research-article

Modeling Gap Seeking Behaviors for Agent-based Crowd Simulation

Authors:

Jianfeng MaAuthors Info & Claims

CASA '16: Proceedings of the 29th International Conference on Computer Animation and Social Agents

Pages 37 - 43

https://doi.org/10.1145/2915926.2915944

Published: 23 May 2016 Publication History

Abstract

Research on agent-based crowd simulation has gained tremendous momentum in recent years due to the increase of computing power. One key issue in this research area is to develop various behavioral models to capture the microscopic behaviors of individuals (i.e., agents) in a crowd. In this paper, we propose a novel behavior model for modeling the gap seeking behavior which can be frequently observed in real world scenarios where an individual in a crowd proactively seek for gaps in the crowd flow so as to minimize potential collision with other people. We propose a two-level modeling framework and introduce a gap seeking behavior model as a proactive conflict minimization maneuver at global navigation level. The model is integrated with the reactive collision avoidance model at local steering level. We evaluate our model by simulating a real world scenario. The results show that our model can generate more realistic crowd behaviors compared to the classical social-force model in the given scenario.

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Cited By

Khan SDeng Z(2024)Agent-based crowd simulation: an in-depth survey of determining factors for heterogeneous behaviorThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-024-03503-240:7(4993-5004)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00371-024-03503-2
Muhammed Anees VSanthosh Kumar G(2022)Identification of crowd behaviour patterns using stability analysisJournal of Intelligent & Fuzzy Systems10.3233/JIFS-20066742:4(2829-2843)Online publication date: 4-Mar-2022
https://doi.org/10.3233/JIFS-200667
Yuan ZGuo RTang SHe BBian LLi Y(2019)Simulation of the Separating Crowd Behaviour in a T-shaped Channel Based on the Social Force ModelIEEE Access10.1109/ACCESS.2019.2894345(1-1)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2894345
Show More Cited By

Modeling Gap Seeking Behaviors for Agent-based Crowd Simulation
1. Computing methodologies
  1. Computer graphics

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Published In

cover image ACM Other conferences

CASA '16: Proceedings of the 29th International Conference on Computer Animation and Social Agents

May 2016

200 pages

ISBN:9781450347457

DOI:10.1145/2915926

Conference Chairs:
Nadia Magnenat Thalmann
MIRALab, University of Geneva and NTU Singapore
,
Marina L. Gavrilova
University of Calgary, Canada
,
Program Chairs:
Taku Komura
Edingburgh University, UK
,
Frederic Cordier
University of Haute-Alsace, France
,
Daniel Thalmann
NTU, Singapore & EPFL, Switzerland

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2016

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Refereed limited

Funding Sources

China 111 Project
Fundamental Research Funds for the Central
National Natural Science Foundation of China

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CASA '16

CASA '16: Computer Animation and Social Agents

May 23 - 25, 2016

Geneva, Switzerland

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Overall Acceptance Rate 18 of 110 submissions, 16%

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Cited By

Khan SDeng Z(2024)Agent-based crowd simulation: an in-depth survey of determining factors for heterogeneous behaviorThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-024-03503-240:7(4993-5004)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00371-024-03503-2
Muhammed Anees VSanthosh Kumar G(2022)Identification of crowd behaviour patterns using stability analysisJournal of Intelligent & Fuzzy Systems10.3233/JIFS-20066742:4(2829-2843)Online publication date: 4-Mar-2022
https://doi.org/10.3233/JIFS-200667
Yuan ZGuo RTang SHe BBian LLi Y(2019)Simulation of the Separating Crowd Behaviour in a T-shaped Channel Based on the Social Force ModelIEEE Access10.1109/ACCESS.2019.2894345(1-1)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2894345
Luo LChai CMa JZhou SCai W(2017)ProactiveCrowd: Modelling Proactive Steering Behaviours for Agent‐Based Crowd SimulationComputer Graphics Forum10.1111/cgf.1330337:1(375-388)Online publication date: 21-Sep-2017
https://doi.org/10.1111/cgf.13303

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