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A weighted evolving network model for pedestrian evacuation

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  • Huang, Keke
  • Zheng, Xiaoping

Abstract

We examine how the dynamics of dependency relationship between evacuees affect the evacuation time and cooperative behavior. First, we place the population in a weighted network, and then model the dynamics of dependency relationship between evacuees by letting link weights to evolve. By careful examination of the parameter space, the simulation results indicated that a weaker link weight evolution weakens the local behavioral factor in the evacuation process, which further enhance the efficiency of crowd evacuation. On the contrary, a stronger link weight evolution promotes heterogeneity of the crowd, thus strengthening the local behavioral factor in the evacuation process and prolonging the evacuation time. In addition, we conduct a simple experiment: evacuation of a room with two exits. By adjusting the length of two exits, we can guide the gathering behavior and regulate the crowd evacuation. This experiment can also provide an explanation for why the exits should located symmetrical in the middle of a wall.

Suggested Citation

  • Huang, Keke & Zheng, Xiaoping, 2017. "A weighted evolving network model for pedestrian evacuation," Applied Mathematics and Computation, Elsevier, vol. 298(C), pages 57-64.
    • Handle: RePEc:eee:apmaco:v:298:y:2017:i:c:p:57-64
    DOI: 10.1016/j.amc.2016.10.040
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    References listed on IDEAS

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    1. 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.
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    6. Zheng, Ying & Jia, Bin & Li, Xin-Gang & Zhu, Nuo, 2011. "Evacuation dynamics with fire spreading based on cellular automaton," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(18), pages 3147-3156.
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    Citations

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    Cited by:

    1. Guan, Junbiao & Wang, Kaihua, 2020. "Cooperative evolution in pedestrian room evacuation considering different individual behaviors," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    2. 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).
    3. Hu, Xiangmin & Chen, Tao & Deng, Kaifeng & Wang, Guanning, 2023. "Effects of aggressiveness on pedestrian room evacuation using extended cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    4. 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).
    5. Kurdi, Heba & Almulifi, Asma & Al-Megren, Shiroq & Youcef-Toumi, Kamal, 2021. "A balanced evacuation algorithm for facilities with multiple exits," European Journal of Operational Research, Elsevier, vol. 289(1), pages 285-296.
    6. 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.
    7. Can Liao & Kejun Zhu & Haixiang Guo & Jian Tang, 2019. "Simulation Research on Safe Flow Rate of Bidirectional Crowds Using Bayesian-Nash Equilibrium," Complexity, Hindawi, vol. 2019, pages 1-15, January.
    8. 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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