Exploring crowd persistent dynamism from pedestrian crossing perspective: An empirical study

被引:0
|
作者
Wang, Jinghui [1 ]
Lv, Wei [1 ]
Jiang, Huihua [1 ]
Fang, Zhiming [2 ]
Ma, Jian [3 ]
机构
[1] Wuhan Univ Technol, Sch Safety Sci & Emergency Management, Wuhan, Peoples R China
[2] Univ Shanghai Sci & Technol, Business Sch, Shanghai, Peoples R China
[3] Southwest Jiaotong Univ, Sch Transportat & Logist, Chengdu, Peoples R China
基金
中国国家自然科学基金;
关键词
Experiment; Crowd dynamism; Detour behavior; Cross -channel formation; Fundamental diagram; BEHAVIOR; DENSITY; MODEL; FLOW; CALIBRATION; CONGESTION; MOVEMENT; VELOCITY;
D O I
10.1016/j.trc.2023.104400
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Crowd studies have gained increasing relevance due to the recurring incidents of crowd crush accidents. In addressing the issue of the crowd's persistent dynamism, this paper explored the macroscopic and microscopic features of pedestrians crossing in static and dynamic contexts, employing a series of systematic experiments. Firstly, empirical evidence has confirmed the existence of crowd's persistent dynamism. Subsequently, the research delves into two aspects, qualitative and quantitative, to address the following questions: (1) Cross pedestrians tend to avoid high-density areas when crossing static crowds and particularly evade pedestrians in front to avoid deceleration, thus inducing the formation of cross-channels, a self-organization phenomenon. (2) In dynamic crowds, when pedestrian suffers spatial constrained, two patterns emerge: decelerate or detour. Research results indicate the differences in pedestrian crossing behaviors between static and dynamic crowds, such as the formation of crossing channels, backward detours, and spiral turning. However, the strategy of pedestrian crossing remains consistent: utilizing detours to overcome spatial constraints. Finally, the empirical results of this study address the final question: pedestrians detouring causes crowds' persistent collective dynamism. These findings contribute to an enhanced understanding of pedestrian dynamics in extreme conditions and provide empirical support for research on individual movement patterns and crowd behavior prediction.
引用
收藏
页数:27
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