Literature DB >> 23126453

Risk of large-scale evacuation based on the effectiveness of rescue strategies under different crowd densities.

Jinghong Wang1, Siuming Lo, Qingsong Wang, Jinhua Sun, Honglin Mu.   

Abstract

Crowd density is a key factor that influences the moving characteristics of a large group of people during a large-scale evacuation. In this article, the macro features of crowd flow and subsequent rescue strategies were considered, and a series of characteristic crowd densities that affect large-scale people movement, as well as the maximum bearing density when the crowd is extremely congested, were analyzed. On the basis of characteristic crowd densities, the queuing theory was applied to simulate crowd movement. Accordingly, the moving characteristics of the crowd and the effects of typical crowd density-which is viewed as the representation of the crowd's arrival intensity in front of the evacuation passageways-on rescue strategies was studied. Furthermore, a "risk axle of crowd density" is proposed to determine the efficiency of rescue strategies in a large-scale evacuation, i.e., whether the rescue strategies are able to effectively maintain or improve evacuation efficiency. Finally, through some rational hypotheses for the value of evacuation risk, a three-dimensional distribution of the evacuation risk is established to illustrate the risk axle of crowd density. This work aims to make some macro, but original, analysis on the risk of large-scale crowd evacuation from the perspective of the efficiency of rescue strategies.
© 2012 Society for Risk Analysis.

Entities:  

Keywords:  Characteristic crowd density; evacuation risk; large-scale evacuation; queuing simulation; rescue strategies

Mesh:

Year:  2012        PMID: 23126453     DOI: 10.1111/j.1539-6924.2012.01923.x

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  1 in total

1.  Developing a database for pedestrians' earthquake emergency evacuation in indoor scenarios.

Authors:  Junxue Zhou; Sha Li; Gaozhong Nie; Xiwei Fan; Jinxian Tan; Huayue Li; Xiaoke Pang
Journal:  PLoS One       Date:  2018-06-20       Impact factor: 3.240

  1 in total

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