WO2024105877A1 - Simulation device and simulation method - Google Patents

Simulation device and simulation method Download PDF

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WO2024105877A1
WO2024105877A1 PCT/JP2022/042827 JP2022042827W WO2024105877A1 WO 2024105877 A1 WO2024105877 A1 WO 2024105877A1 JP 2022042827 W JP2022042827 W JP 2022042827W WO 2024105877 A1 WO2024105877 A1 WO 2024105877A1
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bottleneck
simulation
human model
human
simulation device
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PCT/JP2022/042827
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French (fr)
Japanese (ja)
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渉 鳥海
貴大 羽鳥
鋭 寧
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株式会社日立製作所
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Priority to PCT/JP2022/042827 priority Critical patent/WO2024105877A1/en
Publication of WO2024105877A1 publication Critical patent/WO2024105877A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

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  • the present invention relates to a simulation device and a simulation method for simulating people flow.
  • Patent Document 1 which is related to a people flow simulation system, the aim is to simulate interactions due to differences in moving directions and to accurately simulate movement, proposing that "the ratio of the number of mobile agents moving in one direction at a selected edge to the number of mobile agents moving in the other direction is calculated for each direction, and the width in the direction in which the mobile agents are heading is calculated from the ratio of the number of mobile agents to the width of the edge, and for each mobile agent, the population density is calculated based on the length ahead from the mobile agent's position and the area of the section calculated from the width in the direction in which the agent is heading, and the mobile agents in each direction that exist in that section.
  • the moving speed of each mobile agent is calculated based on the free walking speed in the agent information, the calculated population density, and predetermined parameters.”
  • the walking speed is determined based on the number of people moving within the edge and the number of people moving in the opposite direction, but there is no mention of determining the direction of movement to avoid contact in crowded areas. For this reason, for example, in environments where there are obstacles or narrow areas, these can become bottlenecks, and a complete deadlock can occur when a counterflow occurs toward the bottleneck.
  • the present invention aims to provide a simulation device and a simulation method that can deal with bottlenecks and obtain highly convincing people flow simulation results.
  • the present invention provides a "simulation device for simulating people flow, the simulation device having a memory unit and a simulation control unit, the memory unit stores layout information, and a human model that holds at least destination information indicating where the human model is heading within the layout information and current position information, and the control unit changes movement control of the human model from a case where a bottleneck is not detected when a bottleneck that restricts the flow rate of the human model is detected within a certain range ahead in the direction of movement of the human model.”
  • the present invention provides a "simulation method for simulating people flow, the simulation method comprising a storage method and a simulation control method, the storage method storing an arbitrary layout and a human model that holds at least destination information indicating where in the layout the person is heading and current position information, and the control method is characterized in that, when a bottleneck area with a narrow passage width is detected within the visual field of the human model, the effect of avoiding oncoming people is strengthened more than usual.”
  • FIG. 1 is a diagram showing an example of the configuration of a simulation device according to an embodiment of the present invention.
  • FIG. 1 shows the inside of a building as an example of an environment to be simulated.
  • FIG. 3 is a diagram showing the establishment of passage fragments in the building of FIG. 2 .
  • FIG. 13 is a diagram showing the concept of determining the movement direction of a human model in a normal state. 13 is a diagram showing that an oncoming vehicle M2 has been detected ahead in the direction of movement. 13 is a diagram showing that an oncoming person M2 is detected in the direction of movement at a bottleneck portion.
  • FIG. FIG. 1 is a diagram showing a first method for identifying a bottleneck.
  • FIG. 13 is a diagram showing a second method for identifying a bottleneck.
  • FIG. 11 is a diagram showing a processing flow in a preparatory stage.
  • FIG. 4 is a diagram showing a processing flow during a simulation.
  • FIG. 1 is a diagram showing an example of the configuration of a simulation device according to a first embodiment of the present invention.
  • the simulation device 1 is configured by connecting a storage unit DB, a calculation unit 12, and an input/output device 13 to a bus 14.
  • the storage unit DB stores layout information D1 of the environment to be simulated, and a human model D2 that moves in that environment. Functionally expressing the processing content of the calculation unit 12, it can be said that the calculation unit 12 has each of the processing units, a bottleneck detection unit 121, a human movement direction determination unit 122, and a human movement execution unit 123.
  • the input/output device 13 includes an input unit 131 that sets the appropriate simulation conditions, and an output unit (display unit) 132 that outputs the input setting data and simulation results.
  • the building shown in the plan view of Figure 2 which is an example of an environment to be simulated, has multiple entrances A and B. Entrance A faces, for example, an external corridor, and entrance B is where an elevator is installed to move to each floor in the building. Although the illustration is simplified here, other entrances may include stairs, and there may be multiple entrances. Note that because the building in Figure 2 has a security gate G installed between entrances A and B, the area on the plan view is divided into passable and non-passable areas.
  • the setup procedure is roughly divided into three steps.
  • First, the architectural layout is set by referring to architectural drawings and setting the layout of each floor in the building as well as the floor dimensions and height.
  • the building facilities are set by arranging various building facilities such as elevators, escalators, security gates, automatic doors, etc. and setting the specifications for each.
  • the movement of people is set by setting the entrances and doorways for rooms and setting the number of people moving from where to where and how many people.
  • layout information D1 is formed in the memory unit of Figure 1 as shown in Figure 2, and in more detail in the present invention, it is formed and stored as shown in Figure 3.
  • Figure 2 the layout and floor dimensions and height of each floor in the building are set, but in Figure 3, the area between entrances A and B is further divided into multiple areas in the direction of people movement, and information including distances in perpendicular directions is provided. This is done by setting multiple passage fragments on the route of people movement (for example, the shortest distance between entrances A and B), and calculating the horizontal distance for each passage fragment.
  • entrances and room doorways are set, and the number of people moving from where to where is set. Note that information on entrances and room doorways is managed as part of the layout information D1.
  • Figure 4a is a diagram showing the concept for determining the movement direction of a human model under normal circumstances.
  • eight directions front, back, left, right, left, front, back
  • a cost is set for each direction.
  • the cost is set by size, and normally, if 10 is set in the forward direction, a value greater than 10 is set for the other directions.
  • the front and the left and right forward directions are shown in Figure 4a, but the left and right forward directions are set to 14, which is greater than 10. After such settings, the direction with the lowest cost is set as the traveling direction.
  • the cost of the detection direction is revised to be higher than the initial setting value of 10, for example to 12.
  • the revised cost is set to 12
  • the direction of movement of the human model can be set to take evasive action in the left or right forward direction, etc., in accordance with the principle that the direction with the lowest cost is the direction of travel.
  • information on the human model M1 in which human movement settings have been made is stored for each individual person.
  • This information includes the number of people in a time series, their respective entry and exit routes, destinations, cost information by direction, walking speed, etc.
  • the bottleneck detection unit 121 in the calculation unit 12 detects bottlenecks on the route to the destination.
  • a bottleneck is a location or position where, for example, an obstacle or narrow section is present in the environment, which can cause a counterflow and lead to congestion or jams, and a place that is likely to show such a tendency is set as a bottleneck environment.
  • the human model M1 moves along a route (a straight line with the shortest distance) from its current position (e.g., building entrance/exit A) to its destination, entrance/exit B, and the presence or absence of a bottleneck on this route is set in advance.
  • its current position e.g., building entrance/exit A
  • its destination e.g., entrance/exit B
  • the presence or absence of a bottleneck on this route is set in advance.
  • Method 2 of bottleneck identification is a method that does not use the advance preparation information (distance information for each passage fragment) in Figure 3.
  • distance information for each passage fragment distance information for each passage fragment
  • Figure 6 when determining the direction of movement of a person during the simulation, if there is an area of a certain area or more that the person cannot enter within a certain range ahead (field of vision), it is determined to be a bottleneck.
  • the bottleneck detection unit 121 in the calculation unit 12 detects bottlenecks in the preparation stage before the simulation is executed, or detects bottlenecks during the simulation.
  • the people movement direction determination unit 122 in FIG. 1 determines the direction of people movement in the simulation by setting costs.
  • the cost operation when an oncoming person is detected in the movement direction as described in FIG. 4b is also a process performed by the people movement direction determination unit 122.
  • an oncoming person M2 is detected in the movement direction at a bottleneck.
  • the person movement direction determination unit 122 detects that such a situation has occurred in the simulation and executes a cost operation as shown in Figure 4c. This serves to strengthen the lane formation effect (parameters for avoiding oncoming people) when a bottleneck is detected in the person's travel direction. Specifically, when a bottleneck is detected, a larger cost than usual is applied in the direction where the oncoming person M2 is located, making it easier to determine the next movement direction.
  • the avoidance direction should be determined according to the principle of keeping to the right of way, which creates a lane formation effect for the entire environment and makes it cheaper. Also, the narrower the bottleneck, the higher the cost should be set. Furthermore, in Figure 6, the area in the field of view where the oncoming vehicle M2 is located should also be treated as a no-entry area. When determining the direction of movement, the cost applied in the direction where the oncoming vehicle M2 is located should be inversely proportional to the size of the no-entry area in the field of view.
  • the forward cost is set lower than the cost for other directions, and the cost is increased depending on the presence of oncoming vehicles or bottlenecks, with the direction with the lower cost being the direction of travel; however, this may be reversed.
  • the same can be done by setting the forward cost higher than the cost for other directions, and the cost is decreased depending on the presence of oncoming vehicles or bottlenecks, with the direction with the higher cost being the direction of travel.
  • the present invention is characterized in that when a bottleneck is detected ahead of a person's movement direction during person movement processing, the effectiveness of avoiding oncoming vehicles is increased more than usual.
  • the effectiveness of avoiding oncoming vehicles is also increased by increasing the cost of the location where the oncoming vehicle is located and the location ahead of the oncoming vehicle in inverse proportion to the width of the bottleneck.
  • the effectiveness of avoiding oncoming vehicles is also increased by increasing the cost of the location where the oncoming vehicle is located and the location ahead of the oncoming vehicle in inverse proportion to the area of the impassable area within the person's field of vision.
  • Example 2 a simulation method is described.
  • Figure 7 shows the process flow in the preparatory stage, and
  • Figure 8 shows the process flow during the simulation.
  • the building layout is set, in processing step S12 the building facilities are set, and in processing step S13 the movement of people is set.
  • layout information D1 and a human model D2 are formed in processing step S14, and each is stored in the memory unit.
  • processing step S15 it is determined whether or not to perform aisle fragment processing. If so, in processing step S16, the aisle fragment processing is executed to identify the width, and then in processing step S17, it is determined that the position is a bottleneck based on the identified width, and this is stored as part of the layout information D1.
  • FIG 8 which shows the processing during the simulation, first in processing step S21, layout information D1 of the environment in which people flow processing is performed and human model D2 are obtained. In processing step S22, the processing is repeated while changing the human model M1 and the processing time up to processing step S30. Note that the environment, and therefore the layout, are assumed to be specified.
  • processing step S23 it is determined whether or not the passing fragment process has been performed. If it has not been performed, in processing step S24, bottleneck recognition processing based on the field of view is performed. If it has been performed, or after processing step S24 has been performed, the process moves to processing step S25.
  • the current state is judged based on the presence of an oncoming person M2 for the selected human model M1 and the bottleneck confirmation state. This distinguishes between three states: normal (no bottleneck, no oncoming person), oncoming person detected, and oncoming person detected and bottleneck state.
  • the cost in the forward direction is set lower than in other directions in processing step S26, and when it is detected that an oncoming vehicle M2 is present in the direction of movement, the cost in the forward direction is increased in processing step S28, and when an oncoming vehicle is detected and a bottleneck condition exists, the cost in the forward direction is significantly increased in processing step S27.
  • processing step S29 where a direction of travel is determined according to the cost, and the human model is moved in the determined direction of travel.
  • This process is the process of the human movement execution unit 123 in FIG. 1.
  • Processing step S30 is a process for determining the end of the repetition, and the above process is repeated for the set number of human models over the simulation period while changing the time. This repetitive process is also executed on the time axis, resulting in a simulation of the flow of people over time.

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Abstract

The present invention provides a simulation device and a simulation method, which are capable of addressing bottlenecks and obtaining a people-flow simulation result with a high level of satisfaction. The simulation device for simulating a people flow comprises a storage unit and a control unit for simulation, the simulation device being characterized in that the storage unit stores layout information and human models that hold at least current location information and destination information indicating where to go within the layout information, and the control unit, upon detecting a bottleneck where the flow of the human models may be constrained within a certain area in front of the human models in the human-model movement direction, changes movement control for the human models from the situation in which said bottleneck is not detected.

Description

シミュレーション装置、及びシミュレーション方法Simulation device and simulation method
　本発明は、人流のシミュレーションを行うシミュレーション装置、及びシミュレーション方法に関する。 The present invention relates to a simulation device and a simulation method for simulating people flow.
　近年、イベントや災害時における避難誘導計画の事前評価や、新規集客施設建設にともなう混雑状況の事前評価など、人が局所的に集中することで発生する課題への対応策を評価することを目的として、コンピュータ上で歩行者の流れを再現することができる人流シミュレーションシステムが注目されている。 In recent years, people flow simulation systems that can reproduce pedestrian flows on a computer have been attracting attention for the purpose of evaluating countermeasures to issues that arise when people concentrate in a local area, such as in advance evaluation of evacuation guidance plans for events or disasters, or advance evaluation of congestion conditions associated with the construction of new facilities to attract customers.
　人流シミュレーションシステムに関連して例えば特許文献１では、進行方向の違いによる相互作用を模擬して、精度よく移動をシミュレーションできることを目的として、「選択したエッジにおける、一方の方向に進む移動エージェントの人数と、他方の方向に進む移動エージェントの人数との方向ごとの人数比を求め、当該エッジの幅に対する人数比から、移動エージェントが向かう方向に対する幅員を計算し、移動エージェントの各々について、移動エージェントの位置からの前方の長さ、及び当該エージェントが向かう方向に対して計算した幅員から求まる区間の面積と、当該区間に存在する方向別の移動エージェントに基づいて、人口密度を計算する。移動エージェントの各々について、エージェント情報の自由歩行速度と、計算した人口密度と、予め定めたパラメータとに基づいて、移動エージェントの移動速度を計算する」ことを提案している。 For example, in Patent Document 1, which is related to a people flow simulation system, the aim is to simulate interactions due to differences in moving directions and to accurately simulate movement, proposing that "the ratio of the number of mobile agents moving in one direction at a selected edge to the number of mobile agents moving in the other direction is calculated for each direction, and the width in the direction in which the mobile agents are heading is calculated from the ratio of the number of mobile agents to the width of the edge, and for each mobile agent, the population density is calculated based on the length ahead from the mobile agent's position and the area of the section calculated from the width in the direction in which the agent is heading, and the mobile agents in each direction that exist in that section. The moving speed of each mobile agent is calculated based on the free walking speed in the agent information, the calculated population density, and predetermined parameters."
ＷＯ２０２１／０４４４８１WO2021/044481
　特許文献１によればエッジ内の移動人数および対向人数で歩行速度を決定するが、混雑場面での接触を回避するための移動方向決定に関しては言及されていない。このため例えば障害物が存在する、あるいは狭隘部分が存在するといった環境下ではこれらがボトルネックとなって、ボトルネックへの対向流発生時に完全デッドロックが起きるときがある。 According to Patent Document 1, the walking speed is determined based on the number of people moving within the edge and the number of people moving in the opposite direction, but there is no mention of determining the direction of movement to avoid contact in crowded areas. For this reason, for example, in environments where there are obstacles or narrow areas, these can become bottlenecks, and a complete deadlock can occur when a counterflow occurs toward the bottleneck.
　以上のことから本発明においては、ボトルネックに対しても対応が可能であり、納得感の高い人流シミュレーション結果を得ることができるシミュレーション装置、及びシミュレーション方法を提供することを目的とする。 In light of the above, the present invention aims to provide a simulation device and a simulation method that can deal with bottlenecks and obtain highly convincing people flow simulation results.
　以上のことから本発明においては、「人流を模擬するシミュレーション装置であって、シミュレーション装置は記憶部と、シミュレーションの制御部とを備え、記憶部は、レイアウト情報と、前記レイアウト情報内においてどこに向かうかを示す目的地情報と現在の位置情報を少なくとも保持する人モデルを記憶し、制御部は、人モデルの移動方向前方の一定範囲内に人モデルの流量が制限されるボトルネックが検出される場合に、ボトルネックを検出していない場合から前記人モデルの移動制御を変更することを特徴とする、シミュレーション装置」としたものである。 In view of the above, the present invention provides a "simulation device for simulating people flow, the simulation device having a memory unit and a simulation control unit, the memory unit stores layout information, and a human model that holds at least destination information indicating where the human model is heading within the layout information and current position information, and the control unit changes movement control of the human model from a case where a bottleneck is not detected when a bottleneck that restricts the flow rate of the human model is detected within a certain range ahead in the direction of movement of the human model."
　また本発明においては、「人流を模擬するシミュレーション方法であって、シミュレーション方法は記憶方法と、シミュレーションの制御方法とを備え、記憶方法は、任意のレイアウト、及びレイアウト内のどこに向かうかを示す目的地情報と現在の位置情報を少なくとも保持する人モデルを記憶し、制御方法は人モデルの視野の範囲に通路幅が狭いボトルネック領域が検出される場合に、対向者を避ける効果を通常より強めることを特徴とする、シミュレーション方法」としたものである。 Furthermore, the present invention provides a "simulation method for simulating people flow, the simulation method comprising a storage method and a simulation control method, the storage method storing an arbitrary layout and a human model that holds at least destination information indicating where in the layout the person is heading and current position information, and the control method is characterized in that, when a bottleneck area with a narrow passage width is detected within the visual field of the human model, the effect of avoiding oncoming people is strengthened more than usual."
　ボトルネックに対しても対応が可能であり、納得感の高い人流シミュレーション結果を得ることができるシミュレーション装置、及びにシミュレーション方法を提供することができる。 We can provide a simulation device and a simulation method that can deal with bottlenecks and obtain highly convincing people flow simulation results.
本発明の実施例に係るシミュレーション装置の構成例を示す図。FIG. 1 is a diagram showing an example of the configuration of a simulation device according to an embodiment of the present invention. シミュレーションの対象となる環境の一例としてビル内を示す図。FIG. 1 shows the inside of a building as an example of an environment to be simulated. 図２のビル内に通路フラグメントを設定したことを示す図。FIG. 3 is a diagram showing the establishment of passage fragments in the building of FIG. 2 . 通常時の人モデルの移動方向決定の考え方を示す図。FIG. 13 is a diagram showing the concept of determining the movement direction of a human model in a normal state. 移動方向の先に対向者Ｍ２を検知したことを示す図。13 is a diagram showing that an oncoming vehicle M2 has been detected ahead in the direction of movement. ボトルネック部において移動方向に対向者Ｍ２を検知したことを示す図。13 is a diagram showing that an oncoming person M2 is detected in the direction of movement at a bottleneck portion. FIG. ボトルネック認定の手法１を示す図。FIG. 1 is a diagram showing a first method for identifying a bottleneck. ボトルネック認定の手法２を示す図。FIG. 13 is a diagram showing a second method for identifying a bottleneck. 事前準備段階における処理フローを示す図。FIG. 11 is a diagram showing a processing flow in a preparatory stage. シミュレーション中の処理フローを示す図。FIG. 4 is a diagram showing a processing flow during a simulation.
　以下本発明の実施例について図面を参照して説明する。 The following describes an embodiment of the present invention with reference to the drawings.
　図１は、本発明の実施例１に係るシミュレーション装置の構成例を示す図である。シミュレーション装置１は、記憶部ＤＢ，演算部１２，入出力装置１３がバス１４に接続されて構成されている。 FIG. 1 is a diagram showing an example of the configuration of a simulation device according to a first embodiment of the present invention. The simulation device 1 is configured by connecting a storage unit DB, a calculation unit 12, and an input/output device 13 to a bus 14.
　このうち記憶部ＤＢには、シミュレーションの対象となる環境のレイアウト情報Ｄ１と、当該環境下で移動行動を行う人モデルＤ２を記憶している。演算部１２は、その処理内容を機能的に表すと、ボトルネック検出部１２１，人移動方向決定部１２２，人移動実行部１２３の各処理部を有するものということができる。入出力装置１３は、シミュレーション条件などの適宜の設定を行う入力部１３１と、入力した設定データやシミュレーション結果を出力する出力部（表示部）１３２を含んでいる。 The storage unit DB stores layout information D1 of the environment to be simulated, and a human model D2 that moves in that environment. Functionally expressing the processing content of the calculation unit 12, it can be said that the calculation unit 12 has each of the processing units, a bottleneck detection unit 121, a human movement direction determination unit 122, and a human movement execution unit 123. The input/output device 13 includes an input unit 131 that sets the appropriate simulation conditions, and an output unit (display unit) 132 that outputs the input setting data and simulation results.
　以下、図１のシミュレーション装置の動作について詳細に説明するが、この前提として、いくつかの事項を説明しておく。まずシミュレーションの対象となる環境について、これはそれぞれの解析目的に応じて適宜の場所や設備が選定可能であるが、実施例では図２のようなビル内をとりあげる。またシミュレーションモデル上で人の移動方向を推定する手法として、図４ａ，図４ｂ，図４ｃのコスト法を用いて行うものとする。 Below, we will explain in detail the operation of the simulation device in Figure 1, but as a prerequisite, we will explain a few points. First, regarding the environment to be simulated, appropriate locations and facilities can be selected depending on the purpose of each analysis, but in this embodiment, the inside of a building as shown in Figure 2 will be taken as the subject. In addition, the cost method in Figures 4a, 4b, and 4c will be used as a method for estimating the direction of movement of people in the simulation model.
　シミュレーションの対象となる環境の一事例とした図２の平面図で示すビルは、複数の出入口Ａ，Ｂを備えている。出入口Ａは例えば外部の通路などに面しており、出入り口Ｂはビル内の各階に移動するためのエレベーターの設置された位置である。ここでは単純化して示しているが、出入口としては他に階段などが含まれ、複数であってもよい。なお、図２のビルディングは出入口Ａ，Ｂの間にセキュリティゲートＧなどを設置しているために、平面図上の領域は通行可能領域と通行不可能領域に区分されているものとする。 The building shown in the plan view of Figure 2, which is an example of an environment to be simulated, has multiple entrances A and B. Entrance A faces, for example, an external corridor, and entrance B is where an elevator is installed to move to each floor in the building. Although the illustration is simplified here, other entrances may include stairs, and there may be multiple entrances. Note that because the building in Figure 2 has a security gate G installed between entrances A and B, the area on the plan view is divided into passable and non-passable areas.
　図２を対象とした人流のシミュレーションを実行するためには、事前に例えば、ビル内の人の移動のモデル化に必要な条件の設定が行われる必要がある。設定手順は，大きく分けて３つのステップから構成される。初めに，建築図面などを参考に，ビル内の各階のレイアウトおよびフロア寸法や高さを設定する、建築レイアウトの設定を行う。次にエレベーター，エスカレーター，セキュリティゲート，自動ドアなどの各種ビル内設備を配置し，それぞれの仕様を設定する、ビル設備の設定を行う。そしてエントランスや居室の出入り口を設定し，どこからどこへ何人が移動するかという人数を設定する、人の移動の設定を行う。これらの設定処理は、入出力装置１３を用いて、適宜の表示を行いながら事前実行されている。 In order to run a people flow simulation for Figure 2, it is necessary to set the conditions necessary for modeling people movement within a building in advance, for example. The setup procedure is roughly divided into three steps. First, the architectural layout is set by referring to architectural drawings and setting the layout of each floor in the building as well as the floor dimensions and height. Next, the building facilities are set by arranging various building facilities such as elevators, escalators, security gates, automatic doors, etc. and setting the specifications for each. Then, the movement of people is set by setting the entrances and doorways for rooms and setting the number of people moving from where to where and how many people. These setup processes are performed in advance using the input/output device 13 with appropriate displays.
　建築レイアウトの設定、及びビル設備の設定が完了したことにより、図１の記憶部にはレイアウト情報Ｄ１が図２のように形成され、さらに詳細には本発明では図３のように形成されて記憶されている。図２では、ビル内の各階のレイアウトおよびフロア寸法や高さを設定したが、図３ではさらに出入口Ａ，Ｂの間を人移動の方向に複数領域に区分して、直交方向の距離を含む情報としている。これは人移動のルート（例えば出入口Ａ，Ｂの間の最短距離）上に、複数の通路フラグメントを設定し、通路フラグメントごとに横方向の距離を求めたものである。 Once the architectural layout and building facilities settings have been completed, layout information D1 is formed in the memory unit of Figure 1 as shown in Figure 2, and in more detail in the present invention, it is formed and stored as shown in Figure 3. In Figure 2, the layout and floor dimensions and height of each floor in the building are set, but in Figure 3, the area between entrances A and B is further divided into multiple areas in the direction of people movement, and information including distances in perpendicular directions is provided. This is done by setting multiple passage fragments on the route of people movement (for example, the shortest distance between entrances A and B), and calculating the horizontal distance for each passage fragment.
　さらに上記設定を前提とした人の移動の設定では、エントランスや居室の出入り口を設定し，どこからどこへ何人が移動するかという人数を設定する。なお、エントランスや居室の出入り口の情報は、レイアウト情報Ｄ１に含めて管理される。 Furthermore, in setting up people movement based on the above settings, entrances and room doorways are set, and the number of people moving from where to where is set. Note that information on entrances and room doorways is managed as part of the layout information D1.
　ここで、このときの人モデルの取り扱いに関して、特に人モデルの移動方向決定の考え方として本発明ではコスト方式を採用している。図４ａは通常時の人モデルの移動方向決定の考え方を示す図である。ここでは、人モデルＭ１の移動方向として、床平面上に例えば８方向（前後左右、並びに左右前後方向）を設定し、各方向にコストを設定する。コストは大きさで設定され、通常は前方向に１０を設定したなら、それ以外の方向には１０より大きい数値を設定しておく。図４ａでは、簡便に前と左右前方のみを記述しているが、左右前方は１０よりも大きい、１４とする。係る設定のうえで、コストが最も低い方向を進行方向とする。 Here, in regard to the handling of the human model at this time, the present invention employs a cost method as a concept for determining the movement direction of the human model in particular. Figure 4a is a diagram showing the concept for determining the movement direction of a human model under normal circumstances. Here, for example, eight directions (front, back, left, right, left, front, back) are set on the floor plane as the movement directions of the human model M1, and a cost is set for each direction. The cost is set by size, and normally, if 10 is set in the forward direction, a value greater than 10 is set for the other directions. For simplicity, only the front and the left and right forward directions are shown in Figure 4a, but the left and right forward directions are set to 14, which is greater than 10. After such settings, the direction with the lowest cost is set as the traveling direction.
　またこのコスト設定を前提として実際のシミュレーションの中では、図４ｂのように移動方向の先に対向者Ｍ２を検知した時には、検知方向のコストを初期設定値の１０よりも高く、例えば１２にするような見直しを行う。なお見直し後のコストは１２としているが、対向者Ｍ２との間の距離が近いほどコストを大きく設定することにより、左右前方のコストより大きくなるときには、コストが最も低い方向を進行方向とする原則に則り、左右前方方向などへの回避行動を起こすような人モデルの移動方向設定とすることができる。 Also, in an actual simulation based on this cost setting, when an oncoming person M2 is detected ahead in the direction of movement as shown in Figure 4b, the cost of the detection direction is revised to be higher than the initial setting value of 10, for example to 12. Note that although the revised cost is set to 12, by setting the cost higher the closer the distance to the oncoming person M2, when the cost becomes greater than the cost to the left or right, the direction of movement of the human model can be set to take evasive action in the left or right forward direction, etc., in accordance with the principle that the direction with the lowest cost is the direction of travel.
　図１の人モデル記憶部ＤＢ２には、人の移動の設定が行われた人モデルＭ１の情報が個々人毎に記憶されている。これらの情報は時系列的な人の個数であり、それぞれの進入、退出経路であり、目的地であり、方向別のコスト情報であり、あるいは歩速度などを含んでいる。 In the human model storage unit DB2 in Figure 1, information on the human model M1 in which human movement settings have been made is stored for each individual person. This information includes the number of people in a time series, their respective entry and exit routes, destinations, cost information by direction, walking speed, etc.
　上記の記憶内容を準備したうえで、演算部１２内のボトルネック検出部１２１では、目的地に至る経路上におけるボトルネックを検知する。ボトルネックとは、例えば障害物が存在する、あるいは狭隘部分が存在するといった環境下において、これにより対向流が発生し混雑、渋滞が生じやすい箇所、位置のことであり、このような傾向を示しやすい場所をボトルネック環境として設定しておくものである。 After preparing the above memory contents, the bottleneck detection unit 121 in the calculation unit 12 detects bottlenecks on the route to the destination. A bottleneck is a location or position where, for example, an obstacle or narrow section is present in the environment, which can cause a counterflow and lead to congestion or jams, and a place that is likely to show such a tendency is set as a bottleneck environment.
　なおシミュレーションにおいては、人モデルＭ１は現在位置（例えばビルの出入り口Ａ）から目的地である出入口Ｂに向かうルート（ここでは直線、最短距離のルートを採用するものとする）に沿って進行するものとし、このルート上のボトルネックの有無を予め設定する。 In the simulation, the human model M1 moves along a route (a straight line with the shortest distance) from its current position (e.g., building entrance/exit A) to its destination, entrance/exit B, and the presence or absence of a bottleneck on this route is set in advance.
　ボトルネック認定の手法１として、図５ではレイアウト情報Ｄ１に記憶された図３の通路フラグメントごとに設定された横方向の距離を考慮して求める。図３では、シミュレーション前にあらかじめ入口から出口までのルート上の通路幅をすべて同定しておき、シミュレーションでは移動方向決定時に人モデルＭ１の視野に含まれている通路幅のうち、最も狭い通路幅を用いてボトルネックを検知する。 In method 1 of bottleneck identification in FIG. 5, the horizontal distance set for each passage fragment in FIG. 3 stored in layout information D1 is taken into consideration. In FIG. 3, all passage widths on the route from the entrance to the exit are identified in advance before the simulation, and in the simulation, the bottleneck is detected using the narrowest passage width among those included in the field of view of the human model M1 when determining the direction of movement.
　ボトルネック認定の手法２は、図３の事前準備情報（通路フラグメントごとの距離情報）を使用しない方法である。ここでは図６に示すように、シミュレーション中における、人の移動方向決定時に前方の一定範囲内（視野）にその人の侵入できない領域が一定面積以上あればボトルネックとするものである。 　Method 2 of bottleneck identification is a method that does not use the advance preparation information (distance information for each passage fragment) in Figure 3. In this case, as shown in Figure 6, when determining the direction of movement of a person during the simulation, if there is an area of a certain area or more that the person cannot enter within a certain range ahead (field of vision), it is determined to be a bottleneck.
　このようにして、演算部１２内のボトルネック検出部１２１ではシミュレーション実行前の事前準備段階においてボトルネック検知を行い、あるいはシミュレーション中にボトルネックを検知する。 In this way, the bottleneck detection unit 121 in the calculation unit 12 detects bottlenecks in the preparation stage before the simulation is executed, or detects bottlenecks during the simulation.
　いずれにせよボトルネックが検知されているという状況において、図１の人移動方向決定部１２２は、コストの設定処理によりシミュレーション上における人移動の方向を決定する。なお図４ｂで述べた移動方向に対向者を検知した時のコスト操作も人移動方向決定部１２２における処理である。 In any case, in a situation where a bottleneck is detected, the people movement direction determination unit 122 in FIG. 1 determines the direction of people movement in the simulation by setting costs. The cost operation when an oncoming person is detected in the movement direction as described in FIG. 4b is also a process performed by the people movement direction determination unit 122.
　本発明では、さらにボトルネック部において移動方向に対向者Ｍ２を検知したことを想定する。人移動方向決定部１２２は、シミュレーション上で係る状況が発生していることを検知して図４ｃのようにコスト操作を実行する。これは人の進行方向にボトルネックを検出したとき、レーン形成効果（対向者を避けるパラメータ）を強める働きをさせるものである。具体的には、ボトルネックが検知された場合、対向者Ｍ２のいる方向に通常より大きなコストをかけて次の移動方向を決定しやすくするものである。 In the present invention, it is further assumed that an oncoming person M2 is detected in the movement direction at a bottleneck. The person movement direction determination unit 122 detects that such a situation has occurred in the simulation and executes a cost operation as shown in Figure 4c. This serves to strengthen the lane formation effect (parameters for avoiding oncoming people) when a bottleneck is detected in the person's travel direction. Specifically, when a bottleneck is detected, a larger cost than usual is applied in the direction where the oncoming person M2 is located, making it easier to determine the next movement direction.
　図４ｂの対向者検知の時の前方コストを、正常時に比較して１０から１２に引き上げるものとするのであれば、図４ｃの条件では一気に１５に引き上げて、他方向のコストの１４を超過させることで、直ちに回避行動をとらせるように仕向けたものである。また、他の人モデルについても同様のコスト操作を行うことにより、環境全体としてレーン形成効果を生じさせることが可能である。 If the forward cost when detecting an oncoming vehicle in Figure 4b is increased from 10 to 12 compared to normal, then in the conditions of Figure 4c it is increased all at once to 15, exceeding the other direction cost of 14, encouraging the vehicle to take immediate evasive action. Also, by performing similar cost manipulations on other vehicle models, it is possible to create a lane formation effect in the entire environment.
　上記のコスト操作に関しては、さらに以下の点を考慮するのがよい。例えば、回避方向の決定は、日本国内であれば右側通行の原則に従って決定することで、環境全体としてレーン形成効果を生じさせ安くなる。また、ボトルネックが狭いほど大きなコスト設定とするのがよい。さらに、図６において視野内のボトルネック部に対向者Ｍ２がいる領域も含めて侵入不可領域と扱うのがよい。移動方向決定時に対向者Ｍ２のいる方向にかけるコストは視野内の侵入不可領域の広さに反比例させるのがよい。 The following points should be further considered regarding the above cost manipulation. For example, in Japan, the avoidance direction should be determined according to the principle of keeping to the right of way, which creates a lane formation effect for the entire environment and makes it cheaper. Also, the narrower the bottleneck, the higher the cost should be set. Furthermore, in Figure 6, the area in the field of view where the oncoming vehicle M2 is located should also be treated as a no-entry area. When determining the direction of movement, the cost applied in the direction where the oncoming vehicle M2 is located should be inversely proportional to the size of the no-entry area in the field of view.
　上記コスト操作によれば、他の地点での人流特性を変えずに、ボトルネックでのデッドロックを防止した動きをさせることができる。これはシミュレータの精度向上や、動きの納得感につながる。 The above cost manipulation allows movements to be made that prevent deadlocks at bottlenecks without changing the characteristics of people flow at other points. This leads to improved accuracy of the simulator and a more convincing feeling of movement.
　なお、上記のコスト設定についての前提の説明では、前方コストを他の方向のコストよりも低く設定し、対向者やボトルネックの存在に応じてコスト上昇操作させ、コストが低い方向を進行方向とするというものであるが、これは大小関係などを逆転させるものであってもよい。つまり、前方コストを他の方向のコストよりも高く設定し、対向者やボトルネックの存在に応じてコストを下降操作させ、コストが高い方向を進行方向とする考え方であっても同様に行える。 In the explanation of the premise for setting the costs above, the forward cost is set lower than the cost for other directions, and the cost is increased depending on the presence of oncoming vehicles or bottlenecks, with the direction with the lower cost being the direction of travel; however, this may be reversed. In other words, the same can be done by setting the forward cost higher than the cost for other directions, and the cost is decreased depending on the presence of oncoming vehicles or bottlenecks, with the direction with the higher cost being the direction of travel.
　以上要するに本発明においては、人の移動処理時に人の移動方向の先にボトルネックが検知されるときに、対向者を避ける効果を通常より大きくすることを特徴とするものである。また、ボトルネックの幅に反比例して対向者のいる位置、および対向者前方の位置のコストを上昇させることで対向者を避ける効果を上昇させるものである。このためには、シミュレーション前にあらかじめルート上の通路幅をすべて同定しておき、シミュレーション中は人の視野に含まれる通路の幅を用いてボトルネックを検知するのがよい。また、人の視野内にある通行不能領域の面積に反比例して、対向者のいる位置、および対向者前方の位置のコストを上昇させることで対向者を避ける効果を上昇させるのがよい。 In summary, the present invention is characterized in that when a bottleneck is detected ahead of a person's movement direction during person movement processing, the effectiveness of avoiding oncoming vehicles is increased more than usual. The effectiveness of avoiding oncoming vehicles is also increased by increasing the cost of the location where the oncoming vehicle is located and the location ahead of the oncoming vehicle in inverse proportion to the width of the bottleneck. To achieve this, it is preferable to identify all aisle widths on the route before the simulation, and to detect bottlenecks during the simulation using the width of the aisle included in the person's field of vision. The effectiveness of avoiding oncoming vehicles is also increased by increasing the cost of the location where the oncoming vehicle is located and the location ahead of the oncoming vehicle in inverse proportion to the area of the impassable area within the person's field of vision.
　実施例２では、シミュレーション方法について説明する。図７は、事前準備段階における処理フロー、図８はシミュレーション中の処理フローを示している。 In Example 2, a simulation method is described. Figure 7 shows the process flow in the preparatory stage, and Figure 8 shows the process flow during the simulation.
　図７の最初の処理ステップＳ１１では建築レイアウトの設定、処理ステップＳ１２ではビル設備の設定、処理ステップＳ１３では人の移動の設定を行い、これら一連処理の実行により、処理ステップＳ１４ではレイアウト情報Ｄ１と人モデルＤ２が形成され、それぞれ記憶部に記憶される。 In the first processing step S11 in FIG. 7, the building layout is set, in processing step S12 the building facilities are set, and in processing step S13 the movement of people is set. By executing this series of processing, layout information D1 and a human model D2 are formed in processing step S14, and each is stored in the memory unit.
　処理ステップＳ１５では、通路フラグメント処理を行うか否かを判断し、行う場合には処理ステップＳ１６において通路フラグメント処理を実行して横幅を同定し、続いて処理ステップＳ１７では、同定した幅に応じてボトルネックとなる位置であることを認定し、レイアウト情報Ｄ１に含めて記憶しておく。 In processing step S15, it is determined whether or not to perform aisle fragment processing. If so, in processing step S16, the aisle fragment processing is executed to identify the width, and then in processing step S17, it is determined that the position is a bottleneck based on the identified width, and this is stored as part of the layout information D1.
　なお、以下の図７、図８の処理フローでは、２組のボトルネック検出手法が採用された処理フローとしている。従っていずれか一方のボトルネック検出手法のみを採用するときには、処理ステップＳ１５、Ｓ２３における、通路フラグメント処理を行うか否かの判断処理を適宜削除する処理の流れとすればよい。 Note that the process flows in Figures 7 and 8 below employ two sets of bottleneck detection methods. Therefore, when only one of the bottleneck detection methods is employed, the process flow can be such that the process of determining whether or not to perform passage fragmentation processing in process steps S15 and S23 is appropriately deleted.
　シミュレーション中の処理である図８では、最初に処理ステップＳ２１において人流処理を行う環境のレイアウト情報Ｄ１と人モデルＤ２などを入手する。処理ステップＳ２２では、処理ステップＳ３０までの間で人モデルＭ１や処理時刻を変更しながら、繰り返し処理を実行する。なお、環境、従ってレイアウトは特定されているものとする。 In Figure 8, which shows the processing during the simulation, first in processing step S21, layout information D1 of the environment in which people flow processing is performed and human model D2 are obtained. In processing step S22, the processing is repeated while changing the human model M1 and the processing time up to processing step S30. Note that the environment, and therefore the layout, are assumed to be specified.
　繰り返し処理の中では、処理ステップＳ２３において、通過フラグメント処理が実行済みであるか、否かを判断する。実行済みでない場合には、処理ステップＳ２４において視野によるボトルネック認定処理を実行する。実行済みの場合、及び処理ステップＳ２４実行後には、処理ステップＳ２５の処理に移る。 In the repeated process, in processing step S23, it is determined whether or not the passing fragment process has been performed. If it has not been performed, in processing step S24, bottleneck recognition processing based on the field of view is performed. If it has been performed, or after processing step S24 has been performed, the process moves to processing step S25.
　処理ステップＳ２５の処理では、選択した人モデルＭ１について対向者Ｍ２が存在すること、及びボトルネックの確認状態に応じて、現在状態の判断を行う。これにより、通常時（ボトルネック無、対向者無）と、対向者検知状態と、対向者検知かつボトルネック状態の３態様に区分される。 In processing step S25, the current state is judged based on the presence of an oncoming person M2 for the selected human model M1 and the bottleneck confirmation state. This distinguishes between three states: normal (no bottleneck, no oncoming person), oncoming person detected, and oncoming person detected and bottleneck state.
　通常時とされたときには、処理ステップＳ２６において前方方向のコストを他方向よりも低く設定し、移動方向の先に対向者Ｍ２が存在することを検知するときは、処理ステップＳ２８において前方方向のコストを上昇させ、対向者検知かつボトルネック状態であるときは、処理ステップＳ２７において前方方向のコストを大幅上昇させる。 In normal times, the cost in the forward direction is set lower than in other directions in processing step S26, and when it is detected that an oncoming vehicle M2 is present in the direction of movement, the cost in the forward direction is increased in processing step S28, and when an oncoming vehicle is detected and a bottleneck condition exists, the cost in the forward direction is significantly increased in processing step S27.
　コスト操作処理を実行後は、処理ステップＳ２９に移動してコストに応じた進行方向決定、並びに人モデルを決定した進行方向への移動を実行する。なおこの処理が、図１の人移動実行部１２３の処理である。処理ステップＳ３０は繰り返しの終了判断処理であり、設定された人数分の人モデルに対して上記処理をシミュレーション期間にわたり、時刻を変更しながら繰り返す。この繰り返し処理は、時間軸に対しても実行されることで時系列的な人の流れのシミュレーションとなる。 After the cost operation process is executed, the process proceeds to processing step S29, where a direction of travel is determined according to the cost, and the human model is moved in the determined direction of travel. This process is the process of the human movement execution unit 123 in FIG. 1. Processing step S30 is a process for determining the end of the repetition, and the above process is repeated for the set number of human models over the simulation period while changing the time. This repetitive process is also executed on the time axis, resulting in a simulation of the flow of people over time.
　実施例１、実施例２によれば、ボトルネックに対しても対応が可能であり、納得感の高い人流シミュレーション結果を得ることができるシミュレーション装置及びシミュレーション方法を提供することができる。 According to the first and second embodiments, it is possible to provide a simulation device and a simulation method that can deal with bottlenecks and obtain highly convincing people flow simulation results.
１：シミュレーション装置、ＤＢ：記憶部、１２：演算部、１３：入出力装置、１４：バス、Ｄ１：レイアウト情報、Ｄ２：人モデル、１２１：ボトルネック検出部、１２２：人移動方向決定部、１２３：人移動実行部、１３１：入力部、１３２：出力部（表示部） 1: Simulation device, DB: Storage unit, 12: Calculation unit, 13: Input/output device, 14: Bus, D1: Layout information, D2: Human model, 121: Bottleneck detection unit, 122: Person movement direction determination unit, 123: Person movement execution unit, 131: Input unit, 132: Output unit (display unit)

Claims (6)

  1. 　人流を模擬するシミュレーション装置であって、
    　前記シミュレーション装置は記憶部と、シミュレーションの制御部とを備え、
    　前記記憶部は、レイアウト情報と、前記レイアウト情報内においてどこに向かうかを示す目的地情報と現在の位置情報を少なくとも保持する人モデルを記憶し、
    　前記制御部は、前記人モデルの移動方向前方の一定範囲内に人モデルの流量が制限されるボトルネックが検出される場合に、前記ボトルネックを検出していない場合から前記人モデルの移動制御を変更することを特徴とする、シミュレーション装置。     A simulation device for simulating people flow,
    The simulation device includes a storage unit and a simulation control unit,
    the storage unit stores layout information, and a human model that holds at least destination information indicating where the person is heading within the layout information and current position information;
    The simulation device is characterized in that the control unit changes movement control of the human model from a case where the bottleneck is not detected when a bottleneck that restricts the flow rate of the human model is detected within a certain range ahead of the movement direction of the human model.
  2. 　請求項１に記載のシミュレーション装置であって、
    　前記制御部は、前記ボトルネックを検出するボトルネック検出部と、前記人モデルの周囲の複数方向にコストを設定し、前記コストの大小により移動方向を決定する人移動方向決定部と、シミュレーション上で前記人モデルを移動させる人移動実行部を備え、
    　前記人移動方向決定部は、前記人モデルが現在位置から目的位置に至るルート上に対向者を検知するときに前記人モデルの前方方向の前記コストを第１の値に変更し、前記ボトルネックを検出しかつ前記ルート上に前記対向者を検知するときに前記人モデルの前方方向のコストを第２の値に変更することを特徴とするシミュレーション装置。     The simulation device according to claim 1 ,
    the control unit includes a bottleneck detection unit that detects the bottleneck, a human movement direction determination unit that sets costs in a plurality of directions around the human model and determines a movement direction depending on the magnitude of the costs, and a human movement execution unit that moves the human model in a simulation,
    The human movement direction determination unit changes the cost of the human model in the forward direction to a first value when the human model detects an oncoming person on the route from the current position to the destination position, and changes the cost of the human model in the forward direction to a second value when the bottleneck is detected and the oncoming person is detected on the route.
  3. 　請求項２に記載のシミュレーション装置であって、
    　前記ボトルネック検出部は、検出したボトルネックの位置情報を前記記憶部に保存し、前記人移動方向決定部は、前記記憶部に記憶された前記ボトルネックの位置情報を参照することを特徴とするシミュレーション装置。     The simulation device according to claim 2,
    A simulation device characterized in that the bottleneck detection unit stores location information of the detected bottleneck in the memory unit, and the person movement direction determination unit refers to the location information of the bottleneck stored in the memory unit.
  4. 　請求項２に記載のシミュレーション装置であって、
    　前記ボトルネック検出部は、シミュレーション中における、前記人モデルの移動方向決定時に前方の一定範囲内に前記人モデルの侵入できない領域が一定面積以上あれば、当該領域を前記ボトルネックとして検出することを特徴とするシミュレーション装置。     The simulation device according to claim 2,
    The simulation device is characterized in that, when a movement direction of the human model is determined during a simulation, if there is an area of a certain area or more that the human model cannot enter within a certain range forward, the bottleneck detection unit detects the area as the bottleneck.
  5. 　請求項２に記載のシミュレーション装置であって、
    　前記ボトルネックにより前記人モデルの通過幅が狭まるときに、通過幅に応じて前記第２の値を可変にすることを特徴とするシミュレーション装置。     The simulation device according to claim 2,
    a bottleneck that narrows a pass width of the human model, the bottleneck being configured to vary the second value in accordance with the pass width;
  6. 　人流を模擬するシミュレーション方法であって、
    　前記シミュレーション方法は記憶方法と、シミュレーションの制御方法とを備え、
    　前記記憶方法は、任意のレイアウト、及び前記レイアウト内のどこに向かうかを示す目的地情報と現在の位置情報を少なくとも保持する人モデルを記憶し、
    　前記制御方法は前記人モデルの視野の範囲に通路幅が狭いボトルネック領域が検出される場合に、対向者を避ける効果を通常より強めることを特徴とする、シミュレーション方法。     A simulation method for simulating a flow of people, comprising:
    The simulation method includes a storage method and a simulation control method,
    The storage method includes storing an arbitrary layout, and a human model that holds at least destination information indicating where the human model is heading within the layout and current position information;
    The control method is characterized in that, when a bottleneck area with a narrow passage width is detected within the visual field of the human model, the effect of avoiding oncoming people is strengthened more than usual.
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Citations (3)

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Publication number Priority date Publication date Assignee Title
WO2018211599A1 (en) * 2017-05-16 2018-11-22 富士通株式会社 Simulation program, simulation method, and simulation device
JP2020077222A (en) * 2018-11-08 2020-05-21 株式会社日立製作所 Pedestrian simulation device
JP2021135705A (en) * 2020-02-26 2021-09-13 トヨタテクニカルディベロップメント株式会社 Information processing device, information processing method and information processing program

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018211599A1 (en) * 2017-05-16 2018-11-22 富士通株式会社 Simulation program, simulation method, and simulation device
JP2020077222A (en) * 2018-11-08 2020-05-21 株式会社日立製作所 Pedestrian simulation device
JP2021135705A (en) * 2020-02-26 2021-09-13 トヨタテクニカルディベロップメント株式会社 Information processing device, information processing method and information processing program

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