A dual-layer pedestrian motion model for crowd movement simulation

Yawen Yu and Qun Chen

Physica A: Statistical Mechanics and its Applications, 2025, vol. 676, issue C

Abstract: In this paper, a dual-layer pedestrian motion (DLM) model is proposed for the analysis of crowd stampede risks, which utilizes spatial decoupling and multi-scale dynamic coupling mechanisms to investigate high-density crowd dynamics. The model comprises two main components: (a) individual dual-layer motion model modeling and (b) physical contact effects among the crowd. The DLM abstracts pedestrians as a “dual-foot-single-point” composite structure: the upper layer uses elliptical morphologies to describe torso dynamics and crowd collision risks, while the lower layer employs rectangular convex hulls to characterize gait support domains and ground contact dynamics. The model classifies pedestrian motion states into three states—steady locomotion (S1), dynamic imbalance (S2), and unsteady fallen (S3)—with phase transitions governed by contact conflict mechanics and biomechanical stability criteria. Multi-scenario simulations validate the DLM’s ability to reveal key mechanisms of high-density crowd movement: (1) Single-exit scenarios exhibit arch-shaped clustering and bottleneck effects, reducing evacuation efficiency, whereas dual-exit layouts disperse crowd pressure. (2) In high-density environments, external disturbances trigger individual instability, and fallen pedestrians induce chain reactions by obstructing force transmission pathways, forming localized “basin distributions” that exacerbate global instability. Quantitative evaluations indicate that high crowd inflow rates (>6 peds/s) and slopes (>8°) significantly increase stampede risks. The DLM establishes a multi-scale framework linking microscopic behaviors (collisions, tripping) to macroscopic phenomena (congestion, cascading instability), providing a tool for analyzing complex crowd dynamics.

Keywords: Crowd simulation; Dual-layer motion model; Trampling risk; High-density crowds; Agent-based modeling (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:676:y:2025:i:c:s0378437125005321

DOI: 10.1016/j.physa.2025.130880

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