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Dynamics of pedestrians in regions with no visibility— A lattice model without exclusion

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  • Cirillo, Emilio N.M.
  • Muntean, Adrian

Abstract

We investigate the motion of pedestrians through obscure corridors where the lack of visibility (due to smoke, fog, darkness, etc.) hides the precise position of the exits. We focus our attention on a set of basic mechanisms, which we assume to be governing the dynamics at the individual level. Using a lattice model, we explore the effects of non-exclusion on the overall exit flux (evacuation rate). More precisely, we study the effect of the buddying threshold (of no-exclusion per site) on the dynamics of the crowd and investigate to which extent our model confirms the following pattern revealed by investigations on real emergencies: If the evacuees tend to cooperate and act altruistically, then their collective action tends to favor the occurrence of disasters. The research reported here opens many fundamental questions and should be seen therefore as a preliminary investigation of the very complex behavior of the people and their motion in dark regions.

Suggested Citation

  • Cirillo, Emilio N.M. & Muntean, Adrian, 2013. "Dynamics of pedestrians in regions with no visibility— A lattice model without exclusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3578-3588.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:17:p:3578-3588
    DOI: 10.1016/j.physa.2013.04.029
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    References listed on IDEAS

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    1. Guo, Ren-Yong & Huang, Hai-Jun & Wong, S.C., 2012. "Route choice in pedestrian evacuation under conditions of good and zero visibility: Experimental and simulation results," Transportation Research Part B: Methodological, Elsevier, vol. 46(6), pages 669-686.
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    5. Guo, Xiwei & Chen, Jianqiao & Zheng, Yaochen & Wei, Junhong, 2012. "A heterogeneous lattice gas model for simulating pedestrian evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 582-592.
    6. Iain D. Couzin & Jens Krause & Nigel R. Franks & Simon A. Levin, 2005. "Effective leadership and decision-making in animal groups on the move," Nature, Nature, vol. 433(7025), pages 513-516, February.
    7. Kirchner, Ansgar & Schadschneider, Andreas, 2002. "Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(1), pages 260-276.
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    Cited by:

    1. Li, Xingli & Guo, Fang & Kuang, Hua & Geng, Zhongfei & Fan, Yanhong, 2019. "An extended cost potential field cellular automaton model for pedestrian evacuation considering the restriction of visual field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 47-56.
    2. Li, Na & Guo, Ren-Yong, 2020. "Simulation of bi-directional pedestrian flow through a bottleneck: Cell transmission model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    3. Tu, Lihua & Zhou, Jie, 2019. "Memory’s effect on bidirectional pedestrian flow based on lattice hydrodynamic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    4. Wan, Jiahui & Sui, Jie & Yu, Hua, 2014. "Research on evacuation in the subway station in China based on the Combined Social Force Model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 33-46.
    5. Cirillo, Emilio N.M. & Krehel, Oleh & Muntean, Adrian & van Santen, Rutger & Sengar, Aditya, 2016. "Residence time estimates for asymmetric simple exclusion dynamics on strips," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 436-457.
    6. Jiang, Yan-Qun & Zhang, Wei & Zhou, Shu-Guang, 2016. "Comparison study of the reactive and predictive dynamic models for pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 51-61.
    7. Lovreglio, Ruggiero & Ronchi, Enrico & Nilsson, Daniel, 2015. "Calibrating floor field cellular automaton models for pedestrian dynamics by using likelihood function optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 308-320.

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