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Comparison study of the reactive and predictive dynamic models for pedestrian flow

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  • Jiang, Yan-Qun
  • Zhang, Wei
  • Zhou, Shu-Guang

Abstract

This paper formulates the reactive and predictive dynamic models for pedestrian flow and presents a comparison of the two models. The path-choice behavior of pedestrians in the reactive dynamic model is described that pedestrians tend to walk along a path with the lowest instantaneous cost. The desired walking direction of pedestrians in the predictive dynamic model is chosen to minimize the actual cost based on predictive traffic conditions. An algorithm used to solve the two models encompasses a cell-centered finite volume method for a hyperbolic system of conservation laws and a time-dependent Hamilton–Jacobi equation, a fast sweeping method for an Eikonal-type equation, and a self-adaptive method of successive averages for an arisen discrete fixed point problem. The two models and their algorithm are applied to investigate the spatio-temporal patterns of flux or density and path-choice behaviors of pedestrian flow marching in a facility scattered with an obstacle. Numerical results show that the two models are able to capture macroscopic features of pedestrian flow, traffic instability and other complex nonlinear phenomena in pedestrian traffic, such as the formation of stop-and-go waves and clogging at bottlenecks. Different path-choice strategies of pedestrians cause different spatial distributions of pedestrian density specially in the high-density regions (near the obstacle and exits).

Suggested Citation

  • Jiang, Yan-Qun & Zhang, Wei & Zhou, Shu-Guang, 2016. "Comparison study of the reactive and predictive dynamic models for pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 51-61.
    • Handle: RePEc:eee:phsmap:v:441:y:2016:i:c:p:51-61
    DOI: 10.1016/j.physa.2015.08.047
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    References listed on IDEAS

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    3. Guo, Fang & Li, Xingli & Kuang, Hua & Bai, Yang & Zhou, Huaguo, 2016. "An extended cost potential field cellular automata model considering behavior variation of pedestrian flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 630-640.
    4. He, Mengchen & Wang, Qiao & Chen, Juan & Xu, Shiwei & Ma, Jian, 2023. "Modeling pedestrian walking behavior in the flow field with moving walkways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
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    6. Aghamohammadi, Rafegh & Laval, Jorge A., 2020. "Dynamic traffic assignment using the macroscopic fundamental diagram: A Review of vehicular and pedestrian flow models," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 99-118.
    7. Li, Xingli & Guo, Fang & Kuang, Hua & Zhou, Huaguo, 2017. "Effect of psychological tension on pedestrian counter flow via an extended cost potential field cellular automaton model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 47-57.

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