Improved Crowd Dynamics Analysis Considering Physical Contact Force and Panic Emotional Propagation

恐慌 动力学(音乐) 心理学 焦虑 精神科 教育学
作者
Rongyong Zhao,Bingyu Wei,Chuanfeng Han,Ping Jia,Wenjie Zhu,Cuiling Li,Yunlong Ma
出处
期刊:IEEE Transactions on Intelligent Transportation Systems [Institute of Electrical and Electronics Engineers]
卷期号:26 (2): 1840-1851 被引量:2
标识
DOI:10.1109/tits.2024.3512501
摘要

Panic behaviors in a pedestrian flow often lead to a state of chaos or disorder among the pedestrian crowd, resulting in a crowd accident with high possibility. To investigate the panic pedestrian dynamics and further prevent serious crowd accidents, simulation based on dynamics modeling and accident video data is a popular solution to date. Thereby, it is challenging but significant to improve the crowd dynamics model more consistent with the ground truth of real pedestrian movement scenarios, with consideration of both physical contact force and panic emotional propagation in a crowd. Therefore, this study proposed an extended social force model (ESFM) by applying the physical contact-force estimation during pedestrian collision based on non-smooth contact dynamics. Subsequently, the ESFM was integrated with an improved panic propagation model (IPPM) considering obstacle and promotion factors. Finally, taking the crowd panic accident happened in Nepal in 2015 as an experiment case, the simulation of panic crowd dynamics was conducted within Anylogic software. Four cases of SFM, ESFM, SFM+IPPM, and ESFM+IPPM were compared quantitatively and graphically. The experimental results showed that the pedestrian distribution obtained from the proposed ESFM+IPPM was the closest to the ground truth during the panic response period, with 28.8% lower of Hausdorff distance than the original SFM, and 21.6% lower the well-known BHSFM, respectively. This approach can help improve the panic crowd modeling and pedestrian distribution prediction in real scenarios.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
wenzi完成签到,获得积分10
1秒前
LpYzD3发布了新的文献求助10
2秒前
小学僧发布了新的文献求助10
3秒前
3秒前
4秒前
JamesPei的应助被羞涩的烨华采纳,获得10
4秒前
小夏完成签到,获得积分10
4秒前
陈崟发布了新的文献求助10
5秒前
田様的应助被gura采纳,获得10
5秒前
kkkay发布了新的文献求助10
6秒前
Owen的应助被wwrjj采纳,获得10
6秒前
7秒前
9秒前
9秒前
9秒前
kunzai发布了新的文献求助10
10秒前
川上富江完成签到 ,获得积分10
11秒前
BY完成签到,获得积分10
11秒前
周游发布了新的文献求助10
11秒前
wangwangwang完成签到,获得积分10
12秒前
科研通AI6.2的应助被子轩采纳,获得10
12秒前
lcychem发布了新的文献求助10
12秒前
13秒前
互化化发布了新的文献求助10
13秒前
13秒前
13秒前
14秒前
鲤角兽完成签到,获得积分10
15秒前
perfumei完成签到,获得积分10
15秒前
辣爆虾尾发布了新的文献求助10
18秒前
gura发布了新的文献求助10
19秒前
wwrjj发布了新的文献求助10
20秒前
Jerry发布了新的文献求助30
20秒前
安然完成签到 ,获得积分10
21秒前
lyy发布了新的文献求助10
21秒前
秋风的应助被kkkay采纳,获得10
21秒前
三冬四夏完成签到 ,获得积分10
21秒前
123发布了新的文献求助10
21秒前
22秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Composite Materials Handbook Volume 1 - Revision H 1500
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
Decentring Leadership 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7808096
求助须知:如何正确求助?哪些是违规求助? 9340548
关于积分的说明 20502608
捐赠科研通 7400245
什么是DOI,文献DOI怎么找? 3328699
关于科研通互助平台的介绍 2475421
邀请新用户注册赠送积分活动 2346929