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A dual adaptive cellular automaton model based on a composite field and pedestrian heterogeneity

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  • Zhang, Xinwei
  • Zhang, Peihong
  • Zhong, Maohua

Abstract

To better reveal the law of pedestrian flow and the mechanism of crowd accidents, this paper establishes a dual adaptive cellular automaton model (DACA) that integrates pedestrian heterogeneity, local density, target distance and asynchronous behaviour. The validity of the model is verified, and when the crowd density is greater than 3 persons/m2, the free movement of pedestrians is generally constrained by crowd density. In contrast, the critical density that affects the velocity of pedestrian movement is positively correlated with the complete free movement velocity (CFMV) of pedestrians. The steady-state density of the straight channel is negatively correlated with CFMV. A negative correlation between CFMV and the average crowd density at maximum flow is observed, and the time from highest density to steady density is independent of CFMV, but when the density is not the limit, the crowd dredging time is related to CFMV and the initial density of congestion. Finally, a case study of the start-up characteristics of a static crowd in a straight channel shows that the transmission speed of the start information under the limit density is greater than the moving speed of the crowd. The self-dredging process of crowds consumes additional time. The crowd distribution is sparse in the front and dense in the tail, and the crowd gathering risk is found to be directly proportional to the initial crowd density at the acceptable risk level. This study can effectively explore the laws of crowd movement and provide a theoretical reference for crowd safety management.

Suggested Citation

  • Zhang, Xinwei & Zhang, Peihong & Zhong, Maohua, 2021. "A dual adaptive cellular automaton model based on a composite field and pedestrian heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    • Handle: RePEc:eee:phsmap:v:583:y:2021:i:c:s0378437121006075
    DOI: 10.1016/j.physa.2021.126334
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    Cited by:

    1. Dong, Shiyu & Huang, Ping & Wang, Wei, 2022. "An optimization method for evacuation guidance under limited visual field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    2. 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).
    3. Zhihai, Tang & Longcheng, Yang & Jun, Hu & Xiaoning, Li & Lei, You, 2024. "An improved social force model for improving pedestrian avoidance by reducing search size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).

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