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Study on evacuation behaviors at a T-shaped intersection by a force-driving cellular automata model

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  • Chen, Chang-Kun
  • Li, Jian
  • Zhang, Dong

Abstract

A force-driving cellular automata model considering the social force on cell movement, such as the desirous willing of a pedestrian to exit, the repulsive interaction among pedestrians or between pedestrians and obstacles, was set up to investigate the evacuation behaviors of pedestrians at a T-shaped intersection. And an analogical formulation, taking reference of the magnetic force, was introduced to describe the above repulsive actions. Based on the model, the evacuation behaviors of pedestrians were simulated in terms of different pedestrian density, distribution and corridor width, and then evacuation time was obtained and analyzed. Furthermore, an experiment was conducted to verify the results of the presented model. The results demonstrate that when the density of pedestrians is greater than a certain threshold, pedestrians of a certain direction would be jammed by the repulsion from pedestrians of the counter flow from another direction, and the evacuation time of the former would be longer, even though they are closer to the exit, which would possibly result in a serious casualty in an emergency circumstance. And the phenomenon has been validated by the experiments well. In addition, a corresponding critical corridor width related to different DOPs, beyond which the evacuation time could be decreased rapidly due to a strong degradation of jamming behaviors near the T-shaped intersection, was also discovered and predicted by the proposed model.

Suggested Citation

  • Chen, Chang-Kun & Li, Jian & Zhang, Dong, 2012. "Study on evacuation behaviors at a T-shaped intersection by a force-driving cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2408-2420.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:7:p:2408-2420
    DOI: 10.1016/j.physa.2011.12.001
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    References listed on IDEAS

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    4. Ling Yin & Jie Chen & Hao Zhang & Zhile Yang & Qiao Wan & Li Ning & Jinxing Hu & Qi Yu, 2020. "Improving emergency evacuation planning with mobile phone location data," Environment and Planning B, , vol. 47(6), pages 964-980, July.
    5. Li, Jun & Fu, Siyao & He, Haibo & Jia, Hongfei & Li, Yanzhong & Guo, Yi, 2015. "Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 304-321.
    6. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
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    8. Liu, Yixue & Mao, Zhanli, 2022. "An experimental study on the critical state of herd behavior in decision-making of the crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    9. 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).
    10. Li, Yongxing & Yang, Xiaoxia & Wang, Zijia & Chen, Liang & Chen, Yanyan, 2022. "Lane-design for mixed pedestrian flow in T-shaped passage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
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