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Emergence of cooperation during an emergency evacuation

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  • Cheng, Yuan
  • Zheng, Xiaoping

Abstract

Understanding how crowds behave in an emergency has long been held to be necessary to emergency response and management. Competition due to mass panic is often assumed to be a natural response during emergencies, which is in contrast with the current psychological research that evacuees rarely demonstrate competitive behaviors, but do exhibit cooperative behaviors. In this work cooperative behaviors and evacuation efficiency has been examined in detail by using a cellular automata evacuation model from a game-theoretical perspective. Simulation results show that the self-regarding evacuees are able to be cooperative to each other when faced with an emergency. It is found that during an emergency evacuation high levels of escape aspiration promote cooperation among evacuees while in non-emergency situations they inhibit cooperative behaviors, and heterogeneous learning rates for different strategies can lead to various levels of cooperation. This work provides a new insight into crowd behaviors in an emergency evacuation.

Suggested Citation

  • Cheng, Yuan & Zheng, Xiaoping, 2018. "Emergence of cooperation during an emergency evacuation," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 485-494.
    • Handle: RePEc:eee:apmaco:v:320:y:2018:i:c:p:485-494
    DOI: 10.1016/j.amc.2017.10.011
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    References listed on IDEAS

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    Cited by:

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    2. Ren, Huan & Yan, Yuyue & Gao, Fengqiang, 2021. "Variable guiding strategies in multi-exits evacuation: Pursuing balanced pedestrian densities," Applied Mathematics and Computation, Elsevier, vol. 397(C).
    3. Qing Yang & Ying Sun & Xingxing Liu & Jinmei Wang, 2020. "MAS-Based Evacuation Simulation of an Urban Community during an Urban Rainstorm Disaster in China," Sustainability, MDPI, vol. 12(2), pages 1-19, January.
    4. Zhou, Bo & Song, Qiankun & Zhao, Zhenjiang & Liu, Tangzhi, 2020. "A reinforcement learning scheme for the equilibrium of the in-vehicle route choice problem based on congestion game," Applied Mathematics and Computation, Elsevier, vol. 371(C).
    5. Cao, Shuchao & Fu, Libi & Song, Weiguo, 2018. "Exit selection and pedestrian movement in a room with two exits under fire emergency," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 136-147.
    6. Guan, Junbiao & Wang, Kaihua, 2019. "Towards pedestrian room evacuation with a spatial game," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 492-501.
    7. Miyagawa, Daiki & Ichinose, Genki, 2020. "Cellular automaton model with turning behavior in crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    8. Zou, Baobao & Lu, Chunxia & Mao, Shirong & Li, Yi, 2020. "Effect of pedestrian judgement on evacuation efficiency considering hesitation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    9. Guan, Junbiao & Wang, Kaihua, 2020. "Cooperative evolution in pedestrian room evacuation considering different individual behaviors," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    10. Gao, Fengqiang & Yan, Yuyue & Chen, Zhihao & Zheng, Linxiao & Ren, Huan, 2022. "Effect of density control in partially observable asymmetric-exit evacuation under guidance: Strategic suggestion under time delay," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    11. Yang, Xiaoxia & Yang, Xiaoli & Xue, Shuqi & Zhang, Jihui & Pan, Fuquan & Kang, Yuanlei & Wang, Qianling, 2019. "The effect of waiting area design at the metro platform on passengers’ alighting and boarding behaviors," Applied Mathematics and Computation, Elsevier, vol. 358(C), pages 177-193.

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