Effects of Crowding Perception on Self-organized Pedestrian Flows Using Adaptive Agent-based Model
Qi Xu, Baohua Mao, Xujie Feng, Jia Feng

TL;DR
This paper introduces an adaptive agent-based pedestrian model that explicitly incorporates crowding perception and anisotropic visual information, successfully reproducing complex self-organized flow phenomena like lane formation and flow phase transitions.
Contribution
It extends existing pedestrian models by integrating perceptive mechanisms, providing a more realistic simulation of crowd dynamics and collective behavior.
Findings
Lane formation can be accurately simulated and influenced by view distance.
Heterogeneity in crowding perception affects flow stability and congestion.
Model aligns well with empirical data on pedestrian flow patterns.
Abstract
Pedestrian behavior has much more complicated characteristics in a dense crowd and thus attracts the widespread interest of scientists and engineers. However, even successful modeling approaches such as pedestrian models based on particle systems are still not fully considered the perceptive mechanism underlying collective pedestrian behavior. This paper extends a behavioral heuristics-based pedestrian model to an adaptive agent-based model, which explicitly considers the crowding effect of neighboring individuals and perception anisotropy on the representation of a pedestrians visual information. The adaptive agents with crowding perception are constructed to investigate complex, selforganized collective dynamics of pedestrian motion. The proposed model simulates selforganized pedestrian flows in good quantitative agreement with empirical data. The selforganized phenomena include lane…
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Taxonomy
TopicsEvacuation and Crowd Dynamics · Traffic control and management · Traffic and Road Safety
