Experimental study of pedestrian dynamics and crowd risk on ramps

IF 3.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2025-02-01 Epub Date: 2024-12-31 DOI:10.1016/j.physa.2024.130345
Zhijian Fu , Shengxian Yang , Lin Luo , Jian Li , Xiaobo Liu
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Abstract

This study investigates pedestrian dynamics and crowd risk on ramps, a topic not fully explored in previous research. Our experimental setup covers a boarder range of densities for both walking and running scenarios. Our main findings include: (1) Once pedestrian density exceeds 1.70ped/m2, flow rates continue to increase and remain consistently higher during ascending the ramp compared to descending, a trend not observed on level ground. This phenomenon can be explained by step behavior mechanisms, driven by the transition from two to three lanes, which help maintain consistent headway and step lengths. (2) The addition of walking lanes increases velocity curl (i.e., local spinning motion) on the ascending segment, especially in running scenarios. When combined with the high-density levels typically seen in ascending movement, these effects amplify crowd danger. Statistical analyses confirm crowd risks are more strongly correlate with movement directions (descending vs. ascending) than with movement speeds (walking vs. running).
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坡道上行人动态与人群风险的实验研究
本研究探讨坡道上的行人动态与人群风险,这是以往研究未充分探讨的课题。我们的实验设置涵盖了步行和跑步场景的密度范围。研究发现:(1)当行人密度超过1.70ped/m2时,上升坡道的流量会持续增加,并且在下降过程中保持较高的流量,而在平地上则没有这种趋势。这种现象可以用步进行为机制来解释,由两车道到三车道的过渡驱动,这有助于保持一致的车头时距和步长。(2)步行道的增加增加了上升段的速度旋度(即局部旋转运动),特别是在跑步场景中。当与上升运动中常见的高密度水平相结合时,这些效应会放大人群危险。统计分析证实,人群风险与运动方向(下行vs上行)的相关性比与运动速度(步行vs跑步)的相关性更强。
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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