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Detection of Primitive Collective Behaviours in a Crowd Panic Simulation Based on Multi-Agent Approach

Detection of Primitive Collective Behaviours in a Crowd Panic Simulation Based on Multi-Agent Approach

Jérémy Patrix, Abdel-Illah Mouaddib, Sylvain Gatepaille
Copyright: © 2012 |Volume: 3 |Issue: 3 |Pages: 16
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781466614352|DOI: 10.4018/jsir.2012070104
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MLA

Patrix, Jérémy, et al. "Detection of Primitive Collective Behaviours in a Crowd Panic Simulation Based on Multi-Agent Approach." IJSIR vol.3, no.3 2012: pp.50-65. http://doi.org/10.4018/jsir.2012070104

APA

Patrix, J., Mouaddib, A., & Gatepaille, S. (2012). Detection of Primitive Collective Behaviours in a Crowd Panic Simulation Based on Multi-Agent Approach. International Journal of Swarm Intelligence Research (IJSIR), 3(3), 50-65. http://doi.org/10.4018/jsir.2012070104

Chicago

Patrix, Jérémy, Abdel-Illah Mouaddib, and Sylvain Gatepaille. "Detection of Primitive Collective Behaviours in a Crowd Panic Simulation Based on Multi-Agent Approach," International Journal of Swarm Intelligence Research (IJSIR) 3, no.3: 50-65. http://doi.org/10.4018/jsir.2012070104

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Abstract

In case of emergency and evacuation, it is often impossible to interpret manually the complex behaviour of a crowd, essentially due to the lack of staff and time needed to understand a situation. In the literature, a monitored system using data fusion methods makes it possible to perform automatic situation awareness. Using Swarm Intelligence domain, the authors propose an approach based on multi-agent system to simulate and detect primitive collective behaviours emerging from a crowd panic. It enables anticipating collective behaviours in real-time as well as their anomalies according to specific scenarios. Detection is the possibility to learn, recognize and anticipate different behaviours by a probabilistic model. The collective behaviour detection of a crowd panic in real-time is based on a learning method on an extended model of Hidden Markov Model. This paper presents experiments of simulation and detection using an implementation of a virtual environment.

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