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Behavior-based cellular automaton model for pedestrian dynamics

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  • Huang, Keke
  • Zheng, Xiaoping
  • Cheng, Yuan
  • Yang, Yeqing

Abstract

Pedestrian evacuation is one open question in a myriad of scientific disciplines and has attracted considerable attention during the past decades. Aim to issue, various research approaches, such as mathematical modeling and simulation, experimental studied and socio-psychology surveys, have been extensively employed. Different from previous frameworks, here a behavior-based cellular automaton model is proposed, which involves the environmental characteristics and neighbors’ behaviors. Given the certain range of degree of emergency, it is shown that enhancing the degree of emergency will shorten evacuation time yet decrease cooperation enthusiasm. The larger the degree of familiarity is, the shorter the evacuation time will be. In variance, larger the dependence of pedestrians will prolong the evacuation time. Besides, the novel model also produces some interesting self-organization phenomena, such as the collective behavior at the beginning of the evacuation and arch-like blocking at the end of the evacuation. When our model is finally applied to the evacuation scenario where a room has two symmetrically located exits, the symmetry breaking effect takes place. Our model may shed new light to the study of pedestrian dynamics in realistic world.

Suggested Citation

  • Huang, Keke & Zheng, Xiaoping & Cheng, Yuan & Yang, Yeqing, 2017. "Behavior-based cellular automaton model for pedestrian dynamics," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 417-424.
    • Handle: RePEc:eee:apmaco:v:292:y:2017:i:c:p:417-424
    DOI: 10.1016/j.amc.2016.07.002
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    References listed on IDEAS

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    Cited by:

    1. Yaping Ma & Xiaoying Liu & Feizhou Huo & Hui Li, 2022. "Analysis of Cooperation Behaviors and Crowd Dynamics during Pedestrian Evacuation with Group Existence," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    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. 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.
    4. 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).
    5. Lu, Peng & Wen, Feier & Li, Yan & Chen, Dianhan, 2021. "Multi-agent modeling of crowd dynamics under mass shooting cases," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    6. Lu, Jinna & Wang, Lu & Wang, Yi-Ling & Zhang, Xiaoguang, 2017. "Logit selection promotes cooperation in voluntary public goods game," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 134-138.
    7. 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).
    8. Huang, Keke & Zheng, Xiaoping, 2017. "A weighted evolving network model for pedestrian evacuation," Applied Mathematics and Computation, Elsevier, vol. 298(C), pages 57-64.
    9. Kang, Zengxin & Zhang, Lei & Li, Kun, 2019. "An improved social force model for pedestrian dynamics in shipwrecks," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 355-362.

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