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Experiment and simulation of the bidirectional pedestrian flow model with overtaking and herding behavior

Author

Listed:
  • Jun Hu

    (Faculty of Computer Science, Chengdu Normal University, Chengdu 611130, China;
    School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Zhongwen Li

    (College of Information Science and Technology, Chengdu University, Chengdu 610106, China)

  • Hong Zhang

    (College of Information Science and Technology, Chengdu University, Chengdu 610106, China)

  • Juan Wei

    (Faculty of Computer Science, Chengdu Normal University, Chengdu 611130, China)

  • Lei You

    (Faculty of Computer Science, Chengdu Normal University, Chengdu 611130, China;
    College of Information Science and Technology, Chengdu University, Chengdu 610106, China)

  • Peng Chen

    (Faculty of Computer Science, Chengdu Normal University, Chengdu 611130, China)

Abstract

In order to effectively depict the characteristics of bidirectional pedestrian flow, a novel pedestrian flow model is proposed based on cellular automata. At first, according to direction gain, velocity gain and herding gain, the calculation formula of target position is defined, and the walking rules by combining overtaking behavior and herding behavior are given in the model. Meanwhile, the actual channel is used for experiments, where the self-organizing effect formed by pedestrian flow is observed. The simulation platform is established to study the key factors influencing pedestrian flow characteristics. The numerical analysis results showed that when the pedestrian density in the channel reached to the critical degree, the overtaking behavior can easily produce jamming. Moreover, pedestrians' rational choice is good for relieving jamming.

Suggested Citation

  • Jun Hu & Zhongwen Li & Hong Zhang & Juan Wei & Lei You & Peng Chen, 2015. "Experiment and simulation of the bidirectional pedestrian flow model with overtaking and herding behavior," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(11), pages 1-14.
    • Handle: RePEc:wsi:ijmpcx:v:26:y:2015:i:11:n:s0129183115501314
    DOI: 10.1142/S0129183115501314
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    Citations

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    Cited by:

    1. Zhao, Xuedan & Xia, Long & Zhang, Jun & Song, Weiguo, 2020. "Artificial neural network based modeling on unidirectional and bidirectional pedestrian flow at straight corridors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    2. Ding, Ning & Chen, Tao & Zhu, Yu & Lu, Yang, 2021. "State-of-the-art high-rise building emergency evacuation behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    3. Ning Ding, 2020. "The effectiveness of evacuation signs in buildings based on eye tracking experiment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 1201-1218, August.
    4. Sobhana, Karthika P. & Choubey, Nipun & Verma, Ashish, 2023. "Modelling and simulating the leader–follower behaviour of pedestrians in unidirectional flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).

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