Modeling of pedestrian turning behavior and prediction of pedestrian density distribution

Cheng Sun, Shi Sun, Dagang Qu, Xun Zhu and Ying Liu

Physica A: Statistical Mechanics and its Applications, 2023, vol. 630, issue C

Abstract: As urban public spaces attract more pedestrians, it is essential to prevent excessive pedestrian aggregation. Use of a walking behavior model is crucial to predict the distribution of pedestrian density. In earlier studies, the modeling of walking behavior generally focused on straight walking or aimless strolling. In recent years, more complex models of walking behavior, including turning behavior, have increasingly gained attention. Because the majority of models are calibrated using data gathered from experimental settings, research on the prediction of turning behavior of multi-scale walking passages in life scenarios remains in its development.

Keywords: Turning behavior; Crowd dynamics; Pedestrian density prediction; Attention field; Unmanned aerial vehicle (UAV) (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:630:y:2023:i:c:s0378437123007720

DOI: 10.1016/j.physa.2023.129217

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