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Anisotropic contractile particle model with avoidance for simulating pedestrian navigation in dilute and dense systems

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  • Martin, Rafael F.
  • Parisi, Daniel R.

Abstract

We introduce a novel rule-based pedestrian simulation model that extends an existing one by incorporating enhanced particle contact rules and evasive maneuver capabilities for collision avoidance. The model is calibrated using individual trajectory data from avoidance experiments. With the same set of parameters, the new model satisfactorily replicates experimental observations, including the avoidance behavior of individual agents, fundamental diagrams of unidirectional and bidirectional flows, as well as specific flow rates through bottlenecks.

Suggested Citation

  • Martin, Rafael F. & Parisi, Daniel R., 2024. "Anisotropic contractile particle model with avoidance for simulating pedestrian navigation in dilute and dense systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    • Handle: RePEc:eee:phsmap:v:633:y:2024:i:c:s037843712300969x
    DOI: 10.1016/j.physa.2023.129414
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    References listed on IDEAS

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    1. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    2. Parisi, Daniel R. & Gilman, Marcelo & Moldovan, Herman, 2009. "A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3600-3608.
    3. Steffen, B. & Seyfried, A., 2010. "Methods for measuring pedestrian density, flow, speed and direction with minimal scatter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1902-1910.
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