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Simulation of pedestrian counter flow through bottlenecks by using an agent-based model

Author

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  • Dai, Jicai
  • Li, Xia
  • Liu, Lin

Abstract

Considerable research has been conducted on the topic of unidirectional evacuations from exits. However, few studies aim at simulating counter flow through a bottleneck with complex conflict. This paper proposes an agent-based model to investigate bidirectional flow evacuation. Pedestrian speed is determined by the speed of the leading agent and the surrounding agents. The moving direction of pedestrian originates from four forces, namely, gradient force, repulsive force, resistance force, and random force. These four forces dominate the main stream of the pedestrian moving trajectory, the interaction between pedestrians and their local environment, the resistance or disinclination to movement, and the random variations and chaotic nature of pedestrian dynamics. The novelty of this research is in the agent-based model that combines the agent and forces while providing insights for the simulation of the pedestrian dynamic on the cognitive level. The experiment results show that the behavior that arises from this model is consistent with the observations from Guangzhou Metro and that this model could help capture the essence of pedestrian behavior near egresses.

Suggested Citation

  • Dai, Jicai & Li, Xia & Liu, Lin, 2013. "Simulation of pedestrian counter flow through bottlenecks by using an agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2202-2211.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:9:p:2202-2211
    DOI: 10.1016/j.physa.2013.01.012
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    Citations

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    Cited by:

    1. 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).
    2. Li, Zitong & Lo, S.M. & Ma, Jian & Luo, X.W., 2020. "A study on passengers’ alighting and boarding process at metro platform by computer simulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 840-854.
    3. Li, Shuying & Zhuang, Jun & Shen, Shifei & Wang, Jia, 2017. "Driving-forces model on individual behavior in scenarios considering moving threat agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 127-140.
    4. Guo, Ren-Yong, 2014. "Simulation of spatial and temporal separation of pedestrian counter flow through a bottleneck," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 428-439.
    5. Nimrod Serok & Efrat Blumenfeld-Lieberthal, 2015. "A Simulation Model for Intra-Urban Movements," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    6. Li, Yang & Yang, Xin & Wu, Jianjun & Sun, Huijun & Guo, Xin & Zhou, Li, 2021. "Discrete-event simulations for metro train operation under emergencies: A multi-agent based model with parallel computing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    7. Jiang, Yan-Qun & Hu, Ying-Gang & Huang, Xiaoqian, 2022. "Modeling pedestrian flow through a bottleneck based on a second-order continuum model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    8. Leng, Biao & Wang, Jianyuan & Xiong, Zhang, 2015. "Pedestrian simulations in hexagonal cell local field model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 532-543.
    9. Wang, Jia & Ni, Shunjiang & Shen, Shifei & Li, Shuying, 2019. "Empirical study of crowd dynamic in public gathering places during a terrorist attack event," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1-9.

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