Velocity-based model for pedestrian dynamics considering direction preferences

Jun Zhang, Haoran Cui, Mohcine Chraibi, Hang Yu and Weiguo Song

Physica A: Statistical Mechanics and its Applications, 2023, vol. 613, issue C

Abstract: To reflect the direction preferences of the individual moving process, a velocity-based model is developed based on the Collision Free Speed (CFS) model. Our model used the local optimal direction selection algorithm based on a greedy algorithm that considers individual direction preferences for greater headway distance and dynamic willingness to turn during movement. The headway distance is calculated based on the principle of conflict avoidance, while gaussian distribution is used to fit individual willingness to turn and the optimal velocity (OV) function is used to determine the magnitude of the velocity. The concept of competition coefficient is proposed to quantitatively describe individual variability of direction preferences. The lane formation phenomena are reproduced in the bidirectional flow. In high-competition bottleneck, flow-width relation and pedestrian concentration fit better in the experimental data of our new model compared with the original CFS model. Furthermore, we analyze the competition coefficient and reproduce the typical phenomenon of fast-is-slow.

Keywords: Pedestrian model; Evacuation simulation; Direction preferences; Individual differences (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:613:y:2023:i:c:s0378437122010020

DOI: 10.1016/j.physa.2022.128444

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