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

Rafael F. Martin and Daniel R. Parisi

Physica A: Statistical Mechanics and its Applications, 2024, vol. 633, issue C

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.

Keywords: Pedestrian dynamics; Collision avoidance; Navigation; Steering; Off-lattice cellular automaton (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:633:y:2024:i:c:s037843712300969x

DOI: 10.1016/j.physa.2023.129414

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