc is a directed arc from the node with the earlier reference time to the node with the later reference time, the inter-station arc 20 indicating that the train is traveling between stations, and the train being stopped at the station A stop arc 22 indicating that the passenger gets off the train, a boarding arc 26 indicating that the passenger gets on the train, and a staying arc 28 indicating that the passenger is at the station. .

駅間アーク２０は、同一列車の発ノード１２から次の停車駅の着ノード１０に向かって設定される。停車アーク２２は、同一列車の同一駅の着ノード１０から発ノード１２に向かって設定される。降車アーク２４は、同一駅の着ノード１０から直後の滞留ノード１４に向かって設定される。乗車アーク２６は、滞留ノード１４から対応する発ノード１２に向かって設定される。滞留アーク２８は、同一駅の滞留ノード１４から直後の滞留ノード１４に向かって設定される。ここで、あるノードの“直後”や“直前”のノードとは、各ノードに定められた基準時刻に従った時間的な順序を表す。   The inter-station arc 20 is set from the departure node 12 of the same train toward the arrival node 10 of the next stop station. The stop arc 22 is set from the arrival node 10 at the same station of the same train toward the departure node 12. The dismounting arc 24 is set from the arrival node 10 at the same station toward the staying node 14 immediately after. The boarding arc 26 is set from the staying node 14 toward the corresponding departure node 12. The stay arc 28 is set from the stay node 14 at the same station toward the stay node 14 immediately after. Here, “immediately after” or “immediately before” a certain node represents a temporal order according to a reference time defined for each node.

また、アークには当該アークを選択する際の基準となる重みづけであるコストが設定される。基本的には、ノード間の遷移に要する時間、すなわち、アークの始端ノードの基準時刻と、終端ノードの基準時刻との時間差が、当該アークのコストとして設定される。また、降車アーク２４及び乗車アーク２６については、時間差に加え、更に、乗り換えにかかるコストとして所定値を加算する。   In addition, the arc is set with a cost, which is a weight that serves as a reference when selecting the arc. Basically, the time required for transition between nodes, that is, the time difference between the reference time of the start node of the arc and the reference time of the end node is set as the cost of the arc. For the dismounting arc 24 and the getting-on arc 26, in addition to the time difference, a predetermined value is added as the cost required for transfer.

本実施形態では、旅客の乗車状況である着席／立席を区別した列車乗継経路の探索を行うため、図３に示すように、各ノードを更に区分した経路探索ネットワークを用いる。   In this embodiment, in order to search for a train connection route that distinguishes between seating and standing that is a passenger's boarding situation, a route search network in which each node is further divided as shown in FIG. 3 is used.

図３は、本実施形態の経路探索ネットワークの一例を示す図である。図３では、図１の列車ダイヤの一部分（具体的には、Ｂ駅を発車後、Ｃ駅に停車して発車するまでの１列車に係るダイヤ）に係るネットワークを示している。分かり易くするため、滞留ノード１４を発ノード１２の上方に配置して図示している。   FIG. 3 is a diagram illustrating an example of a route search network according to the present embodiment. FIG. 3 shows a network relating to a part of the train diagram of FIG. 1 (specifically, a diagram relating to one train from the departure from the B station to the departure at the C station). For the sake of clarity, the staying node 14 is illustrated above the source node 12.

着ノード１０及び発ノード１２は、該当する列車の乗客の乗車状況を表す着席／立席に区分される。すなわち、着ノード１０は、乗客が着席していることを表す着席着ノード１０ａと、乗客が立席であることを表す立席着ノード１０ｂとに区分される。発ノード１２は、乗客が着席していることを表す着席発ノード１２ａと、乗客が立席であることを表す立席発ノード１２ｂとに区分される。   The arrival node 10 and the departure node 12 are classified into seating / standing seats representing the boarding status of passengers of the corresponding train. That is, the arrival node 10 is divided into a seating arrival node 10a indicating that the passenger is seated and a standing arrival node 10b indicating that the passenger is standing. The departure node 12 is divided into a seating departure node 12a indicating that a passenger is seated and a standing departure node 12b indicating that the passenger is standing.

また、滞留ノード１４は、旅客の乗車の優先度を表す優先／一般に区分される。この旅客の乗車の優先度は、当該旅客の駅での待ち時間（滞留時間）に応じて定められる。すなわち、滞留ノード１４は、滞留時間が長く優先度が高い優先滞留ノード１４ａと、滞留時間が短く優先度が低い一般滞留ノード１４ｂとに区分される。   The staying node 14 is classified into priority / general indicating the priority of passenger boarding. The priority of the passenger's boarding is determined according to the waiting time (residence time) of the passenger at the station. That is, the stay node 14 is classified into a priority stay node 14a having a long stay time and a high priority, and a general stay node 14b having a short stay time and a low priority.

更に、着ノード１０に対応して、着席乗車予約ノード１６ａと、立席乗車予約ノード１６ｂとが設定される。着席乗車予約ノード１６ａは、滞留旅客が、対応する列車に乗車した場合に着席となる事象を表し、立席乗車予約ノード１６ｂは、滞留旅客が、対応する列車に乗車した場合に立席となる事象を表す。   Further, a seating reservation node 16a and a standing seat reservation node 16b are set corresponding to the arrival node 10. The seated boarding reservation node 16a represents an event that becomes a seat when the staying passenger gets on the corresponding train, and the standing boarding reservation node 16b becomes a seating when the staying passenger gets on the corresponding train. Represents an event.

また、ノードの区分に合わせて、アークも区分して設定される。すなわち、駅間アーク２０として、着席発ノード１２ａから着席着ノード１０ａに向かう、乗客が着席していることを表す着席駅間アーク２０ａと、立席発ノード１２ｂから立席着ノード１０ｂに向かう、乗客が立席であることを表す立席駅間アーク２０ｂと、が設定される。   Further, arcs are also set in accordance with the node classification. That is, as the inter-station arc 20, from the seating departure node 12a to the seated seating node 10a, the seated interstation arc 20a indicating that the passenger is seated, and from the standing departure node 12b to the standing seating node 10b, The standing station arc 20b indicating that the passenger is standing is set.

停車アーク２２として、着席着ノード１０ａから着席発ノード１２ａへ向かう、乗客の着席での継続乗車を表す着席停車アーク２２ａと、立席着ノード１０ｂから立席発ノード１２ｂへ向かう、乗客の立席での継続乗車を表す立席停車アーク２２ｂと、立席着ノード１０ｂから着席発ノード１２ａに向かう、立席の乗客が着席したことを表す着席移行停車アーク２２ｃと、が設定される。   As the stop arc 22, a seating stop arc 22 a representing continuous boarding of the passenger seated from the seated seating node 10 a to the seating departure node 12 a, and a passenger seating from the standing seating node 10 b to the standing departure node 12 b A standing stop arc 22b representing continuous boarding and a seat transition arc 22c representing standing seated passengers from the standing node 10b to the seating departure node 12a are set.

降車アーク２４として、着席着ノード１０ａ及び立席着ノード１０ｂそれぞれから一般滞留ノード１４ｂへ向かうアーク２４ａ，２４ｂが設定される。滞留ノード１４は旅客の滞留時間によって優先滞留ノード１４ａと一般滞留ノード１４ｂとに区分されるため、降車アーク２４は、一般滞留ノード１４ｂに向かうアークのみが設定される。   As the disembarking arc 24, arcs 24a and 24b are set from the seated node 10a and the standing node 10b to the general stay node 14b. The staying node 14 is divided into the priority staying node 14a and the general staying node 14b according to the staying time of the passenger, so that only the arc going to the general staying node 14b is set as the dismounting arc 24.

乗車アーク２６として、優先滞留ノード１４ａから着席発ノード１２ａへ向かう、旅客が乗車して着席したことを表す優先着席乗車アーク２６ａと、優先滞留ノード１４ａから立席発ノード１２ｂへ向かう、旅客が乗車して立席となることを表す優先立席乗車アーク２６ｂと、一般滞留ノード１４ｂから着席発ノード１２ａへ向かう、旅客が乗車して着席したことを表す一般着席乗車アーク２６ｃと、一般滞留ノード１４ｂから立席発ノード１２ｂへ向かう、旅客が乗車して立席となったことを表す一般立席乗車アーク２６ｄと、が設定される。   As the boarding arc 26, the passenger boarding from the priority staying node 14a to the seating departure node 12a, the priority seating boarding arc 26a indicating that the passenger boarded and seated, and the passenger from the priority staying node 14a to the standing departure node 12b. A priority standing boarding arc 26b representing standing, a general seating arc 26c representing a passenger boarding from the general staying node 14b toward the seating departure node 12a, and a general staying node 14b. Is set to a general standing boarding arc 26d indicating that the passenger boarded and became a standing seat from the standing departure node 12b.

滞留アーク２８として、優先滞留ノード１４ａから優先滞留ノード１４ａへ向かう優先継続滞留アーク２８ａと、一般滞留ノード１４ｂから一般滞留ノード１４ｂへ向かう一般継続滞留アーク２８ｂと、一般滞留ノード１４ｂから優先滞留ノード１４ａへ向かう、旅客の滞留時間が所定時間に達したことを表す優先移行滞留アーク２８ｃと、が設定される。   As the staying arc 28, the priority continuous staying arc 28a from the priority staying node 14a to the preferential staying node 14a, the general continuous staying arc 28b from the general staying node 14b to the general staying node 14b, and the preferential staying node 14a from the general staying node 14b. A priority transfer staying arc 28c indicating that the staying time of the passenger has reached a predetermined time is set.

更に、着席乗車予約ノード１６ａから着席発ノード１２ａに向かう、滞留旅客が乗車して着席したことを表すアーク３０ａと、着席乗車予約ノード１６ａから一般滞留ノード１４ｂへ向かう、滞留旅客の乗車予定の列車の変更を表すアーク３０ｂと、立席乗車予約ノード１６ｂから立席発ノード１２ｂに向かう、滞留旅客が乗車して立ち席となったことを表すアーク３０ｃと、立席乗車予約ノード１６ｂから一般滞留ノード１４ｂへ向かう、滞留旅客の乗車予定の列車の変更を表すアーク３０ｄと、が設定される。   Further, an arc 30a indicating that the staying passenger has boarded and seated from the seating boarding reservation node 16a to the seating departure node 12a, and a train scheduled for boarding of the staying passenger from the seating boarding reservation node 16a to the general staying node 14b. An arc 30b representing the change of the vehicle, an arc 30c representing that the staying passenger has boarded from the standing seat reservation node 16b to the standing departure node 12b, and a general stay from the standing seat reservation node 16b. An arc 30d representing the change of the train on which the staying passenger is scheduled to go to the node 14b is set.

これらのアークのうち、旅客が着席状態に移行したことを表すアークである着席移行停車アーク２２ｃ、一般着席乗車アーク２６ｃ、及び、優先着席乗車アーク２６ａの３つのアークを、本実施形態では、特に「着席アーク」という。   Of these arcs, three arcs of the seat transition arc 22c, the general seating riding arc 26c, and the priority seating riding arc 26a, which are arcs indicating that the passenger has transitioned to the seated state, It is called “sitting arc”.

また、アークには、上述のように、当該アークの始端ノードの基準時刻と終端ノードの基準時刻との時間差が、基本のコストとして設定される。   Further, as described above, a time difference between the reference time of the start node and the reference time of the end node of the arc is set as a basic cost for the arc.

更に、着席アークについては、着席できる可能性の程度を示す指標値である着席確率に応じてコストが変更される。具体的には、着席確率が小さいほど、該当する着席アークのコストが大きくなるように変更される。本実施形態では、着席アークに該当する着席確率を、想定する旅客に応じて決まる所定の閾値と比較することで、当該着席アークのコストを変更する。所定の閾値は、当該旅客が着席可能とみなす着席確率の下限値として、当該旅客に応じて設定される（図１７の着席可能認知確率に相当）。着席確率が所定の閾値に達している場合、当該旅客は着席可能とみなすとして、当該着席アークのコストを変更しない。一方、着席確率が所定の閾値に達していない場合には、当該旅客は着席不可能とみなすとして、当該着席アークのコストを「∞（無限大：非常に大きな所定値）」に変更し、当該旅客の列車乗継経路の探索において当該着席アークが選ばれないようにする。   Further, for the seating arc, the cost is changed according to the seating probability which is an index value indicating the degree of possibility of seating. Specifically, the cost is changed so that the seating arc cost increases as the seating probability decreases. In the present embodiment, the cost of the seating arc is changed by comparing the seating probability corresponding to the seating arc with a predetermined threshold determined according to the assumed passenger. The predetermined threshold is set according to the passenger as a lower limit value of the seating probability that the passenger is considered seatable (corresponding to the seatable recognition probability in FIG. 17). If the seating probability has reached a predetermined threshold value, the passenger is considered seatable, and the cost of the seating arc is not changed. On the other hand, if the seating probability does not reach the predetermined threshold value, the passenger is deemed to be unable to seat, and the cost of the seating arc is changed to “∞ (infinity: very large predetermined value)” The seating arc is not selected in the search for the passenger transit route.

着席アークに対応する着席確率は、次のように算出される。すなわち、着席移行停車アーク２２ｃの着席確率は、該当駅において該当列車の立席の継続乗車旅客（継続乗客）が着席した確率（継続乗車時の着席確率）であり、該当列車の到着時の立席の継続乗客の人数に対する停車中に立席から着席に移行した乗客の人数の割合として算出される。   The seating probability corresponding to the seating arc is calculated as follows. In other words, the seating probability of the seating transition stop arc 22c is the probability that the continuation passenger (succession passenger) standing on the corresponding train is seated at the corresponding station (sitting probability at the time of continuous riding), and the standing probability at the time of arrival of the corresponding train. It is calculated as the ratio of the number of passengers who have transitioned from standing to sitting while the vehicle is at a stop relative to the number of passengers in the seat.

また、一般着席乗車アーク２６ｃ、及び、優先着席乗車アーク２６ａの着席確率は、該当駅において該当列車に乗車予定の滞留旅客が乗車して着席した確率（乗車時の着席確率）である。すなわち、優先着席乗車アーク２６ａの着席確率は、該当駅における該当列車に乗車予定の優先滞留旅客の人数に対する、該当列車に乗車して着席した優先滞留旅客の人数の割合として算出される。また、一般着席乗車アーク２６ｃの着席確率は、該当駅における該当列車に乗車予定の一般滞留旅客の人数に対する、該当列車に乗車して着席した一般滞留旅客の人数として算出される。   Moreover, the seating probability of the general seating boarding arc 26c and the priority seating boarding arc 26a is the probability that the staying passenger who is scheduled to board the train at the corresponding station has been seated (the seating probability at the time of boarding). In other words, the seating probability of the priority seating arc 26a is calculated as the ratio of the number of priority staying passengers who have boarded and seated in the corresponding train to the number of priority staying passengers scheduled to board the corresponding train at the corresponding station. Further, the seating probability of the general seated boarding arc 26c is calculated as the number of general staying passengers who are seated on the corresponding train with respect to the number of general staying passengers who are scheduled to board the corresponding train at the corresponding station.

また、駅間アーク２０については、更に、該当する駅間の混雑率（乗車率ともいう）に応じてコストが変更・設定される。混雑率は、該当列車の定員人数に対する該当列車の該当駅間の乗客の人数の割合として算出される。そして、混雑率を変数とする所定の混雑不効用関数Ｆから得られる混雑不効用値Ｕｃに応じて、着席駅間アーク２０ａ及び立席駅間アーク２０ｂそれぞれを変更する。   Further, for the inter-station arc 20, the cost is further changed / set according to the congestion rate (also referred to as a boarding rate) between the corresponding stations. The congestion rate is calculated as a ratio of the number of passengers between the corresponding stations of the corresponding train to the number of passengers of the corresponding train. Then, according to the congestion invalidity value Uc obtained from a predetermined congestion invalidity function F having the congestion rate as a variable, the seated station arc 20a and the standing station arc 20b are changed.

このとき、同一列車の同一駅間について、着席駅間アーク２０ａのコストよりも立席駅間アーク２０ｂのコストのほうが大きくなるように変更する。具体的には、例えば、先ずは混雑不効用値Ｕｃに応じて着席駅間アーク２０ａのコストを変更し、この変更した着席駅間アーク２０ａのコストの所定倍（例えば、２倍）となるように、立席駅間アーク２０ｂのコストを変更する。これにより、一般的に立席の乗客のほうが着席の乗客よりも混雑の影響（不効用）を受け易く、旅客が立席乗車となる列車乗継経路を選びにくくなるといった様子を模擬することが可能となる。   At this time, it changes so that the cost of the arc 20b between standing stations may become larger than the cost of the arc 20a between seats about the same station of the same train. Specifically, for example, first, the cost of the seated station arc 20a is changed according to the congestion invalidity value Uc, so that the cost of the changed seated station arc 20a is a predetermined multiple (for example, twice). In addition, the cost of the standing station arc 20b is changed. This makes it possible to simulate the situation that standing passengers are generally more susceptible to congestion (invalidity) than seated passengers, making it difficult for passengers to select a transit route for standing passengers. It becomes possible.

そして、このような経路探索ネットワークに基づき、経由する各アークのコストの総和が最小となる経路を、旅客の列車乗継経路として探索する。   Then, based on such a route search network, a route that minimizes the sum of the costs of the respective arcs that pass through is searched for as a passenger transit route.

本実施形態において、旅客の列車乗継経路の探索は、旅客の出現時、及び、各駅における列車の着発時、に行われる。旅客の出現時には、出現駅における出現時刻の直後の一般滞留ノード１４ｂから目的駅に至る経路を、当該旅客の列車乗継経路として探索する。   In this embodiment, the search for a passenger's train connection route is performed when a passenger appears and when a train arrives at each station. When a passenger appears, a route from the general staying node 14b immediately after the appearance time at the appearance station to the destination station is searched as a train connection route of the passenger.

また、各駅における列車の着発時（到着時および出発時）には、当該着発が発生した駅に係る全ての旅客それぞれについて、列車乗継経路の再探索を行い、当該駅以降の列車乗継経路を更新する。このとき、対象の旅客の現在状況に応じたノードから目的駅に至る経路を探索する。すなわち、停車中の列車の乗客のうち、着席している乗客については、当該列車の当該駅への着席着ノード１０ａから目的駅に至る経路を探索し、立席の乗客については、当該列車の当該駅への立席着ノード１０ｂから目的駅に至る経路を探索する。また、駅の滞留旅客のうち、一般滞留旅客については、当該駅における現在時刻の直後の一般滞留ノード１４ｂから目的駅に至る経路を探索し、優先滞留旅客については、当該駅における現在時刻の直後の優先滞留ノード１４ａから目的駅に至る経路を探索する。更に、停車中の列車に関する着席乗車予約旅客及び立席乗車予約旅客については、当該列車の着席乗車予約ノード１６ａ又は立席乗車予約ノード１６ｂから、目的駅に至る経路を探索する。目的駅の着ノード１０は、着席着ノード１０ａでも立席着ノード１０ｂでもどちらでも構わない。   In addition, at the time of arrival and departure of a train at each station (for arrival and departure), the train connection route is re-searched for all passengers related to the station where the arrival and departure occurs, Update the connection route. At this time, the route from the node corresponding to the current situation of the target passenger to the destination station is searched. That is, for passengers who are seated among the train passengers that are stopped, the route from the seated node 10a to the target station of the train to the target station is searched, and for passengers who are standing, The route from the standing node 10b to the station to the destination station is searched. Further, among the passengers staying at the station, for general staying passengers, the route from the general staying node 14b immediately after the current time at the station to the destination station is searched, and for priority staying passengers, immediately after the current time at the station. The route from the priority staying node 14a to the destination station is searched. Furthermore, for the seated boarding reservation passenger and the standing boarding reservation passenger related to the stopped train, the route from the seating boarding reservation node 16a or the standing boarding reservation node 16b of the train to the target station is searched. The destination node 10 at the destination station may be either the seated node 10a or the standing node 10b.

次に、乗客の着席／立席の制御について説明する。但し、旅客は、当該旅客に設定された列車乗継経路に従って列車の乗降が制御される。また、着席した乗客は、その列車を降車するまで着席を継続することとする。つまり、同一列車の乗車中に着席から立席に移行することは無い。また、乗客は、立席よりも着席を優先することとする。つまり、空席が有るにも関わらず立席の乗客がいる状況は無いとする。   Next, passenger seating / standing control will be described. However, the passenger is controlled to get on and off the train according to the train connection route set for the passenger. In addition, seated passengers continue to sit until they get off the train. That is, there is no transition from sitting to standing while riding the same train. Passengers give priority to sitting rather than standing. In other words, it is assumed that there are no standing passengers even though there are vacant seats.

図４に示すように、列車４０が駅に到着すると、当該列車４０の乗客のうち、当該駅で降車予定の乗客を降車させる。着席の乗客５０が降車することで、新たな空席が発生する。次いで、この新たに発生した空席に、当該列車の立席の継続乗車の乗客５１を着席させる。このとき、新たに発生した空席数が、立席継続乗客の人数以上の場合には、全ての立席継続乗客を着席させる。一方、空席数が、立席継続乗客の人数より少ない場合には、立席の継続乗客のうち、例えばランダムに選択した空席数の乗客を着席させる。   As shown in FIG. 4, when a train 40 arrives at a station, among the passengers of the train 40, passengers scheduled to get off at the station are dropped off. When the seated passenger 50 gets off, a new vacant seat is generated. Next, a passenger 51 who is continuously standing on the train is seated in the newly generated vacant seat. At this time, if the number of newly generated vacant seats is greater than or equal to the number of standing passengers, all standing passengers are seated. On the other hand, when the number of vacant seats is smaller than the number of standing passengers, for example, passengers with the vacant number selected at random are seated among the standing passengers.

続いて、図５に示すように、当該列車４０に乗車予定の当該駅の滞留旅客５２を、当該列車に乗車した場合に着席となる着席乗車予約旅客５６と、立席となる立席乗車予約旅客５７とに振り分ける。すなわち、先ず、当該列車４０に乗車予定の滞留旅客５２のうち、滞留時間（待ち時間）が所定時間に達している旅客を、優先的に着席できる優先滞留旅客５３とし、達していない旅客を一般滞留旅客５４とする。   Subsequently, as shown in FIG. 5, when the staying passenger 52 of the station scheduled to board the train 40 is seated when the passenger rides on the train, the seating reservation passenger 56 becomes seated, and the standing boarding reservation becomes standing. Assign to passenger 57. That is, first, among the staying passengers 52 scheduled to board the train 40, a passenger whose staying time (waiting time) has reached a predetermined time is designated as a preferential staying passenger 53 that can be seated preferentially, and a passenger who has not reached the general passenger Let it be a staying passenger 54.

そして、優先滞留旅客５３を優先して着席させるように、上述の継続乗客を着席させた後の空席数Ｎに応じて、滞留旅客を着席乗車予約旅客５６及び立席乗車予約旅客５７に振り分ける。具体的には、優先滞留旅客５３の人数Ｘが空席数Ｎ以下ならば（Ｘ≦Ｎ）、優先滞留旅客５３の全てを着席乗車予約旅客５６とする。また、一般滞留旅客５４のうちから、例えばランダムに選択した、空席数Ｎと優先滞留旅客の人数Ｘとの差人数（＝Ｎ−Ｘ）の旅客を着席乗車予約旅客５６としそれ以外の旅客を立席乗車予約旅客５７とする。一方、優先滞留旅客人数Ｘが空席数Ｎを越えるならば（Ｘ＞Ｎ）、優先滞留旅客５３のうち、例えばランダムに選択した空席数Ｎの旅客を着席乗車予約旅客５６とし、それ以外の優先滞留旅客、及び、全ての一般滞留旅客５４を立席乗車予約旅客５７とする。   Then, the staying passengers are distributed to the seated boarding reservation passengers 56 and the standing boarding reservation passengers 57 in accordance with the number of vacant seats N after the above-described continuing passengers are seated so that the priority staying passengers 53 are preferentially seated. Specifically, if the number X of the priority staying passengers 53 is equal to or less than the number of vacant seats N (X ≦ N), all of the priority staying passengers 53 are set as seated boarding reservation passengers 56. Further, for example, randomly selected passengers with a difference (= N−X) between the number of vacant seats N and the number of priority staying passengers X (= N−X) are selected as seated passengers 56 and other passengers are selected. It is assumed that the standing passenger reservation passenger 57. On the other hand, if the priority staying passenger number X exceeds the number of vacant seats N (X> N), among the priority staying passengers 53, for example, a randomly selected passenger with the number of vacant seats N is set as the seated passenger reservation passenger 56, The staying passengers and all general staying passengers 54 are referred to as standing passenger reservation passengers 57.

列車の停車中は、当該駅への他の列車の発着等のタイミングで、当該列車４０の乗客や当該駅の滞留旅客の列車乗継経路が再探索される。つまり、旅客の列車乗継経路の更新によって、当該列車４０に継続乗車予定の乗客が降車することで、当該列車４０の空席数が変動（増加）したり、当該列車４０に乗車予定の滞留旅客が乗車予定の列車を変更することで、滞留旅客５２の人数が変動（増減）するといったことが発生する。このため、列車乗継経路の再探索に合わせて、再度、上述の乗車予約旅客の振り分けが行われる。つまり、当該列車４０の空席数を算出し、算出した空席数に応じて、当該列車４０に乗車予定の滞留旅客５２を、優先滞留旅客５３を優先して着席乗車予約旅客５６と立席乗車予約旅客５７とに振り分ける。   While the train is stopped, the train connection routes of passengers of the train 40 and passengers staying at the station are searched again at the timing of arrival and departure of other trains at the station. In other words, when a passenger who is scheduled to continue to get on the train 40 gets off by updating the train connection route of the passenger, the number of seats of the train 40 changes (increases), or the staying passenger who is scheduled to board the train 40 However, the number of staying passengers 52 may change (increase / decrease) by changing the train scheduled to be boarded. For this reason, according to the re-search of the train connection route, the above-mentioned passenger reservation passengers are sorted again. That is, the number of vacant seats of the train 40 is calculated, and the staying passenger 52 scheduled to board the train 40, the priority staying passenger 53, and the seated passenger reservation passenger 56 and the standing seat reservation according to the calculated number of vacant seats. Assign to passenger 57.

そして、当該列車４０の発車時に、当該駅の当該駅に乗車予定の滞留旅客５５を乗車させる。このとき、着席乗車予約旅客５６を着席乗客とし、立席予約旅客５７を立席乗客とする。   Then, when the train 40 departs, the staying passenger 55 scheduled to board the station is boarded. At this time, the seated passenger reservation passenger 56 is a seated passenger, and the standing seat passenger 57 is a standing passenger.

本実施形態のシミュレーションはシミュレーション時刻（仮想時刻）を時々刻々と計時してシミュレートし、このシミュレーション時刻が、ある駅のある列車の着事象或いは発事象に該当するタイミングで、そのある駅およびある列車に係る旅客の列車乗継経路を再探索する。   In the simulation of this embodiment, the simulation time (virtual time) is measured every moment, and the simulation time is a timing corresponding to an arrival event or a departure event of a certain station. Re-search the train connection routes of passengers involved in the train.

このため、例えば、第１列車が第１駅の停車中（到着から発車までの間）のあるタイミングで、第２列車が第２駅に到着或いは発車したことで、第２列車および第２駅に係る旅客の列車乗継経路が再探索される場合がある。第１列車と第２列車とが第３駅で乗り換え可能である場合、第２列車の空席数や乗客数が変化することで、第１列車が第１駅から出発する際の再探索において、第１列車の乗客の列車乗継経路を可変に設定することが可能となる。こういった連動的・有機的な作用が表れる結果、着席可能性を考慮した特異な旅客流動シミュレーションを実現することができる。   For this reason, for example, when the second train arrives or departs at the second station at a timing when the first train is stopped at the first station (between arrival and departure), the second train and the second station In some cases, the train connection route of the passenger is re-searched. When the first train and the second train can be transferred at the third station, the number of vacant seats and the number of passengers of the second train changes, and in the re-search when the first train departs from the first station, It becomes possible to variably set the train connection route of passengers of the first train. As a result of these interlocking and organic effects, it is possible to realize a unique passenger flow simulation that takes into account the possibility of seating.

［機能構成］
図６は、本実施形態のシミュレーション装置１の機能構成図である。図６によれば、シミュレーション装置１は、操作入力部１１０と、表示部１２０と、通信部１３０と、処理部２００と、記憶部３００とを備えて構成されるコンピュータシステムである。 [Function configuration]
FIG. 6 is a functional configuration diagram of the simulation apparatus 1 of the present embodiment. According to FIG. 6, the simulation apparatus 1 is a computer system that includes an operation input unit 110, a display unit 120, a communication unit 130, a processing unit 200, and a storage unit 300.

操作入力部１１０は、例えばキーボードやマウス、タッチパネル、各種スイッチ等で実現される入力装置であり、操作入力に応じた操作信号を処理部２００に出力する。表示部１２０は、例えばＬＣＤ（液晶ディスプレイ）やＥＬＤ（有機ＥＬディスプレイ）等で実現される表示装置であり、処理部２００からの表示信号に基づく各種表示を行う。通信部１３０は、例えば無線通信モジュール、ルータ、モデム、有線用の通信ケーブルのジャックや制御回路等で実現される通信装置であり、外部機器との間でデータ通信を行う。   The operation input unit 110 is an input device realized by, for example, a keyboard, a mouse, a touch panel, various switches, and the like, and outputs an operation signal corresponding to the operation input to the processing unit 200. The display unit 120 is a display device realized by, for example, an LCD (liquid crystal display) or an ELD (organic EL display), and performs various displays based on display signals from the processing unit 200. The communication unit 130 is a communication device realized by, for example, a wireless communication module, a router, a modem, a wired communication cable jack, a control circuit, and the like, and performs data communication with an external device.

処理部２００は、例えばＣＰＵ等の演算装置で実現され、記憶部３００に記憶されたプログラムやデータ、操作入力部１１０からの入力データ等に基づいて、シミュレーション装置１を構成する各部への指示やデータ転送を行い、シミュレーション装置１の全体制御を行う。また、本実施形態では、処理部２００は、旅客管理部２１０と、着席確率算出部２２０と、混雑率算出部２３０と、列車運行制御部２４０と、列車乗継経路探索部２５０と、不効用値算出部２６０とを有し、シミュレーションプログラム３１０に従った旅客流動シミュレーション処理（図１８〜図２３参照）を実行する。   The processing unit 200 is realized by an arithmetic device such as a CPU, for example, and based on programs and data stored in the storage unit 300, input data from the operation input unit 110, and the like, Data transfer is performed and overall control of the simulation apparatus 1 is performed. In the present embodiment, the processing unit 200 includes a passenger management unit 210, a seating probability calculation unit 220, a congestion rate calculation unit 230, a train operation control unit 240, a train transit route search unit 250, and an invalid use. And a passenger flow simulation process (see FIGS. 18 to 23) according to the simulation program 310.

旅客管理部２１０は、出現制御部２１１と、降車制御部２１２と、継続乗車着席制御部２１３と、乗車制御部２１４と、滞留管理部２１５とを有し、旅客を管理する。   The passenger management unit 210 includes an appearance control unit 211, an exit control unit 212, a continuous boarding / seating control unit 213, a boarding control unit 214, and a stay management unit 215, and manages passengers.

旅客は、旅客管理データ３７０によって管理される。図７は、旅客管理データ３７０のデータ構成の一例を示す図である。図７によれば、旅客管理データ３７０は、旅客毎に生成され、旅客ＩＤ３７１と、行動属性３７２と、出現駅３７３と、出現時刻３７４と、目的駅３７５と、現在状況３７６と、列車乗継経路３７７とを格納している。   Passengers are managed by passenger management data 370. FIG. 7 is a diagram illustrating an example of the data configuration of the passenger management data 370. According to FIG. 7, the passenger management data 370 is generated for each passenger, and the passenger ID 371, the behavior attribute 372, the appearance station 373, the appearance time 374, the destination station 375, the current situation 376, and the train connection. The route 377 is stored.

行動属性３７２は、列車乗継経路の探索の条件となる旅客の行動の特性であり、本実施形態では、着席可能性についての条件とする。具体的には、ある程度の時間を要しても着席できることを重要視する「着席重視型」と、着席できるかには拘らずに最も早く目的駅に到着できることを重視する「最早列車選択型」と、の何れかとする。   The behavior attribute 372 is a characteristic of passenger behavior that is a condition for searching for a train connection route. In this embodiment, the behavior attribute 372 is a condition regarding seating possibility. Specifically, the “seat-oriented type” places importance on being able to sit even if it takes a certain amount of time, and the “early-early train selection type” places importance on being able to arrive at the destination station first, regardless of whether it can be seated. Or either.

現在状況３７６は、旅客の現在の行動状況であり、具体的には、列車に乗車中ならば、乗車中の列車の列車番号といった識別情報や、当該列車が停車中の駅或いは走行中の駅間の他、着席か立席かの区別を格納し、乗車中でないならば、当該旅客が現在いる（滞留している）駅の駅名を格納する。   The current situation 376 is the current behavior situation of the passenger. Specifically, if the user is on a train, identification information such as the train number of the train being boarded, a station where the train is stopped, or a station that is running In addition to the interval, the distinction between seating and standing is stored, and if not on boarding, the station name of the station where the passenger is present (staying) is stored.

列車乗継経路３７７は、出現駅３７３から目的駅３７５に至る列車の乗継経路であり、乗車すべき列車の列車番号や乗り換え駅が時系列に沿って格納される。この列車乗継経路３７７は、先ずは出現時に作成され、列車の運行状況に応じて適宜更新され、最終的には当該旅客の列車乗継経路の実績（行動実績）となる。   The train connection route 377 is a train connection route from the appearance station 373 to the destination station 375, and stores the train number of the train to be boarded and the transfer station in time series. This train connection route 377 is first created at the time of appearance, is updated as appropriate according to the train operation status, and finally becomes the result (actual result) of the passenger's train connection route.

出現制御部２１１は、対象線区内の各駅での旅客の出現を制御する。具体的には、行動属性毎に、該当する旅客出現確率テーブル３５０において定められた出現駅と目的駅との組み合わせ毎の出現確率に従って、当該出現駅に旅客を出現させる。例えば、出現確率に基づいてポワソン分布に従った乱数を発生させ、発生させた乱数に従って旅客の仮想的な出現時刻の分布を生成し、生成した出現時刻の分布に従って旅客を出現させる。出現させた旅客は、出現駅における一般滞留旅客とする。   The appearance control unit 211 controls the appearance of passengers at each station in the target line area. Specifically, for each behavior attribute, the passenger is caused to appear at the appearing station according to the appearing probability for each combination of the appearing station and the target station defined in the corresponding passenger appearance probability table 350. For example, random numbers are generated according to the Poisson distribution based on the appearance probability, a virtual appearance time distribution of passengers is generated according to the generated random numbers, and the passengers appear according to the generated distribution of appearance times. The appearing passenger is assumed to be a general staying passenger at the appearing station.

図８は、旅客出現確率テーブル３５０のデータ構成の一例を示す図である。図８によれば、旅客出現確率テーブル３５０は、行動属性３５１毎に用意され、時間帯３５２毎に、出現駅３５３と目的駅３５４との組み合わせそれぞれについて旅客の出現確率（単位時間当たりの旅客の出現人数に相当）を格納している。すなわち、出現駅３５３毎に、他の各駅を目的駅３５４とする旅客の出現確率を定義している。この出現確率は、例えば、各駅に設置されている自動改札機等で収集された旅客の駅構内への入退場時刻のデータ、乗車駅及び降車駅のデータ等から決定されたり、各旅客の利用列車や時間帯毎の乗車人数といった調査データをもとに決定される値である。時間帯３５２は、対象線区内の運行の始発から終着までを含むシミュレーションの対象となり得る全時間帯を、例えば３０分といった所定の単位時間で区切った時間帯である。出現駅３５３及び目的駅３５４は、対象線区内の全ての駅である。   FIG. 8 is a diagram illustrating an example of a data configuration of the passenger appearance probability table 350. According to FIG. 8, the passenger appearance probability table 350 is prepared for each behavior attribute 351, and for each time zone 352, the passenger appearance probability (passenger per unit time) for each combination of the appearance station 353 and the destination station 354. Equivalent to the number of appearances). That is, for each appearance station 353, the appearance probability of a passenger whose destination station 354 is another station is defined. This probability of appearance is determined from, for example, passenger entry / exit time data collected by automated ticket gates installed at each station, boarding and exiting station data, etc. It is a value determined based on survey data such as the number of passengers by train and time zone. The time zone 352 is a time zone obtained by dividing the entire time zone that can be the target of simulation including the operation from the start to the end of the operation in the target line section by a predetermined unit time such as 30 minutes. The appearance station 353 and the destination station 354 are all stations in the target line ward.

降車制御部２１２は、駅に到着した列車の乗客のうち、当該駅で降車予定の乗客を降車させる。すなわち、当該駅を目的駅とする乗客、及び、当該駅が列車乗継経路で定められる乗り換え駅である乗客が、当該駅での降車予定の乗客となる。降車させた乗客は、当該駅が目的駅ならば目的駅に到着したとして消滅させ、当該駅が乗換駅ならば当該駅の（一般）滞留旅客とする。   The getting-off control unit 212 causes a passenger who is scheduled to get off at the station among the passengers of the train that has arrived at the station. That is, a passenger whose destination is the station and a passenger who is a transfer station determined by a train connection route are passengers who are scheduled to get off at the station. Passengers who get off the vehicle are eliminated if they arrive at the destination station if the station is the destination station, and are (general) staying passengers at the station if the station is a transfer station.

継続乗車着席制御部２１３は、駅に停車した列車について、降車制御部２１２による着席乗客の降車によって生じた空席に、立席の継続乗客を着席させる。具体的には、着席乗客の降車によって生じた空席数が立席の継続乗客の人数以上ならば、立席の継続乗客の全てを着席させる。一方、空席数が立席の継続乗客の人数未満ならば、立席の継続乗客のうち、空席数の乗客を例えばランダムに選択して着席させる。   The continuation boarding / seat control unit 213 causes the standing continuation passenger to seat in the vacant seat generated by the getting-off of the seated passenger by the getting-off control unit 212 for the train stopped at the station. Specifically, if the number of vacant seats generated by getting off the seated passenger is equal to or more than the number of standing passengers, all the standing passengers are seated. On the other hand, if the number of vacant seats is less than the number of standing passengers, the number of vacant passengers among the standing passengers is selected at random, for example.

乗車制御部２１４は、駅に停車中の列車に、当該列車に乗車予定の滞留旅客を乗車させる。このとき、当該列車に乗車予定の滞留旅客のうち、着席予約旅客については着席乗客として乗車させ、立席予約旅客については立席乗客として乗車させる、   The boarding control unit 214 causes a staying passenger on the train to board the train that is stopped at the station. At this time, among the staying passengers scheduled to board the train, seated passengers are boarded as seated passengers, and seated passengers are boarded as standing passengers.

滞留管理部２１５は、各駅の滞留旅客を管理する。具体的には、滞留時間が所定時間に達した滞留旅客を優先滞留旅客とし、それ以外の滞留旅客を一般滞留旅客とする。   The stay management unit 215 manages stay passengers at each station. Specifically, a staying passenger whose staying time has reached a predetermined time is set as a priority staying passenger, and other staying passengers are set as general staying passengers.

滞留旅客は、滞留旅客データ４１０として管理される。図９は、滞留旅客データ４１０のデータ構成の一例を示す図である。図９によれば、滞留旅客データ４１０は、対象線区内の全ての駅４１１毎に生成され、当該駅における滞留旅客のうち、優先滞留旅客の一覧である優先滞留旅客リスト４１２と、一般滞留旅客の一覧である一般滞留旅客リスト４１３とを格納している。   The staying passenger is managed as staying passenger data 410. FIG. 9 is a diagram showing an example of the data configuration of the staying passenger data 410. As shown in FIG. According to FIG. 9, the staying passenger data 410 is generated for every station 411 in the target line area, and among the staying passengers at the station, the priority staying passenger list 412 that is a list of preferential staying passengers, and the general staying passenger data A general stay passenger list 413, which is a list of passengers, is stored.

優先滞留旅客リスト４１２は、優先滞留旅客それぞれについて、旅客ＩＤ４１２ａと、滞留開始時刻４１２ｂと、乗車予定列車４１２ｃとを対応付けて格納している。一般滞留旅客リスト４１３は、一般滞留旅客それぞれについて、旅客ＩＤ４１３ａと、滞留開始時刻４１３ｂと、乗車予定列車４１３ｃとを対応付けて格納している。   The priority staying passenger list 412 stores a passenger ID 412a, a stay start time 412b, and a scheduled train 412c in association with each other for each priority staying passenger. The general staying passenger list 413 stores a passenger ID 413a, a staying start time 413b, and a scheduled train 413c in association with each other for each general staying passenger.

また、滞留管理部２１５は、駅に停車中の列車に乗車予定の滞留旅客を、当該列車に乗車した場合に着席となる着席予約旅客と、立席となる立席予約旅客とに振り分ける。すなわち、停車中の列車について、継続乗車着席制御部２１３によって立席の継続乗客の着席がなされた後の空席数を算出し、当該列車に乗車予定の滞留旅客のうち、優先滞留旅客を優先的に、空席数の滞留旅客を着席乗車予約旅客とし、それ以外の滞留旅客を立席乗車予約旅客とする。より具体的には、空席数がゼロの場合には、全ての滞留旅客を立席乗車予約旅客とし、着席乗車予約旅客はゼロとする。空席数が１以上、且つ、優先滞留旅客の人数以下の場合には、優先滞留旅客のうちから、例えばランダムに選択した空席数の旅客を着席乗車予約旅客とし、それ以外の優先滞留旅客及び全ての一般滞留旅客を立席乗車予約旅客とする。空席数が優先滞留旅客の人数を超える場合には、優先滞留旅客の全てと、一般滞留旅客のうちから例えばランダムに選択した旅客との合計が空席数となる旅客を着席乗車予約旅客とし、それ以外の一般滞留旅客を立席乗車予約旅客とする。   In addition, the stay management unit 215 distributes the stay passengers scheduled to board the train that is stopped at the station into a seat reservation passenger who is seated when the train is boarded and a standing reservation passenger who is a seat. That is, for a stopped train, the number of vacant seats after a standing passenger is seated by the continuous boarding seating control unit 213 is calculated, and priority staying passengers are given priority among the staying passengers scheduled to board the train. In addition, the remaining passengers with the number of vacant seats are designated as seated passenger reservation passengers, and the remaining passengers as standing passenger reservation passengers. More specifically, when the number of seats is zero, all staying passengers are standing passenger reservation passengers, and seated passenger reservation passengers are zero. If the number of vacant seats is 1 or more and the number of priority staying passengers is less than the number of priority staying passengers, for example, a passenger with a randomly selected number of seats is designated as a reserved passenger for seating and all other priority staying passengers and all General passengers staying in Japan will be reserved passengers. If the number of vacant seats exceeds the number of priority staying passengers, a passenger whose seating number is the sum of all priority staying passengers and passengers selected at random from, for example, general staying passengers is regarded as a reserved passenger for seating. General passengers other than the above are reserved passengers for standing passengers.

乗車予約旅客は、乗車予約旅客データ４２０によって管理される。図１０は、乗車予約旅客データ４２０のデータ構成の一例を示す図である。図１０によれば、乗車予約旅客データ４２０は、対象線区内の全ての駅４２１及び当該駅４２１に停車する列車４２２毎に生成され、当該駅から当該列車に乗車予定の滞留旅客である着席乗車予約旅客の旅客ＩＤの一覧である着席乗車予約旅客リスト４２３と、立席乗車予約旅客の旅客ＩＤの一覧である立席乗車予約旅客リスト４２４と、を格納している、   Boarding reservation passengers are managed by boarding reservation passenger data 420. FIG. 10 is a diagram illustrating an example of a data configuration of the passenger reservation passenger data 420. According to FIG. 10, the boarding passenger data 420 is generated for every station 421 in the target line area and each train 422 that stops at the station 421, and seated passengers who are scheduled to board the train from the station. A seated passenger reservation passenger list 423 that is a list of passenger IDs of passenger reservation passengers and a standing passenger reservation passenger list 424 that is a list of passenger IDs of standing passenger reservation passengers are stored.

着席確率算出部２２０は、駅に停車中の列車について、継続乗車時の着席確率と、乗車時の着席確率とを算出する。具体的には、継続乗車時の着席確率については、継続乗車着席制御部２１３による立席の継続乗客の着席への変更がなされた後の空席数がゼロの場合、当該列車の当該駅における継続乗車時の着席確率を「０（ゼロ）」とし、空席数が１以上の場合には、継続乗車時の着席確率を「１」とする。   The seating probability calculation unit 220 calculates a seating probability at the time of continuous boarding and a seating probability at the time of boarding for a train stopped at the station. Specifically, regarding the seating probability at the time of continuous boarding, if the number of vacant seats after the continuous boarding seating control unit 213 has changed the seating of standing passengers to seating is zero, the continuation at that station of the train is continued. The seating probability when boarding is “0 (zero)”, and when the number of vacant seats is 1 or more, the seating probability when continuing boarding is “1”.

また、乗車時の着席確率については、滞留管理部２１５によって計数された立席予約旅客の人数が１以上の場合には、当該列車の当該駅における優先乗車時着席確率、及び、一般乗車時着席確率をともに「０（ゼロ）」とし、立席予約旅客の人数がゼロの場合は、優先乗車時着席確率、及び、一般乗車時着席確率をともに「１」とする。   As for the seating probability at the time of boarding, when the number of standing reservation passengers counted by the stay management unit 215 is 1 or more, the seating probability at the time of priority boarding at the corresponding station of the train and the seating at the time of general boarding When the probabilities are both “0 (zero)” and the number of standing reservation passengers is zero, both the priority seating probability during priority boarding and the seating probability during general boarding are both “1”.

着席確率算出部２２０によって算出された着席確率は、予測着席確率データ４４０として記憶される。図１１は、予測着席確率データ４４０のデータ構成の一例を示す図である。図１１によれば、予測着席確率データ４４０は、各列車４４１の各駅４４２における予測着席確率４４３として、継続乗車着席確率４４３ａと、優先乗車着席確率４４３ｂと、一般乗車着席確率４４３ｃとを対応付けて格納している。   The seating probability calculated by the seating probability calculation unit 220 is stored as predicted seating probability data 440. FIG. 11 is a diagram illustrating an example of a data configuration of the predicted seating probability data 440. According to FIG. 11, the predicted seating probability data 440 is obtained by associating a continuous boarding seating probability 443a, a priority boarding seating probability 443b, and a general boarding seating probability 443c as the predicted seating probability 443 at each station 442 of each train 441. Storing.

混雑率算出部２３０は、列車の駅間の混雑率を算出する。具体的には、各駅に停車中の列車それぞれについて、当該列車に乗車予定の滞留旅客が全て乗車したと仮定した場合の、当該駅から次の停車駅までの駅間の予測される混雑率を算出する。予測混雑率は、当該列車の定員人数に対する、当該列車の継続乗車の乗客の人数と、当該列車に乗車予定の滞留旅客の人数との合計の比率として算出する。   The congestion rate calculation unit 230 calculates the congestion rate between train stations. Specifically, for each train that is stopped at each station, the estimated congestion rate between stations from the station to the next stop station, assuming that all the passengers scheduled to board the train have boarded. calculate. The predicted congestion rate is calculated as the ratio of the total number of passengers on the train and the number of staying passengers scheduled to board the train with respect to the number of passengers on the train.

混雑率算出部２３０によって算出された混雑率は、予測混雑率データ４３０として記憶される。図１２は、予測混雑率データ４３０のデータ構成の一例を示す図である。図１２によれば、予測混雑率データ４３０は、列車４３１それぞれの駅間４３２それぞれに、予測混雑率４３３を対応付けて格納している。   The congestion rate calculated by the congestion rate calculation unit 230 is stored as predicted congestion rate data 430. FIG. 12 is a diagram illustrating an example of a data configuration of the predicted congestion rate data 430. According to FIG. 12, the predicted congestion rate data 430 stores the predicted congestion rate 433 in association with each station 432 of each train 431.

列車運行制御部２４０は、予め定められた計画ダイヤに従って、列車の仮想的な運行を制御する。   The train operation control unit 240 controls the virtual operation of the train according to a predetermined schedule.

ここで、計画ダイヤは、計画ダイヤデータ３２０として記憶されている。図１３は、計画ダイヤデータ３２０のデータ構成の一例を示す図である。図１３によれば、計画ダイヤデータ３２０は、列車毎に生成され、列車番号３２１と、列車種別３２２とを格納しているとともに、運行区間内での停車駅３２３それぞれに、着時刻３２４と、発時刻３２５とを対応付けて格納している。列車種別３２２は、各駅停車や快速といった停車駅による分類や、上り／下りといった進行方向の別である。   Here, the plan diagram is stored as plan diagram data 320. FIG. 13 is a diagram illustrating an example of a data configuration of the plan diagram data 320. According to FIG. 13, the plan schedule data 320 is generated for each train, stores the train number 321 and the train type 322, and arrives at each stop station 323 within the operation section, The departure time 325 is stored in association with each other. The train type 322 is classified according to the stop station such as each station stop or high speed, or the traveling direction such as up / down.

列車運行制御部２４０は、計画ダイヤを運用ダイヤとし、この運用ダイヤに従って列車の仮想的な運行（シミュレーション）を制御する。   The train operation control unit 240 uses the plan diagram as an operation diagram, and controls the virtual operation (simulation) of the train according to the operation diagram.

運用ダイヤは、運用ダイヤデータ３３０として記憶される。図１４は、運用ダイヤデータ３３０のデータ構成の一例を示す図である。図１４によれば、運用ダイヤデータ３３０は、列車毎に生成され、列車番号３３１と、列車種別３３２とを格納しているとともに、運行区間内での停車駅３３３それぞれに、着時刻３３４と、発時刻３３５と、発時更新３３６の有無とを対応付けて格納している。発時更新３３６は、対応する駅からの列車の発車時に、列車運行制御部２４０による当該列車の遅延制御や、着発時再探索部２５２による各旅客の列車乗継経路の再探索といった所定の処理が行われたか否かを示すフラグである。   The operation diagram is stored as operation diagram data 330. FIG. 14 is a diagram illustrating an example of a data configuration of the operation diagram data 330. According to FIG. 14, the operation diagram data 330 is generated for each train, stores the train number 331 and the train type 332, and arrives at each stop station 333 in the operation section, The departure time 335 and the presence / absence of the departure update 336 are stored in association with each other. The departure time update 336 is a predetermined value such as a delay control of the train by the train operation control unit 240 or a re-search of the train connection route of each passenger by the arrival-time re-search unit 252 when the train departs from the corresponding station. It is a flag indicating whether or not processing has been performed.

列車運行制御部２４０は、運用ダイヤに基づく列車の着時刻となると、当該列車が該当する駅に到着可能かを判断する。具体的には、運用ダイヤのうちのシミュレーション時刻が既に経過したダイヤ部分である実績ダイヤをもとに、当該駅における先行列車が発車済みであり、且つ、発車から所定時分が経過しているならば、到着可能と判断する。到着可能ならば、当該列車を到着させると判断して、現在時刻を実績の着時刻として実績ダイヤを更新する。一方、到着可能でないならば、当該列車の着時刻を所定時分（例えば、１分）遅らせた時刻として、運用ダイヤを修正する。   The train operation control unit 240 determines whether the train can arrive at the corresponding station when the arrival time of the train based on the operation schedule is reached. Specifically, the preceding train at the station has already started based on the actual schedule, which is the part of the operation schedule for which the simulation time has already passed, and a predetermined amount of time has passed since the departure. If so, it is determined that the arrival is possible. If arrival is possible, it is determined that the train will arrive, and the actual time schedule is updated with the current time as the actual arrival time. On the other hand, if it is not possible to arrive, the operation schedule is corrected with the arrival time of the train delayed by a predetermined time (for example, 1 minute).

実績ダイヤは、運用ダイヤのうちのシミュレーション時刻が既に経過して運用が完了したダイヤであり、実績ダイヤデータ３４０として記憶される。図１５は、実績ダイヤデータ３４０のデータ構成の一例を示す図である。図１５によれば、実績ダイヤデータ３４０は、計画ダイヤデータ３２０と同様に、列車毎に生成され、列車番号３４１と、列車種別３４２とを格納しているとともに、運行区間内での停車駅３４３それぞれに、着時刻３４４と、発時刻３４５とを対応付けて格納している。   The actual time diagram is a time diagram in which the simulation time has already elapsed and the operation is completed, and is stored as actual time diagram data 340. FIG. 15 is a diagram illustrating an example of a data configuration of the performance diagram data 340. According to FIG. 15, the actual time diagram data 340 is generated for each train and stores the train number 341 and the train type 342 as well as the planned diagram data 320, and the stop station 343 in the operation section. The arrival time 344 and the departure time 345 are stored in association with each other.

また、列車運行制御部２４０は、運用ダイヤに基づく列車の発時刻となると、当該列車を該当する駅から発車させるか否かを判断する。具体的には、当該列車に対する旅客の乗降に要する時間（乗降時間）を乗降客数等に基づいて算出し、この乗降時間を運用ダイヤ上の停車時分と比較する。乗降時間が停車時分以内ならば、停車時分内に旅客の乗降が終了して列車を発車させると判断し、現在時刻を当該列車の実績の発時刻として実績ダイヤを更新する。   Moreover, the train operation control part 240 will judge whether the said train is departed from an applicable station, when it becomes the departure time of the train based on an operation diagram. Specifically, the time required for passengers to get in and out of the train (boarding time) is calculated based on the number of passengers and the like, and the boarding time is compared with the stop time on the operation schedule. If the boarding / alighting time is within the stopping time, it is determined that passenger boarding / exiting is finished within the stopping time and the train is started, and the actual time schedule is updated with the current time as the actual time of the train.

一方、乗降時間が停車時分を超えるならば、停車時分内に旅客の乗降が終了せずに遅延が発生したと判断し、発生した遅延に合わせて運用ダイヤを修正する。すなわち、算出した乗降時間と、運用ダイヤ上の停車時分との差を、発生した遅延時分とする。そして、当該列車の当該駅の発時刻と、次の停車駅における着時刻とを、遅延時分だけ遅らせた時刻として運用ダイヤを修正する。その結果、次の停車駅における修正後の着時刻が発時刻より遅くなる場合には、当該列車の次の停車駅以降の運用ダイヤ全体を、遅延時分だけ遅らせるように修正する。   On the other hand, if the boarding / alighting time exceeds the stopping time, it is determined that the passenger has not finished getting on and off within the stopping time, and the operation diagram is corrected according to the generated delay. That is, the difference between the calculated getting-on / off time and the stopping time on the operation schedule is set as the generated delay time. Then, the operation diagram is corrected as a time obtained by delaying the departure time of the relevant station of the train and the arrival time at the next stop station by the delay time. As a result, when the corrected arrival time at the next stop station is later than the departure time, the entire operation schedule after the next stop station of the train is corrected so as to be delayed by the delay time.

乗降時間ｔｎは、例えば、当該列車の到着時の車内人数ｙ、降車人数ｘ１、及び、乗車人数ｘ２から、次式（１）に従って算出する。
Ｔｎ＝Ａ・（ｘ１＋ｘ２）・２＋Ｂ・（ｘ１＋ｘ２）＋Ｃ・ｙ ・・（１）
式（１）において、Ａ，Ｂ，Ｃは定数であり、例えば、Ａ＝−０．００３１、Ｂ＝０．７９０８、Ｃ＝０．００３、である。 The boarding / alighting time tn is calculated according to the following equation (1) from, for example, the number of passengers y at the arrival of the train, the number of passengers x1, and the number of passengers x2.
Tn = A. (X1 + x2) .2 + B. (X1 + x2) + C.y .. (1)
In the formula (1), A, B, and C are constants, for example, A = −0.0031, B = 0.7908, and C = 0.003.

列車は、列車データ３８０によって管理される。図１６は、列車データ３８０のデータ構成の一例を示す図である。図１６によれば、列車データ３８０は、列車毎に生成され、列車番号３８１と、運行区間３８２と、定員３８３と、座席数３８４と、運行状況３８５と、乗客データ３８６と、乗降実績データ３９０とを格納している。運行状況３８５、乗客データ３８６、および乗降実績データ３９０は、シミュレーションの進行に応じて随時更新されるデータである。   Trains are managed by train data 380. FIG. 16 is a diagram illustrating an example of the data configuration of the train data 380. According to FIG. 16, the train data 380 is generated for each train, and the train number 381, the operation section 382, the capacity 383, the number of seats 384, the operation status 385, the passenger data 386, and the boarding / exiting record data 390. And store. The operation status 385, passenger data 386, and boarding / exiting result data 390 are data updated as needed according to the progress of the simulation.

運行状況３８５は、当該列車の現在（シミュレーション時刻）の運行状況であり、具体的には、走行中ならばその駅間を格納し、停車中ならばその停車駅を格納している。乗客データ３８６は、当該列車に現在乗車中の旅客（乗客）についてのデータであり、立席の乗客の旅客ＩＤの一覧である立席乗客リスト３８７と、立席の乗客の旅客ＩＤの一覧である着席乗客リスト３８８とを含んでいる。   The operation status 385 is the current operation status (simulation time) of the train. Specifically, the operation status 385 stores between the stations when the train is running, and stores the stop station when the train is stopped. Passenger data 386 is data on passengers (passengers) currently on the train, and is a list of standing passengers 387 that is a list of passenger IDs of standing passengers and a list of passenger IDs of standing passengers. A seated passenger list 388 is included.

乗降実績データ３９０は、駅における旅客の乗車及び降車についてのデータであり、当該列車の停車駅３９１毎に生成され、当該駅に到着時の立席乗客の人数３９２と、着席乗客の人数３９３と、着時立席乗客人数３９２および着時着席乗客人数３９３の合計である着時合計乗客人数３９４と、立席乗客のうちの降車人数３９５と、着席乗客のうちの降車人数３９６と、立席降車人数３９５および着席降車人数３９６の合計である合計降車人数３９７と、立席乗車の人数３９８と、着席乗車の人数３９９と、立席乗車人数３９８および着席乗車人数３９９の合計である合計乗車人数４００と、発車時の立席乗車の人数４０１と、発車時の着席乗車の乗客人数４０２と、発時立席乗客人数４０１および発時着席乗客人数４０２の合計である発時合計乗客人数４０３と、発車時の乗車率４０４とを格納している。発時乗車率４０４は、定員３８３に対する発時合計乗客人数４０３の比率である。   The boarding / exiting result data 390 is data on passenger boarding and getting off at the station, and is generated for each stop station 391 of the train, and the number of standing passengers 392 and the number of seated passengers 393 when arriving at the station. , The total number of passengers at the time of arrival 394, which is the sum of the number of seated passengers 392 and the number of seated passengers 393, the number of passengers 395 of the standing passengers, the number of passengers 396 of the seated passengers, The total number of passengers 395, the total number of passengers 396, the total number of passengers 396, the number of passengers 398, the number of seated passengers 399, the number of seated passengers 399, the number of seated passengers 398, and the number of seated passengers 399 400, the number 401 of standing passengers at departure, the number 402 of passengers seated at departure, the total number of standing passengers 401 and departure seated passengers 402 at departure A total number of passengers 403 stores and occupancy 404 at the time of departure. The departure boarding rate 404 is a ratio of the total number of passengers 403 at departure to the capacity 383.

図６に戻り、列車乗継経路探索部２５０は、出現時探索部２５１と、着発時再探索部２５２とを有し、計画ダイヤや運用ダイヤといった各種のダイヤをもとに、旅客の行動属性に応じた列車乗継経路を探索する。   Returning to FIG. 6, the train transit route search unit 250 has an appearance search unit 251 and an arrival re-search unit 252, and passenger behavior based on various types of schedules such as a plan schedule and an operation schedule. Search for train connection routes according to attributes.

出現時探索部２５１は、出現制御部２１１によって出現された旅客を対象として、当該旅客の出現駅から目的駅に至る列車乗継経路の探索を行う。具体的には、対象旅客の出現時刻以降の所定の時間範囲（例えば、２時間）の運用ダイヤに基づいて、出現駅から目的駅までの駅範囲となる経路探索ネットワークを初期生成する。   The appearance search unit 251 searches for a train connection route from the appearance station of the passenger to the destination station for the passenger that appears by the appearance control unit 211. Specifically, based on an operation diagram in a predetermined time range (for example, 2 hours) after the appearance time of the target passenger, a route search network that is a station range from the appearance station to the destination station is initially generated.

次いで、参照シミュレーションの結果を用いて、初期生成した経路探索ネットワークの着席アーク、及び、駅間アークのコストを変更する。参照シミュレーションとは、同一の計画ダイヤに対して過去に行われた旅客流動シミュレーションである。すなわち、着席アークそれぞれに対応する着席確率を、参照シミュレーションの結果を用いて算出する。着席アークのうち、着席移行停車アーク２２ｃの着席確率（継続乗車着席確率）は、該当列車の該当駅への到着時の立席の継続乗客の人数に対する停車中に立席から着席に移行した乗客の人数の割合として算出する。優先着席乗車アーク２６ａの着席確率は、該当駅における該当列車に乗車予定の優先滞留旅客の人数に対する、該当列車に乗車して着席した優先滞留旅客の人数の割合として算出する。一般着席乗車アーク２６ｃの着席確率は、該当駅における該当列車に乗車予定の一般滞留旅客の人数に対する、該当列車に乗車して着席した一般滞留旅客の人数として算出する。   Next, by using the result of the reference simulation, the cost of the seating arc and the station-to-station arc of the initially generated route search network is changed. The reference simulation is a passenger flow simulation performed in the past for the same planning diagram. That is, the seating probability corresponding to each seating arc is calculated using the result of the reference simulation. Among the seating arcs, the seating probability (continuous boarding seating probability) of the seating transition stop arc 22c is a passenger who has transitioned from standing to seating while stopping for the number of standing passengers at the time of arrival at the relevant station of the corresponding train. Calculated as a percentage of the number of people. The seating probability of the priority seating arc 26a is calculated as the ratio of the number of priority staying passengers seated on the corresponding train to the number of priority staying passengers scheduled to board the corresponding train at the corresponding station. The seating probability of the general seating arc 26c is calculated as the number of general staying passengers who have boarded and seated in the corresponding train with respect to the number of general staying passengers scheduled to board the corresponding train at the corresponding station.

さらに、予測着席確率データ４４０を参照し、着席アークのうち、着席確率算出部２２０によって着席確率が算出されている着席アークについては、この着席確率に変更する。   Further, referring to the predicted seating probability data 440, among the seating arcs, the seating arcs for which the seating probability is calculated by the seating probability calculation unit 220 are changed to this seating probability.

なお、参照シミュレーションを用いない場合には、各着席アークに対応する着席確率を全て「０（ゼロ）」とする。   When the reference simulation is not used, all seating probabilities corresponding to each seating arc are set to “0 (zero)”.

そして、各着席アークについて、対応する着席確率が、当該旅客の行動属性に応じた着席可能認知確率未満である場合、当該着席アークのコストを「∞（無限大：非常に大きな値）」に変更する。   For each seating arc, if the corresponding seating probability is less than the seatable recognition probability according to the behavior attribute of the passenger, the cost of the seating arc is changed to “∞ (infinity: very large value)” To do.

着席可能認知確率は、行動属性設定テーブル３６０にて定められている。図１７は、行動属性設定テーブル３６０のデータ構成の一例を示す図である。図１７によれば、行動属性設定テーブル３６０は、行動属性３６１と、旅客が着席可能とみなす着席確率である着席可能認知確率３６２とを対応付けて格納している。この着席可能認知確率３６２によって、旅客が着席可能とみなす着席確率の閾値（下限値）が設定される。   The seatable recognition probability is determined in the behavior attribute setting table 360. FIG. 17 is a diagram illustrating an example of a data configuration of the behavior attribute setting table 360. According to FIG. 17, the behavior attribute setting table 360 stores a behavior attribute 361 and a seating possibility recognition probability 362, which is a seating probability that the passenger considers seatable. A seating probability threshold value (lower limit value) that the passenger considers seatable is set by the seatable recognition probability 362.

また、駅間アークについては、参照シミュレーションの結果を参照して算出する。例えば、混雑率は、該当列車の定員に対する該当列車の該当駅間の乗客の人数の割合として算出する。更に、予測混雑率データ４３０を参照し、駅間アークのうち、混雑率算出部２３０によって予測混雑率が算出されている駅間アークについては、この予測混雑率に変更する。   The station-to-station arc is calculated with reference to the result of the reference simulation. For example, the congestion rate is calculated as a ratio of the number of passengers between corresponding stations of the corresponding train with respect to the capacity of the corresponding train. Furthermore, with reference to the predicted congestion rate data 430, among the arcs between stations, the inter-station arcs for which the predicted congestion rate is calculated by the congestion rate calculation unit 230 are changed to this predicted congestion rate.

そして、各駅間アークについて、混雑率を変数とする所定の混雑不効用関数Ｆに基づいて混雑不効用値Ｕｃを算出し、算出した混雑不効用値Ｕｃに応じて着席駅間アーク２０ａ及び立席駅間アーク２０ｂのそれぞれのコスト（重みづけ）を変更する。このとき、立席駅間アーク２０ｂのほうが着席駅間アーク２０ａよりもコストが大きくなるようにする。   Then, for each arc between the stations, a congestion invalidity value Uc is calculated based on a predetermined congestion invalidity function F having the congestion rate as a variable, and the seated inter-station arc 20a and the standing seat are set according to the calculated congestion invalidity value Uc. Each cost (weighting) of the arc 20b between stations is changed. At this time, the cost of the standing station arc 20b is set to be higher than that of the seated station arc 20a.

なお、参照シミュレーションを用いない場合には、混雑率に応じた駅間アークのコスト変更を実施しない。   In addition, when not using a reference simulation, the cost change of the arc between stations according to a congestion rate is not implemented.

そして、コストを変更した後の経路探索ネットワークに基づいて、出現駅から目的駅に至る経路であって、経由する各アークのコストが最小となる経路を、対象旅客の列車乗継経路として設定する。   Then, based on the route search network after changing the cost, the route from the appearing station to the destination station and the cost of each passing arc is minimized is set as the train connection route of the target passenger. .

着発時再探索部２５２は、各駅への列車の着発時に、当該駅に係る全ての旅客を対象とした列車乗継経路の再探索を行う。このとき、再探索の対象となる旅客は、当該駅に停車中の列車の乗客、及び、当該駅の滞留旅客である。   The arrival-time re-search unit 252 re-searches the train connection route for all passengers associated with the station when the train arrives at each station. At this time, the passengers to be re-searched are the passengers of the train stopped at the station and the staying passengers at the station.

具体的には、対象の旅客それぞれについて、出現時探索部２５１による列車乗継経路の探索と同様に、目的駅までの列車乗継経路を探索する。すなわち、対象旅客の現在駅から目的駅までの駅範囲となる経路探索ネットワークを初期生成する。このとき、対象の旅客が停車中の列車の着席乗客ならば、当該列車の当該駅への着席着ノード１０ａを出発ノードとし、立席乗客ならば、当該列車の当該駅への立席着ノード１０ｂを出発ノードとする経路探索ネットワークを生成する。或いは、対象の旅客が一般滞留旅客ならば、当該駅における現在時刻（現在のシミュレーション時刻の意）の直後の一般滞留ノード１４ｂを出発ノードとし、優先滞留旅客ならば、当該駅における現在時刻の直後の優先滞留ノード１４ａを出発ノードとする経路探索ネットワークを生成する。更に、対象の旅客が、停車中の列車に関する着席乗車予約旅客又は立席乗車予約ならば、該当する列車の着席乗車予約ノード１６ａ又は立席乗車予約ノード１６ｂを出発ノードとする経路探索ネットワークを生成する。   Specifically, for each target passenger, the train connection route to the destination station is searched in the same manner as the train connection route search by the appearance search unit 251. That is, a route search network that is a station range of the target passenger from the current station to the destination station is initially generated. At this time, if the target passenger is a seated passenger of a stopped train, the seated node 10a at the corresponding station of the train is set as a departure node, and if the target passenger is a standing passenger, the seated node at the corresponding station of the train is used. A route search network starting from 10b is generated. Alternatively, if the target passenger is a general stay passenger, the general stay node 14b immediately after the current time (meaning the current simulation time) at the station is set as the departure node, and if the target passenger is a priority stay passenger, immediately after the current time at the station. A route search network having the priority staying node 14a as a departure node is generated. Furthermore, if the target passenger is a seated boarding reservation passenger or standing boarding reservation for a stopped train, a route search network is generated using the seating boarding reservation node 16a or the standing boarding reservation node 16b of the corresponding train as a departure node. To do.

そして、生成した経路探索ネットワークにおいて、参照シミュレーションの結果や、予測着席確率データ４４０、予測混雑率データ４３０を用いて、着席アークや駅間アークのコストを変更し、経路探索ネットワークに基づいて、現在駅から目的駅までの経路を探索し、現在駅以降の列車乗継経路を更新する。   Then, in the generated route search network, the cost of the seating arc and the inter-station arc is changed using the result of the reference simulation, the predicted seating probability data 440, and the predicted congestion rate data 430, and based on the route search network, the current The route from the station to the destination station is searched, and the train connection route after the current station is updated.

不効用値算出部２６０は、計画ダイヤや運用ダイヤといった各種ダイヤに対する旅客の不効用値を算出する。ダイヤに対する旅客の不効用値Ｕは、次式（２）により与えられる。

Figure 2015229459
式（２）において、α，β，γ，δは定数であり、例えば、α＝０．０１９，β＝４．５２，γ＝５．６３，δ＝１．２０２、である。また、ｊは、旅客の出現駅から目的駅に至る実際の列車乗継経路中の列車で通過した駅間の集合である。ｔｊは、該当する駅間ｊの走行時間（乗車時間）であり、ｃｊは、該当する駅間ｊの乗車率である。Ｎは、旅客の列車乗継経路中の乗り換え回数である。ＴＷは、旅客の待ち時間であり、列車乗継経路中の各乗り換えの際の待ち時間の総和である。ＴＲは、乗車時間であり、列車乗継経路中に乗車した各列車の乗車時間の総和である。不効用値算出部２６０が算出した不効用値は、不効用値データ４５０として記憶される。 The invalid value calculation unit 260 calculates a passenger's invalid value for various types of schedules such as a schedule diagram and an operation diagram. The passenger's invalid value U for the diamond is given by the following equation (2).
Figure 2015229459
 In Expression (2), α, β, γ, and δ are constants, for example, α = 0.199, β = 4.52, γ = 5.63, δ = 1.202. In addition, j is a set of stations that have passed through a train in an actual train connection route from a station where a passenger appears to a destination station. t j is the travel time (riding time) between the corresponding stations j , and c j is the boarding rate of the corresponding j between stations. N is the number of transfers in the passenger's train connection route. TW is the waiting time of the passenger, and is the total waiting time at each transfer in the train connection route. T R is the traveling time is the sum of the traveling time of the train and riding in the train transit path. The invalid value calculated by the invalid value calculator 260 is stored as invalid value data 450.

記憶部３００は、処理部２００がシミュレーション装置１を統合的に制御するための諸機能を実現するためのシステムプログラムや、本実施形態を実現するための各種のプログラムやデータ等を記憶するとともに、処理部２００の作業領域として用いられ、処理部２００が各種プログラムに従って実行した演算結果や、操作入力部１１０からの入力データ等が一時的に格納される。本実施形態では、記憶部３００には、シミュレーションプログラム３１０と、計画ダイヤデータ３２０と、運用ダイヤデータ３３０と、実績ダイヤデータ３４０と、旅客出現確率テーブル３５０と、行動属性設定テーブル３６０と、旅客管理データ３７０と、列車データ３８０と、滞留旅客データ４１０と、乗車予約旅客データ４２０と、予測混雑率データ４３０と、予測着席確率データ４４０と、不効用値データ４５０とが記憶される、   The storage unit 300 stores a system program for realizing various functions for the processing unit 200 to control the simulation apparatus 1 in an integrated manner, various programs and data for realizing the present embodiment, and the like. It is used as a work area of the processing unit 200 and temporarily stores calculation results executed by the processing unit 200 according to various programs, input data from the operation input unit 110, and the like. In the present embodiment, the storage unit 300 stores the simulation program 310, the plan diagram data 320, the operation diagram data 330, the performance diagram data 340, the passenger appearance probability table 350, the behavior attribute setting table 360, and the passenger management. Data 370, train data 380, stay passenger data 410, boarding reservation passenger data 420, predicted congestion rate data 430, predicted seating probability data 440, and invalid value data 450 are stored.

［処理の流れ］
（Ａ）シミュレーション処理
図１８は、本実施形態の旅客流動シミュレーション処理の流れを説明するためのフローチャートである。この処理は、処理部２００が、シミュレーションプログラム３１０を実行することで実現される。 [Process flow]
(A) Simulation Process FIG. 18 is a flowchart for explaining the flow of the passenger flow simulation process of the present embodiment. This process is realized by the processing unit 200 executing the simulation program 310.

図１８によれば、先ず、初期設定として、シミュレーション時刻である現在時刻ｔを、所定の開始時刻ｔ０に設定する（ステップＡ１）。また、各列車の計画ダイヤを運用ダイヤに設定する（ステップＡ３）。   According to FIG. 18, first, as an initial setting, the current time t, which is a simulation time, is set to a predetermined start time t0 (step A1). In addition, the schedule of each train is set as an operation schedule (step A3).

次いで、出現制御部２１１が旅客出現処理を行って、各駅に旅客を出現させる。すなわち、対象線区内の全ての駅を対象としたループＡの処理を行う。ループＡでは、旅客出現確率テーブル３５０に従って、行動属性毎に、当該駅を出現駅とし他の各駅を目的駅とする旅客の出現人数を決定する（ステップＡ５）。次いで、出現させると決定した各旅客を対象としたループＢの処理を行う。ループＢでは、出現時探索部２５１が、当該旅客を対象とした経路探索処理（図２３参照）を行って、当該旅客の出現駅から目的駅に至る列車乗継経路を設定する（ステップＡ７）。そして、当該旅客を当該駅に出現させる（ステップＡ９）。ループＢ，ループＡはこのように行われる。   Next, the appearance control unit 211 performs passenger appearance processing to cause passengers to appear at each station. That is, the loop A process is performed for all stations in the target line section. In the loop A, according to the passenger appearance probability table 350, the number of appearances of passengers having the station as an appearing station and the other stations as target stations is determined for each behavior attribute (step A5). Next, processing of loop B is performed for each passenger determined to appear. In Loop B, the appearance search unit 251 performs route search processing for the passenger (see FIG. 23), and sets a train connection route from the station where the passenger appears to the destination station (step A7). . Then, the passenger appears at the station (step A9). Loop B and loop A are performed in this way.

続いて、対象線区内の全ての駅を対象とするループＣの処理を行う。ループＣでは、着時処理（図１９参照）を行う（ステップＡ１１）。次いで、発時処理（図２０〜図２２参照）を行う（ステップＡ１３）。ループＣはこのように行われる。   Subsequently, the process of Loop C for all stations in the target line section is performed. In the loop C, the arrival process (see FIG. 19) is performed (step A11). Next, a departure process (see FIGS. 20 to 22) is performed (step A13). Loop C is performed in this way.

対象線区内の全ての駅を対象としたループＣの処理を終了とすると、続いて、列車運行制御部２４０が、現在時刻ｔが所定の終了時刻ｔｅに達したかを判断する。終了時刻ｔｅに達していないならば（ステップＡ１５：ＮＯ）、現在時刻ｔを所定時分Δｔ（例えば、１分）だけ進め（ステップＡ１７）、ステップＡ５に戻る。一方、現在時刻ｔが終了時刻ｔｅに達しているならば（ステップＡ１５：ＹＥＳ）、不効用値算出部２６０が、計画ダイヤ及び実績ダイヤそれぞれに対する各旅客の不効用値を算出する（ステップＡ１９）。以上の処理を行うと、本処理は終了となる。   When the processing of the loop C for all stations in the target line area is finished, the train operation control unit 240 subsequently determines whether the current time t has reached a predetermined end time te. If the end time te has not been reached (step A15: NO), the current time t is advanced by a predetermined time Δt (for example, 1 minute) (step A17), and the process returns to step A5. On the other hand, if the current time t has reached the end time te (step A15: YES), the invalid value calculation unit 260 calculates the invalid value of each passenger for each of the planned and actual diamonds (step A19). . When the above processing is performed, this processing ends.

（Ｂ）着時処理
図１９は、着時処理の流れを説明するフローチャートである。先ず、列車運行制御部２４０が、現在時刻ｔが、運用ダイヤに基づく何れかの列車（着列車）が何れかの駅への着時刻となったかを判断する。着時刻ならば（ステップＢ１：ＹＥＳ）、続いて、実績ダイヤ等を参照して、当該列車が到着可能か否かを判断する。到着可能でないならば（ステップＢ３：ＮＯ）、当該列車の当該駅への着時刻を所定時分（例えば、１分）遅らせて、運用ダイヤを更新する（ステップＢ３５）。 (B) Wearing process FIG. 19 is a flowchart for explaining the flow of the wearing process. First, the train operation control unit 240 determines whether the current time t is the arrival time at which station any train (arrival train) based on the operation schedule. If it is the arrival time (step B1: YES), it is then determined whether or not the train can arrive with reference to a performance diagram or the like. If arrival is not possible (step B3: NO), the operation schedule is updated by delaying the arrival time of the train at the station by a predetermined time (for example, 1 minute) (step B35).

一方、到着可能ならば（ステップＢ３：ＹＥＳ）、現在時刻ｔを当該列車の実績の着時刻として実績ダイヤを更新する（ステップＢ５）。続いて、着発時再探索部２５２が、当該駅にかかる全ての旅客を対象とした経路探索処理（図２３参照）を行って、各旅客の当該駅以降の列車乗継経路を更新する（ステップＢ７）。次いで、降車制御部２１２が、当該列車の乗客のうち、当該駅で降車する乗客を判断し、判断した乗客を当該列車から降車させる（ステップＢ９）。   On the other hand, if arrival is possible (step B3: YES), the actual time schedule is updated with the current time t as the actual arrival time of the train (step B5). Subsequently, the incoming / outgoing re-search unit 252 performs route search processing (see FIG. 23) for all passengers at the station, and updates the train connection routes after the station of each passenger ( Step B7). Next, the getting-off control unit 212 determines passengers getting off at the station among passengers of the train, and makes the determined passengers get off the train (step B9).

続いて、継続乗車着席制御部２１３が、当該列車の空席数を算出する（ステップＢ１１）。また、当該列車の乗客のうち、立席の継続乗客人数を算出する（ステップＢ１３）。そして、空席数と立席の継続乗車人数とを比較し、空席数が立席の継続乗客人数以上ならば（ステップＢ１５：ＹＥＳ）、全ての立席の継続乗客を着席させる（ステップＢ１７）。一方、空席数が立席の継続乗客人数未満ならば（ステップＢ１５：ＮＯ）、立席の継続乗客のうち、空席数だけの乗客を着席させる（ステップＢ１９）。そして、着席確率算出部２２０が、当該列車の当該駅における継続乗車着席確率を「０」とする（ステップＢ２１）。   Subsequently, the continuous boarding / seating control unit 213 calculates the number of vacant seats of the train (step B11). In addition, the number of standing passengers among the passengers of the train is calculated (step B13). Then, the number of vacant seats and the number of standing passengers are compared. If the number of vacant seats is equal to or greater than the number of continuing passengers standing (step B15: YES), all standing passengers are seated (step B17). On the other hand, if the number of vacant seats is less than the number of standing passengers (step B15: NO), only the number of vacant seats out of the standing passengers are seated (step B19). And the seating probability calculation part 220 sets the continuous boarding seating probability in the said station of the said train to "0" (step B21).

その後、滞留管理部２１５が、再度、当該列車の空席数を算出する（ステップＢ２３）。そして、当該駅の当該列車に乗車予定の滞留旅客のうち、優先滞留旅客から優先的に、空席数だけの滞留旅客を着席乗車予約旅客とし（ステップＢ２５）、それ以外の滞留旅客を立席乗車予約旅客とする（ステップＢ２７）。その結果、立席乗車予約旅客人数が「１」以上ならば（ステップＢ２９：ＹＥＳ）、着席確率算出部２２０が、当該駅の当該列車への一般乗車着席確率、及び、優先乗車着席確率をともに「０」とする（ステップＢ３１）。一方、立席乗車予約旅客数が「０」ならば（ステップＢ２９：ＮＯ）、着席確率算出部２２０は、当該駅の当該列車への一般乗車着席確率、及び、優先乗車着席確率をともに「１」とする（ステップＢ３３）。以上の処理を行うと、着時処理を終了する。   Thereafter, the stay management unit 215 calculates again the number of vacant seats of the train (step B23). Then, among the staying passengers scheduled to board the train at the station, the staying passengers with the number of vacant seats are given priority as priority seating passengers (step B25), and the other staying passengers are standing on board. A reserved passenger is set (step B27). As a result, if the number of standing passenger reservation passengers is “1” or more (step B29: YES), the seating probability calculation unit 220 displays both the general boarding seating probability and the priority boarding seating probability of the train at the station. “0” is set (step B31). On the other hand, if the number of standing passenger reservation passengers is “0” (step B29: NO), the seating probability calculation unit 220 sets both the general boarding seating probability and the priority boarding seating probability to the train at the station to “1”. (Step B33). When the above process is performed, the arrival process is terminated.

（Ｃ）発時処理
図２０〜図２２は、発時処理の流れを説明するフローチャートである。先ず、列車運行制御部２４０が、現在時刻ｔが運用ダイヤで定められる何れかの列車（発列車）の何れかの駅からの発時刻であるかを判断する。発時刻ならば（ステップＣ１：ＹＥＳ）、当該列車について当該駅での発時更新済みであるか否かを判断する。発時更新済みならば（ステップＣ３：ＹＥＳ）、図２１のステップＤ１７に移行する。 (C) Departure process FIG. 20 to FIG. 22 are flowcharts for explaining the flow of the departure process. First, the train operation control unit 240 determines whether the current time t is the departure time from any station of any train (departure train) determined by the operation schedule. If it is the departure time (step C1: YES), it is determined whether or not the train has been updated at the station for departure. If updated at the time of departure (step C3: YES), the process proceeds to step D17 in FIG.

発時更新済みでないならば（ステップＣ３：ＮＯ）、滞留管理部２１５が、当該駅の一般滞留旅客のうち、滞留時間が所定時間以上の旅客を、優先滞留旅客とする（ステップＣ５）。続いて、着発時再探索部２５２が、当該駅にかかる全ての旅客を対象とした経路探索処理（図２３参照）を行って、各旅客の当該駅以降の列車乗継経路を更新する（ステップＣ７）。そして、降車制御部２１２が、この列車乗継経路の更新の結果、当該列車の乗客のうち、新たに当該駅において降車予定となった乗客を降車させる（ステップＣ９）。   If it has not been updated at the time of departure (step C3: NO), the stay management unit 215 sets a passenger having a stay time of a predetermined time or more among the general stay passengers at the station as a priority stay passenger (step C5). Subsequently, the incoming / outgoing re-search unit 252 performs route search processing (see FIG. 23) for all passengers at the station, and updates the train connection routes after the station of each passenger ( Step C7). And the getting-off control part 212 gets off the passenger newly scheduled to get off at the said station among the passengers of the said train as a result of the update of this train connection path | route (step C9).

続いて、滞留管理部２１５が、当該列車の空席数を算出する（ステップＣ１１）。そして、当該発列車に乗車予定の滞留旅客のうち、優先滞留旅客を優先的に、空席数だけの旅客を着席乗車予約旅客とし（ステップＣ１３）、それ以外の旅客を立席乗車予約旅客とする（ステップＣ１５）。その結果、立席乗車予約旅客人数が「１」以上ならば（ステップＣ１７：ＹＥＳ）、着席確率算出部２２０が、当該駅の当該列車への一般乗車着席確率、及び、優先乗車着席確率を「０」とする（ステップＣ１９）。一方、立席乗車予約人数が「０」ならば（ステップ１７：ＮＯ）、当該駅の当該列車への一般乗車着席確率、及び、優先乗車着席確率を「１」とする（ステップＣ２１）。   Subsequently, the stay management unit 215 calculates the number of vacant seats of the train (step C11). Of the staying passengers scheduled to board the departure train, priority staying passengers are given priority, passengers with the number of vacant seats are designated as seated passenger reservation passengers (step C13), and other passengers are designated as standing passenger reservation passengers. (Step C15). As a result, if the number of passengers reserved for standing seating is “1” or more (step C17: YES), the seating probability calculation unit 220 sets the general boarding seating probability and the priority boarding seating probability to the train at the station. 0 "(step C19). On the other hand, if the standing seating reservation number is “0” (step 17: NO), the general boarding seating probability and the priority boarding seating probability to the train at the station are set to “1” (step C21).

その後、混雑率算出部２３０が、当該列車の乗車予約旅客の全てが当該列車に乗車したと仮定した場合の、当該駅から次の停車駅までの駅間の予測混雑率を算出する（ステップＣ２３）。   Thereafter, the congestion rate calculation unit 230 calculates the predicted congestion rate between stations from the station to the next stop station assuming that all of the passengers on the train have boarded the train (step C23). ).

続いて、図２１に示すように、着発時再探索部２５２が、当該駅にかかる全ての旅客を対象とした経路探索処理（図２３参照）を行って、各旅客の当該駅以降の列車乗継経路を更新する（ステップＤ１）。そして、降車制御部２１２が、この列車乗継経路の更新の結果、当該列車の乗客のうち、新たに当該駅において降車予定となった乗客を降車させる（ステップＤ３）。   Subsequently, as shown in FIG. 21, the arrival and departure time re-search unit 252 performs route search processing (see FIG. 23) for all passengers on the station, and trains for each passenger after the station. The connection route is updated (step D1). Then, as a result of the update of the train connection route, the getting-off control unit 212 gets off the passengers newly scheduled to get off at the station among the passengers of the train (step D3).

次いで、列車運行制御部２４０が、当該駅における当該列車降車人数と、乗車予定人数とから、当該発列車の当該駅での旅客の乗降に要する乗降時間を算出する（ステップＤ５）。そして、算出した乗降時間を運用ダイヤにおける停車時分と比較することで、発遅延が生じるかを判断する（ステップＤ７）。   Next, the train operation control unit 240 calculates the boarding / alighting time required for passengers to get on and off at the station of the departure train from the number of passengers getting off at the station and the number of people scheduled to board (step D5). Then, by comparing the calculated boarding / alighting time with the stopping time in the operation diagram, it is determined whether or not a departure delay occurs (step D7).

発遅延が生じるならば（ステップＤ９：ＹＥＳ）、算出した乗降時間と運用ダイヤにおける停車時分との差を遅延時分として算出し（ステップＤ１１）、当該発列車の発時刻をこの遅延時分だけ遅延させて運用ダイヤを修正する（ステップＤ１３）。このとき、この運用ダイヤの修正に伴い、必要に応じて他の列車の運用ダイヤを修正する。そして、当該発列車の当該駅の発時更新を“済み”とする（ステップＤ１５）。   If a departure delay occurs (step D9: YES), the difference between the calculated boarding / alighting time and the stop time on the operation schedule is calculated as a delay time (step D11), and the departure time of the departure train is determined as the delay time. The operation diagram is corrected with a delay of only (step D13). At this time, along with the correction of this operation diagram, the operation diagrams of other trains are corrected as necessary. And the update at the time of the departure of the said train of the said departure train shall be "completed" (step D15).

一方、発遅延が生じないならば（ステップＤ９：ＮＯ）、継続乗車着席制御部２１３が、当該発列車の空席数を算出する（ステップＤ１７）。その結果、空席が有る場合、当該発列車の立席の継続乗客のうち、空席数の乗客を着席させる（ステップＤ１９）。   On the other hand, if there is no departure delay (step D9: NO), the continuous boarding seating control unit 213 calculates the number of vacant seats of the departure train (step D17). As a result, when there are vacant seats, among the continuation passengers standing on the departure train, the number of vacant passengers is seated (step D19).

続いて、滞留管理部２１５が、再度、当該列車の空席数を算出する（ステップＤ２１）。そして、当該列車に乗車予定の滞留旅客のうち、空席数の旅客を着席乗車予約旅客とし、空整数以上の滞留旅客を、立席乗車予約旅客とする（ステップＤ２３）。   Subsequently, the stay management unit 215 calculates again the number of vacant seats of the train (step D21). Then, among the staying passengers scheduled to board the train, the number of vacant passengers is set as a seated boarding reservation passenger, and the staying passengers equal to or larger than the empty integer are set as standing boarding reservation passengers (step D23).

その後、乗車制御部２１４が、立席乗車予約旅客を立席乗客とし、着席乗車予約旅客を着席乗客として、乗車予約旅客を当該列車に乗車させる（ステップＤ２７）。そして、列車運行制御部２４０が、現在時刻ｔを当該列車の実績の発時刻として実績ダイヤを更新する（ステップＤ２９）。   Thereafter, the boarding control unit 214 causes the reserved passenger to board the train, with the standing passenger reservation passenger as the standing passenger and the seated passenger reservation passenger as the seated passenger (step D27). Then, the train operation control unit 240 updates the actual time schedule with the current time t as the departure time of the actual result of the train (step D29).

続いて、図２２に示すように、当該駅に停車中の他の列車が存在するかを判断する。停車中の列車が存在するならば（ステップＥ１：ＹＥＳ）、滞留管理部２１５が、当該駅の一般滞留旅客のうち、滞留時間が所定時間以上の旅客を優先滞留旅客とする（ステップＥ３）。次いで、着発時再探索部２５２が、当該駅にかかる全ての旅客を対象とした経路探索処理（図２３参照）を行って、各旅客の当該駅以降の列車乗継経路を更新する（ステップＥ５）。   Subsequently, as shown in FIG. 22, it is determined whether there is another train stopped at the station. If there is a stopped train (step E1: YES), the stay management unit 215 sets a passenger having a stay time of a predetermined time or more as a priority stay passenger among the general stay passengers at the station (step E3). Next, the incoming / outgoing re-search unit 252 performs route search processing (see FIG. 23) for all passengers at the station, and updates the train connection routes after the station of each passenger (step S31). E5).

続いて、当該駅に停車中の他の各列車を対象としたループＤの処理を行う。ループＤでは、降車制御部２１２が、この列車乗継経路の更新の結果、当該列車の乗客のうち、新たに当該駅において降車予定となった乗客を降車させる（ステップＥ７）。次いで、滞留管理部２１５が、当該列車の空席数を算出する（ステップＥ９）。そして、当該発列車に乗車予定の滞留旅客のうち、優先滞留旅客を優先的に、空席数だけの旅客を着席乗車予約旅客とし（ステップＥ１１）、それ以外の旅客を立席乗車予約旅客とする（ステップＥ１３）。   Then, the process of the loop D which makes object each other train stopped at the said station is performed. In the loop D, the getting-off control unit 212 gets off the passengers newly scheduled to get off at the station among the passengers of the train as a result of updating the train connection route (step E7). Next, the stay management unit 215 calculates the number of vacant seats of the train (step E9). Of the staying passengers scheduled to board the departure train, priority staying passengers are given priority, passengers with the number of vacant seats are designated as seated passenger reservation passengers (step E11), and other passengers are designated as standing passenger reservation passengers. (Step E13).

その結果、立席乗車予約旅客人数が「１」以上ならば（ステップＥ１５：ＹＥＳ）、着席確率算出部２２０が、当該駅の当該列車への一般乗車着席確率、及び、優先乗車着席確率を「０」とする（ステップＥ１７）。一方、立席乗車予約人数が「０」ならば（ステップＥ１５：ＮＯ）、当該駅の当該列車への一般乗車着席確率、及び、優先乗車着席確率を「１」とする（ステップＥ１９）。ループＤはこのように行われる。停車中の列車の全てを対象としたループＤの処理を終了すると、発時処理を終了する。   As a result, if the number of standing passenger reservation passengers is “1” or more (step E15: YES), the seating probability calculation unit 220 sets the general boarding seating probability and the priority boarding seating probability to the train at the station. 0 "(step E17). On the other hand, if the standing passenger reservation number is “0” (step E15: NO), the general boarding seating probability and the priority boarding seating probability to the train at the station are set to “1” (step E19). Loop D is performed in this way. When the loop D process for all the stopped trains is completed, the departure process is terminated.

（Ｄ）経路探索処理
図２３は、経路探索処理の流れを説明するフローチャートである。図２３によれば、対象旅客それぞれについてのループＥの処理を行う。ループＥでは、運用ダイヤに基づいて、対象旅客の現在駅を出発駅とし、目的駅までの駅範囲となる、経路探索ネットワークを初期生成する（ステップＦ１）。このとき、各アークのコストは、始端ノードと終端ノードとの基準時刻の差とする。次いで、参照シミュレーションの有無を判断する。参照シミュレーションが無いならば（ステップＦ３：ＮＯ）、経路探索ネットワークに含まれる全ての着席アークのコストを「∞（非常に大きな値）」に変更する（ステップＦ２３）。 (D) Route Search Processing FIG. 23 is a flowchart illustrating the flow of route search processing. According to FIG. 23, the processing of loop E is performed for each target passenger. In the loop E, a route search network is initially generated based on the operation schedule, with the current station of the target passenger as the departure station and the station range to the target station (step F1). At this time, the cost of each arc is the difference in the reference time between the start node and the end node. Next, it is determined whether or not there is a reference simulation. If there is no reference simulation (step F3: NO), the cost of all seating arcs included in the route search network is changed to “∞ (very large value)” (step F23).

一方、参照シミュレーションが有るならば（ステップＦ３：ＹＥＳ）、経路探索ネットワークに含まれる着席アークそれぞれを対象としたループＦの処理を行う。ループＦでは、参照シミュレーションの結果をもとに、対象着席アークに対応する着席確率を算出する（ステップＦ５）。次いで、対応する予測着席確率が算出されているかを判断し、算出されているならば（ステップＦ７：ＹＥＳ）、着席確率を、この予測着席確率に変更する（ステップＦ９）。算出されていないならば（ステップＦ７：ＮＯ）、着席確率をそのままとする。   On the other hand, if there is a reference simulation (step F3: YES), loop F processing is performed for each seated arc included in the route search network. In loop F, a seating probability corresponding to the target seating arc is calculated based on the result of the reference simulation (step F5). Next, it is determined whether or not the corresponding predicted seating probability is calculated. If so (step F7: YES), the seating probability is changed to this predicted seating probability (step F9). If not calculated (step F7: NO), the seating probability is left as it is.

続いて、着席確率を、仮想旅客の行動属性に応じた着席可能認知確率と比較し、着席確率が着席可能認知確率未満ならば（ステップＦ１１：ＮＯ）、対象着席アークのコストを「∞を示す所定値」に変更する（ステップＦ１３）。ループＦの処理はこのように行われる。   Subsequently, the seating probability is compared with the seatable recognition probability according to the behavior attribute of the virtual passenger. If the seating probability is less than the seatable recognition probability (step F11: NO), the cost of the target seating arc is expressed as “∞”. Change to “predetermined value” (step F13). The process of the loop F is performed in this way.

経路探索ネットワークに含まれる全ての着席アークを対象としたループＦの処理を行うと、続いて、経路探索ネットワークに含まれる駅間アークそれぞれを対象としたループＧの処理を行う。ループＧでは、参照シミュレーションの結果をもとに、対象駅間アークに対応する駅間の混雑率を算出する（ステップＦ１５）。次いで、対応する予測混雑率が算出されているかを判断し、算出されているならば（ステップＦ１７：ＹＥＳ）、混雑率を、この予測混雑率に変更する（ステップＦ１９）。そして、混雑率に基づいて、対象駅間アークのコストを変更する（ステップＦ２１）。このとき、対象駅間アークである着席駅間アーク２０ａ及び立席駅間アーク２０ｂのうち、着席駅間アーク２０ａのほうが、立席駅間アークよりもコストが大きくなるように変更する。ループＧの処理はこのように行われる。   When the processing of the loop F for all the seating arcs included in the route search network is performed, the processing of the loop G for each of the inter-station arcs included in the route search network is subsequently performed. In the loop G, the congestion rate between stations corresponding to the target inter-station arc is calculated based on the result of the reference simulation (step F15). Next, it is determined whether or not the corresponding predicted congestion rate is calculated. If it is calculated (step F17: YES), the congestion rate is changed to this predicted congestion rate (step F19). Then, the cost of the arc between the target stations is changed based on the congestion rate (step F21). At this time, among the seated station arc 20a and the standing station arc 20b, which are target station-to-station arcs, the seated station arc 20a is changed to have a higher cost than the standing station arc. The process of loop G is performed in this way.

経路探索ネットワークに含まれる全ての駅間アークを対象としたループＧの処理を行うと、経路探索ネットワークに基づいて出発駅から目的駅に至る経路を探索し、対象旅客の列車乗継経路として設定する（ステップＦ２５）。ループＥはこのように行われる。全ての対象旅客についてのループＥの処理を行うと、経路探索処理を終了する。   When loop G processing is performed for all inter-station arcs included in the route search network, the route from the departure station to the target station is searched based on the route search network and set as the train connection route of the target passenger (Step F25). Loop E is performed in this way. When the process of loop E is performed for all target passengers, the route search process is terminated.

［作用効果］
このように、本実施形態によれば、列車の着席可能性を考慮した旅客流動シミュレーションが可能となる。すなわち、着席乗客が降車した場合に、降車した着席乗客数に応じた数の立席乗客を着席に変更したり、滞留旅客が乗車した場合に、乗車した滞留旅客を空席数に応じて着席／立席の何れかとすることで、列車の乗客を着席／立席に区別して管理する。また、着席乗車と立席乗車それぞれに対応付けた重み付けと、列車の着席可能性とを用いて、旅客の列車乗継経路を再探索する。これにより、着席／立席の何れになるかによって列車乗継経路が変化し得る様子を模擬することが可能となる。 [Function and effect]
Thus, according to the present embodiment, a passenger flow simulation considering the seating possibility of a train is possible. In other words, when a seated passenger gets off, the number of standing passengers corresponding to the number of seated passengers who have alighted is changed to seated, or when a stagnant passenger gets on the board, By using one of the standing seats, the passengers of the train are managed separately from the seated / standing seats. Further, the train connection route of the passenger is re-searched using the weighting associated with each of the seated boarding and the standing boarding and the seating possibility of the train. This makes it possible to simulate a situation in which the train connection route can change depending on whether the user is seated or standing.

また、列車の着発の度に、列車乗継経路の再探索が実行される。これにより、列車運行に遅延が生じた場合や、旅客が乗車予定の列車に着席できないと判断した場合など、状況に応じて旅客の列車乗継経路が動的に変化する様子を模擬することが可能となる。   In addition, every time a train arrives or departs, a re-search for a train connection route is executed. As a result, it is possible to simulate a situation in which a passenger's train connection route changes dynamically according to the situation, such as when there is a delay in train operation, or when it is determined that the passenger cannot sit on the scheduled train. It becomes possible.

また、乗車人数に応じた混雑指標値を用いて、立席乗車に対する重み付けが可変される。一般的に、着席乗車は、立席乗車に比較して混雑の影響をさほど受けない。また、乗車人数が多いほど、混雑の影響が大きくなる。これにより、着席乗車と立席乗車とを区別したより精度の高い旅客行動シミュレーションが可能となる。   Further, the weighting for standing passengers is varied using the congestion index value corresponding to the number of passengers. In general, a seated ride is less affected by congestion than a standing ride. In addition, the greater the number of passengers, the greater the impact of congestion. As a result, a more accurate passenger behavior simulation can be performed in which seated boarding and standing boarding are distinguished.

また、乗車した滞留旅客のうち、優先的に着席とする旅客が、当該滞留旅客の滞留時間を用いて判断される。これにより、駅における列車の待ち時間が長いほど、乗車待ちをしていて乗車すれば着席できる可能性が高まるといった状況を模擬することが可能となる。   In addition, among the staying passengers who have boarded, a passenger who is preferentially seated is determined using the staying time of the staying passenger. This makes it possible to simulate a situation where the longer the waiting time of a train at a station, the more likely it is to be seated if the user waits and gets on.

なお、本発明の適用可能な実施形態は上述の実施形態に限定されることなく、本発明の趣旨を逸脱しない範囲で適宜変更可能なのは勿論である。   It should be noted that embodiments to which the present invention can be applied are not limited to the above-described embodiments, and can of course be changed as appropriate without departing from the spirit of the present invention.

１ シミュレーション装置
１１０ 操作入力部、１２０ 表示部、１３０ 通信部
２００ 処理部
２１０ 旅客管理部
２１１ 出現制御部、２１２ 降車制御部、２１３ 継続乗車着席制御部
２１４ 乗車制御部、２１５ 滞留管理部
２２０ 着席確率算出部、２３０ 混雑率算出部、２４０ 列車運行制御部
２５０ 列車乗継経路探索部、２５１ 出現時探索部、２５２ 着発時再探索部
２６０ 不効用値算出部
３００ 記憶部
３１０ シミュレーションプログラム
３２０ 計画ダイヤデータ、３３０ 運用ダイヤデータ、３４０実績ダイヤデータ
３５０ 旅客出現確率テーブル、３６０ 行動属性設定テーブル
３７０旅客データ、３８０ 列車データ、４１０滞留旅客データ
４２０ 乗車予約旅客データ、４３０ 予測混雑率データ
４４０ 予測着席確率データ、４５０ 不効用値データ
１０ 着ノード、１０ａ 着席着ノード、１０ｂ 立席着ノード
１２ 発ノード、１２ａ 着席発ノード、１２ｂ 立席発ノード
１４ 滞留ノード、１４ａ 優先滞留ノード、１４ｂ 一般滞留ノード
１６ａ 着席乗車予約ノード、１６ｂ 立席乗車予約ノード
２０ 駅間アーク、２０ａ 着席駅間アーク、２０ｂ 立席駅間アーク
２２ 停車アーク
２２ａ 着席停車アーク、２２ｂ 立席停車アーク、２２ｃ 着席移行停車アーク
２４（２４ａ，２４ｂ） 降車アーク
２６ 乗車アーク
２６ａ 優先着席乗車アーク、２６ｂ 優先立席乗車アーク
２６ｃ 一般着席乗車アーク、２６ｄ 一般立席乗車アーク
２８ 滞留アーク
２８ａ 優先継続滞留アーク、２８ｂ 一般継続滞留アーク
２８ｃ 優先移行滞留アーク DESCRIPTION OF SYMBOLS 1 Simulation apparatus 110 Operation input part, 120 Display part, 130 Communication part 200 Processing part 210 Passenger management part 211 Appearance control part, 212 Alighting control part 213 Continuation boarding seating control part 214 Boarding control part, 215 Stay management part 220 Seating probability Calculation unit, 230 Congestion rate calculation unit, 240 Train operation control unit 250 Train transit route search unit, 251 Appearance search unit, 252 Arrival re-search unit 260 Invalid value calculation unit 300 Storage unit 310 Simulation program 320 Planning diagram Data, 330 operation diagram data, 340 performance diagram data 350 passenger appearance probability table, 360 action attribute setting table 370 passenger data, 380 train data, 410 stay passenger data 420 boarding reservation passenger data, 430 predicted congestion rate data 440 predicted seating probability data 45 0 Invalid value data 10 Landing node, 10a Seated node, 10b Standing node 12 Departing node, 12a Standing node, 12b Standing node 14 Staying node, 14a Preferential staying node, 14b General staying node 16a Seating reservation Node, 16b Standing boarding reservation node 20 Station-to-station arc, 20a Seated station-to-station arc, 20b Station-to-station arc 22 Stopping arc 22a Seated stopping arc, 22b Standing-stop arc, 22c Seat-shifting stop arc 24 (24a, 24b) Dismounting arc 26 Riding arc 26a Priority seating riding arc, 26b Priority seating riding arc 26c General seating riding arc, 26d General seating riding arc 28 Residential arc 28a Priority continuous retention arc 28b General continuous retention arc 28c Priority transition retention arc

Claims (6)

シミュレーション時刻を時々刻々と計時し、出現駅と目的駅とが定められた仮想旅客の当該出現駅への出現制御、前記出現駅から前記目的駅までの乗車列車を特定した所与の列車乗継経路に沿って前記仮想旅客を乗降させる乗降制御、前記仮想旅客の乗降人数に応じた遅延制御を含む所与の列車ダイヤに沿った列車の運行制御、を含む旅客流動シミュレーションをコンピュータに実行させるためのプログラムであって、
前記仮想旅客それぞれについて、乗車中の列車の識別情報、及び、当該乗車の着席／立席の区別を少なくとも含む状況情報を管理する個別旅客状況管理手段、
予め定められた座席数と前記状況情報とを用いて各列車の着席可能性を算出する着席可能性算出手段、
着席乗車と立席乗車それぞれに対応づけられた重み付けと、前記着席可能性とを用いて、前記列車乗継経路の再探索を実行する再探索実行手段、
着席乗客（着席乗車の仮想旅客のこと。以下同じ）が前記乗降制御によって降車した場合に、降車した当該着席乗客の数に応じた数の当該列車の立席乗客（立席乗車の仮想旅客のこと。以下同じ）を着席に変更する継続乗車着席制御手段、
滞留旅客（駅に滞留していた仮想旅客のこと。以下同じ）が前記乗降制御によって乗車した場合に、乗車した当該滞留旅客を、前記継続乗車着席制御手段による変更制御後の当該列車の空席数を用いて、着席及び立席の何れかとする乗車時制御手段、
として前記コンピュータを機能させるためのプログラム。 Controls the appearance of a virtual passenger whose appearance time and destination station are determined, and the train transfer from the appearance station to the destination station. To cause a computer to execute passenger flow simulation including boarding / alighting control for getting on and off the virtual passenger along a route and train operation control along a given train schedule including delay control according to the number of passengers getting on and off the virtual passenger The program of
For each of the virtual passengers, individual passenger status management means for managing the status information including at least the identification information of the train being boarded and the seating / standing position of the boarding,
Seating possibility calculating means for calculating the seating possibility of each train using a predetermined number of seats and the situation information;
Re-search execution means for re-searching the train connection route using the weighting associated with each of the seated boarding and the standing boarding and the seating possibility;
When seated passengers (referred to as virtual passengers of seated passengers; the same shall apply hereinafter) get off by the above-mentioned boarding / alighting control, the number of seated passengers (the number of virtual passengers of seated passengers) corresponding to the number of seated passengers that have exited The same applies to the following)
When a staying passenger (a virtual passenger staying at a station; the same applies hereinafter) gets on the boarding / alighting control, the number of seats in the train after the staying passenger seating control means changes the staying passenger A boarding time control means to be either seated or standing, using
A program for causing the computer to function as 前記再探索実行手段は、列車の着発の度に前記再探索を実行する、
請求項１に記載のプログラム。 The re-search execution means executes the re-search every time a train arrives.
The program according to claim 1. 前記着席可能性判定手段は、前記座席数と、前記乗降制御によって降車した着席乗客の数と、当該列車の立席乗客の数と、前記乗降制御によって乗車した滞留旅客の数とを用いて、着席できる可能性の程度を示す指標値として前記着席可能性を算出する、
請求項１又は２に記載のプログラム。 The seating possibility determination means uses the number of seats, the number of seated passengers who got off by the boarding / alighting control, the number of standing passengers of the train, and the number of staying passengers boarded by the boarding / alighting control, Calculating the seating possibility as an index value indicating the degree of possibility of being seated;
The program according to claim 1 or 2. 乗車人数に応じた混雑指標値を用いて立席乗車に対応する前記重み付けを可変に算出する手段、
として前記コンピュータを更に機能させるための請求項１〜３の何れか一項に記載のプログラム。 Means for variably calculating the weighting corresponding to standing passengers using a congestion index value according to the number of passengers;
The program as described in any one of Claims 1-3 for making the said computer function further as. 前記乗車時制御手段は、前記乗降制御によって乗車した滞留旅客のうち、優先的に着席とする旅客を、当該滞留旅客の滞留時間を用いて判断する、
請求項１〜４の何れか一項に記載のプログラム。 The boarding time control means determines a passenger to be preferentially seated among the staying passengers boarded by the boarding / alighting control using the staying time of the staying passengers.
The program as described in any one of Claims 1-4. シミュレーション時刻を時々刻々と計時し、出現駅と目的駅とが定められた仮想旅客の当該出現駅への出現制御、前記出現駅から前記目的駅までの乗車列車を特定した所与の列車乗継経路に沿って前記仮想旅客を乗降させる乗降制御、前記仮想旅客の乗降人数に応じた遅延制御を含む所与の列車ダイヤに沿った列車の運行制御、を含む旅客流動シミュレーションを実行するシミュレーション装置であって、
前記仮想旅客それぞれについて、乗車中の列車の識別情報、及び、当該乗車の着席／立席の区別を少なくとも含む状況情報を管理する個別旅客状況管理手段と、
予め定められた座席数と前記状況情報とを用いて各列車の着席可能性を算出する着席可能性算出手段と、
着席乗車と立席乗車それぞれに対応づけられた重み付けと、前記着席可能性とを用いて、前記列車乗継経路の再探索を実行する再探索実行手段と、
着席乗客が前記乗降制御によって降車した場合に、降車した当該着席乗客の数に応じた数の当該列車の立席乗客を着席に変更する継続乗車着席制御手段と、
滞留旅客が前記乗降制御によって乗車した場合に、乗車した当該滞留旅客を、前記継続乗車着席制御手段による変更制御後の当該列車の空席数を用いて、着席及び立席の何れかとする乗車時制御手段と、
を備えたシミュレーション装置。 Controls the appearance of a virtual passenger whose appearance time and destination station are determined, and the train transfer from the appearance station to the destination station. A simulation device for executing passenger flow simulation including boarding / alighting control for getting on and off the virtual passenger along a route and train operation control along a given train schedule including delay control according to the number of passengers getting on and off the virtual passenger There,
For each of the virtual passengers, individual passenger status management means for managing the identification information of the train being boarded and the status information including at least the distinction between seating / standing of the boarding,
Seating possibility calculating means for calculating the seating possibility of each train using a predetermined number of seats and the situation information;
Re-search execution means for re-searching the train connection route using the weighting associated with each of the seated boarding and the standing boarding and the seating possibility;
When a seated passenger gets off by the boarding / alighting control, the continuous boarding seating control means for changing the number of standing passengers of the train corresponding to the number of the seated passengers to the seated seats,
When a staying passenger gets on the boarding / alighting control, the boarding time control that makes the staying passenger either seated or standing using the number of seats of the train after the change control by the continuous boarding seating control means Means,
A simulation apparatus with
JP2014117566A 2014-06-06 2014-06-06 Program and simulation device Active JP6231946B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2014117566A JP6231946B2 (en) 2014-06-06 2014-06-06 Program and simulation device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP2014117566A JP6231946B2 (en) 2014-06-06 2014-06-06 Program and simulation device

Publications (2)

Publication Number Publication Date
JP2015229459A true JP2015229459A (en) 2015-12-21
JP6231946B2 JP6231946B2 (en) 2017-11-15

Family

ID=54886474

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2014117566A Active JP6231946B2 (en) 2014-06-06 2014-06-06 Program and simulation device

Country Status (1)

Country Link
JP (1) JP6231946B2 (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2019001448A (en) * 2017-06-13 2019-01-10 公益財団法人鉄道総合技術研究所 Program and passenger movement route estimation device
CN112918523A (en) * 2021-02-25 2021-06-08 北京电子科技职业学院 Passenger flow cooperative accurate control method for crowded subway line based on train schedule optimization
JP2022502777A (en) * 2018-09-26 2022-01-11 コスモ テッキ How to tune a multimodal transportation network
CN117227810A (en) * 2023-10-18 2023-12-15 中国矿业大学 Emergency linkage method and system for rail transit

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002037076A (en) * 2000-07-27 2002-02-06 Kawasaki Heavy Ind Ltd Method and device for simulating train operation
US20020032587A1 (en) * 2000-02-23 2002-03-14 Paul Bermel Method and apparatus for notifying passengers of delay exception events in transit systems
JP2007118674A (en) * 2005-10-26 2007-05-17 Hitachi Ltd Operation arrangement supporting system and operation arrangement supporting method
JP2007210507A (en) * 2006-02-10 2007-08-23 Navitime Japan Co Ltd Navigation system and route searching method, and route searching server and navigation terminal device
JP2010018221A (en) * 2008-07-14 2010-01-28 Railway Technical Res Inst Program, passenger flow estimation device, operation arrangement proposal preparation device, passenger flow estimation method, and operation arrangement proposal preparation method
JP2011157056A (en) * 2010-02-04 2011-08-18 Railway Technical Research Institute Passenger boarding route estimating method, train diagram preparing method, program and passenger boarding route estimating device

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020032587A1 (en) * 2000-02-23 2002-03-14 Paul Bermel Method and apparatus for notifying passengers of delay exception events in transit systems
JP2002037076A (en) * 2000-07-27 2002-02-06 Kawasaki Heavy Ind Ltd Method and device for simulating train operation
JP2007118674A (en) * 2005-10-26 2007-05-17 Hitachi Ltd Operation arrangement supporting system and operation arrangement supporting method
JP2007210507A (en) * 2006-02-10 2007-08-23 Navitime Japan Co Ltd Navigation system and route searching method, and route searching server and navigation terminal device
JP2010018221A (en) * 2008-07-14 2010-01-28 Railway Technical Res Inst Program, passenger flow estimation device, operation arrangement proposal preparation device, passenger flow estimation method, and operation arrangement proposal preparation method
JP2011157056A (en) * 2010-02-04 2011-08-18 Railway Technical Research Institute Passenger boarding route estimating method, train diagram preparing method, program and passenger boarding route estimating device

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2019001448A (en) * 2017-06-13 2019-01-10 公益財団法人鉄道総合技術研究所 Program and passenger movement route estimation device
JP2022502777A (en) * 2018-09-26 2022-01-11 コスモ テッキ How to tune a multimodal transportation network
CN112918523A (en) * 2021-02-25 2021-06-08 北京电子科技职业学院 Passenger flow cooperative accurate control method for crowded subway line based on train schedule optimization
CN117227810A (en) * 2023-10-18 2023-12-15 中国矿业大学 Emergency linkage method and system for rail transit
CN117227810B (en) * 2023-10-18 2024-04-26 中国矿业大学 Emergency linkage method and system for rail transit

Also Published As

Publication number Publication date
JP6231946B2 (en) 2017-11-15

Similar Documents

Publication Publication Date Title
Fonzone et al. A model of bus bunching under reliability-based passenger arrival patterns
Hamdouch et al. Schedule-based transit assignment model with vehicle capacity and seat availability
Hassannayebi et al. Urban rail transit planning using a two-stage simulation-based optimization approach
Berrebi et al. A real-time bus dispatching policy to minimize passenger wait on a high frequency route
He et al. Multi-modal traffic signal control with priority, signal actuation and coordination
Cats et al. Modeling the impacts of public transport reliability and travel information on passengers’ waiting-time uncertainty
Cats et al. Effect of real-time transit information on dynamic path choice of passengers
Muñoz et al. Comparison of dynamic control strategies for transit operations
JP6231946B2 (en) Program and simulation device
Lin et al. Transit priority strategies for multiple routes under headway-based operations
Binart et al. A 2-stage method for a field service routing problem with stochastic travel and service times
Petit et al. Multiline bus bunching control via vehicle substitution
Cats et al. Effect of real-time transit information on dynamic passenger path choice
Deng et al. Reduce bus bunching with a real-time speed control algorithm considering heterogeneous roadway conditions and intersection delays
Ruokokoski et al. Assignment formulation for the Elevator Dispatching Problem with destination control and its performance analysis
Liu et al. A multi-modal evacuation-based response strategy for mitigating disruption in an intercity railway system
CN108364093B (en) Road network passenger flow cooperative control optimization method based on capacity bottleneck untwining strategy
Drabicki et al. Mitigating bus bunching with real-time crowding information
WO2023142295A1 (en) Non-supersaturated state-based appointed travel management and control method and apparatus, and storage medium
Samà et al. Optimal aircraft traffic flow management at a terminal control area during disturbances
Ding et al. Dynamic dispatch of connected taxis for large-scale urban road networks with stochastic demands: An MFD-enabled hierarchical and cooperative approach
Zhen et al. Train rescheduling model with train delay and passenger impatience time in urban subway network
CN112070275A (en) Method, device and equipment for cooperatively limiting current of rail transit road network
Liu et al. Real-time traffic impedance and priority based cooperative path planning mechanism for SOC-ITS: Efficiency and equilibrium
JP2012162209A (en) Train set vehicle number determining method, seat classification setting plan making method and train set vehicle number determining system

Legal Events

Date Code Title Description
A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20161110

A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20170914

TRDD Decision of grant or rejection written
A01 Written decision to grant a patent or to grant a registration (utility model)

Free format text: JAPANESE INTERMEDIATE CODE: A01

Effective date: 20171003

A61 First payment of annual fees (during grant procedure)

Free format text: JAPANESE INTERMEDIATE CODE: A61

Effective date: 20171020

R150 Certificate of patent or registration of utility model

Ref document number: 6231946

Country of ref document: JP

Free format text: JAPANESE INTERMEDIATE CODE: R150