Representing crowds using a multi‐agent model – Development of the SimTread pedestrian simulation system

Kondo, Takahisa; Sano, Takeshi; Hayashida, Kentaro; Takeichi, Naohiro; Minegishi, Yoshikazu; Yoshida, Yoshiyuki; Watanabe, Hitoshi

doi:10.1002/2475-8876.12073

Cited by 7 publications

(8 citation statements)

References 6 publications

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“…Inspired by the fluid flow paradigm of Henderson [ 15 ] and others, Helbing and Molnar’s social force model (SFM) [ 38 ] is a microscopic, continuous model which uses ‘attractive’ and ‘repulsive’ force fields between individuals (and between individuals and their environment) to guide movement. The SFM provides the base movement model for a number of pedestrian simulation packages, including FDS + Evac [ 39 ], PedSim [ 40 ], SimWalk [ 41 ] and MassMotion [ 42 ], and it has been used extensively in movement research. Additionally, the SFM has been validated using real-world data [ 20 , 23 ], and the comprehensive review of [ 37 ] recommends its use in pedestrian movement studies.…”

Section: Methodsmentioning

confidence: 99%

A Turing test for crowds

Webster

Amos

2020

R. Soc. open sci.

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The accuracy and believability of crowd simulations underpins computational studies of human collective behaviour, with implications for urban design, policing, security and many other areas. Accuracy concerns the closeness of the fit between a simulation and observed data, and believability concerns the human perception of plausibility. In this paper, we address both issues via a so-called ‘Turing test’ for crowds, using movies generated from both accurate simulations and observations of real crowds. The fundamental question we ask is ‘Can human observers distinguish between real and simulated crowds?’ In two studies with student volunteers ( n = 384 and n = 156), we find that non-specialist individuals are able to reliably distinguish between real and simulated crowds when they are presented side-by-side, but they are unable to accurately classify them. Classification performance improves slightly when crowds are presented individually, but not enough to out-perform random guessing. We find that untrained individuals have an idealized view of human crowd behaviour which is inconsistent with observations of real crowds. Our results suggest a possible framework for establishing a minimal set of collective behaviours that should be integrated into the next generation of crowd simulation models.

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Section: Methodsmentioning

confidence: 99%

A Turing test for crowds

Webster

Amos

2020

R. Soc. open sci.

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“…In Plan-A3, while the width of Stairs 1 is reduced by half, reduction of flow volume to the stairways causes an uncontainable accumulation in the concourse (3), and there is a sequencing of the accumulation into the spectator seats ( 4). If such an accumulation occurs, it will take a significantly longer time to complete the evacuation from the spectator seats (5). While Exit 1 is closed in Plan-A4, and there is no accumulation in the concourse, the spectator seat accumulation conditions are at a similar level to those in Plan-A2 and Plan-A3.…”

Section: Observation Of Concourse Accumulation Behaviormentioning

confidence: 96%

Design guidelines for crowd evacuation in a stadium for controlling evacuee accumulation and sequencing

Minegishi

Takeichi

2018

Japan Architectural Review

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In the design of large‐scale sports facilities, architectural and fire‐service regulations are consulted to secure evacuation safety. However, these regulations define only the number, width, or amount of evacuation facilities, such as the path, exit, and stairs. These regulations not only limit the flexibility of the architectural design, but also not clarify that how evacuees should be secured or controlled under emergency situation. For this circumstance, we propose guidelines for the design and management of crowd evacuation by showing the process of an actual design project for a large‐scale 40 000‐seat stadium using a multi‐agent evacuation simulator. We mainly discuss three situations: (i) evacuation from the spectator stands, (ii) merging and accumulation around stairs, and (iii) evacuation to/on the ground. We clarify that most problems emerge from the accumulation of evacuees and the accumulation sequencing. We hence propose a design method and crowd management policy that avoid generation of a sequence of accumulations and while guiding on where accumulations should be generated.

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“…Unlike network and mesh models, this pedestrian model is a multi-agent system, where an individual pedestrian is modelled as an agent, and the spatial model is based on actual coordinates; this enables the direct representation of plans. [2] The crowd characteristics represented by this system have been evaluated through test cases by measuring the flow rate, a primary indicator of crowd evaluation [3][4].…”

Section: Human Behaviour -Multi-agent Simulationmentioning

confidence: 99%

Virtual Reality approaches for evacuation simulation of various disasters

et al. 2020

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This paper presents a virtual reality (VR) system of evacuation in the cases of various disasters. We considered a combination of disasters under realistic scenarios. Disaster simulations by numerical models were imported into the VR system to express a realistic situation. Not only disaster experts but also designers and non-professionals are able to share realistic experiences for escape from the disasters. This system is useful for performance-based design, planning of escape, disaster prevention, evacuation drill etc. The VR system consists of Building Information Modelling, physical simulation models for disasters and human behaviour’s simulation.

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Representing crowds using a multi‐agent model – Development of the SimTread pedestrian simulation system

Cited by 7 publications

References 6 publications

A Turing test for crowds

A Turing test for crowds

Design guidelines for crowd evacuation in a stadium for controlling evacuee accumulation and sequencing

Virtual Reality approaches for evacuation simulation of various disasters

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