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A perception-based emotion contagion model in crowd emergent evacuation simulation

Ma, Minhua, Liu, Zhen, Liu, Tingting, Hsu, Hui-Huang, Ni, Zhongrui and Chai, Yanjie (2018) A perception-based emotion contagion model in crowd emergent evacuation simulation. Computer Animation and Virtual Worlds, 29 (e1817). ISSN 1546-4261

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Abstract or description

With the increasing number of emergencies, the crowd simulation technology has attracted wide attention in recent years. Existing emergencies have shown that individuals are easy to be influenced by other’s emotion during the evacuation. This will make it easier for people to aggregate together and increase security risks. Some of the existing evacuation models without considering emotion are therefore not suitable for describing crowd behaviors in emergencies. We propose a perception-based emotion contagion model and use multi-agent technology to simulate the crowd behaviors. Navigation points are introduced to guide the movement of the agents. Based on the proposed model, a prototype simulation system for crowd emotion contagion is developed. The comparative simulation experiments verify that the model can effectively deduct the evacuation time and crowd emotion contagion. The proposed model could be an assistant analysis method for crowd management in emergencies.

Item Type: Article
Additional Information: "This is the peer reviewed version of the following article: Zhen Liu, Tingting Liu, Minhua Ma, Hui-Huang Hsu, Zhongrui Ni, Yanjie Chai (2018) A perception-based emotion contagion model in crowd emergent evacuation simulation. In Computer Animation & Virtual Worlds, e1817, Wiley. DOI:10.1002/cav.1817 , which has been published in final form at http://doi.org/10.1002/cav.1817. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions."
Faculty: School of Computing and Digital Technologies > Games and Visual Effects
Depositing User: Library STORE team
Date Deposited: 04 Jun 2018 08:51
Last Modified: 24 Feb 2023 13:51
URI: https://eprints.staffs.ac.uk/id/eprint/4471

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