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Modeling the dynamics of pedestrian evacuation in a complex environment

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  • Liu, Qiujia
  • Lu, Linjun
  • Zhang, Yijing
  • Hu, Miaoqing

Abstract

The study of crowd evacuation dynamics is important for the management of public safety, and crowd evacuation dynamics models can be used to simulate the behaviors of pedestrians during an evacuation. In this paper, we propose a new force model for simulation of the evacuation of complex environments. In comparison to existing models, this model considers more environmental factors to make it applicable to complex emergency environments. By verification using real data, the model is demonstrated to be able to predict evacuation efficiency and better reproduce the microscopic behavior of pedestrians under extreme conditions. We discuss the impact of the presence of different kinds of hazards and different types of obstacles in the environment on pedestrian evacuation performance and put forward suggestions for crowd evacuation management.

Suggested Citation

  • Liu, Qiujia & Lu, Linjun & Zhang, Yijing & Hu, Miaoqing, 2022. "Modeling the dynamics of pedestrian evacuation in a complex environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    • Handle: RePEc:eee:phsmap:v:585:y:2022:i:c:s0378437121006993
    DOI: 10.1016/j.physa.2021.126426
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    References listed on IDEAS

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    Cited by:

    1. Jiaying Qin & Sasa Ma & Lei Zhang & Qianling Wang & Guoce Feng, 2022. "Modeling and Simulation for Non-Motorized Vehicle Flow on Road Based on Modified Social Force Model," Mathematics, MDPI, vol. 11(1), pages 1-18, December.
    2. Xianing Wang & Zhan Zhang & Ying Wang & Jun Yang & Linjun Lu, 2022. "A Study on Safety Evaluation of Pedestrian Flows Based on Partial Impact Dynamics by Real-Time Data in Subway Stations," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    3. Faizul Chasanah & Hiroyuki Sakakibara, 2022. "Implication of Mutual Assistance Evacuation Model to Reduce the Volcanic Risk for Vulnerable Society: Insight from Mount Merapi, Indonesia," Sustainability, MDPI, vol. 14(13), pages 1-23, July.
    4. Zhang, Yijing & Lu, Linjun & Liu, Qiujia & Hu, Miaoqing, 2023. "Modeling of low-risk behavior of pedestrian movement based on dynamic data analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
    5. Liu, Zongtuan & Dong, Gang & Gui, Yunmiao, 2023. "Data-driven emergency evacuation decision for cruise ports under COVID-19: An improved genetic algorithm and simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    6. Ding, Ning & Zhu, Yu & Liu, Xinyan & Dong, Dapeng & Wang, Yang, 2024. "A modified social force model for crowd evacuation considering collision predicting behaviors," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    7. Yuan, Shuaiqi & Cai, Jitao & Reniers, Genserik & Yang, Ming & Chen, Chao & Wu, Jiansong, 2022. "Safety barrier performance assessment by integrating computational fluid dynamics and evacuation modeling for toxic gas leakage scenarios," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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