Pre-evacuation Time Estimation Based Emergency Evacuation Simulation in Urban Residential Communities

Jiayan Chen, Jia Yu, Jiahong Wen, Chuanrong Zhang, Zhan’e Yin, Jianping Wu and Shenjun Yao
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Jiayan Chen: School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China
Jia Yu: School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China
Jiahong Wen: School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China
Chuanrong Zhang: Department of Geography, University of Connecticut, Storrs, CT 06269, USA
Zhan’e Yin: School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China
Jianping Wu: Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
Shenjun Yao: Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China

IJERPH, 2019, vol. 16, issue 23, 1-25

Abstract: The timely and secure evacuation of an urban residential community is crucial to residents’ safety when emergency events happen. This is different to evacuation of office spaces or schools, emergency evacuation in residential communities must consider the pre-evacuation time. The importance of estimating evacuation time components has been recognized for approximately 40 years. However, pre-evacuation time is rarely discussed in previous community-scale emergency evacuation studies. This paper proposes a new method that estimates the pre-evacuation time, which makes the evacuation simulation in urban residential communities more realistic. This method integrates the residents’ pre-evacuation behavior data obtained by surveys to explore the influencing factors of pre-evacuation time and builds a predictive model to forecast pre-evacuation times based on the Random Forest algorithm. A sensitivity analysis is also conducted to find the critical parameters in evacuation simulations. The results of evacuation simulations in different scenarios can be compared to identify potential evacuation problems. A case study in Luoshanqicun Community, Pudong New District, Shanghai, China, was conducted to demonstrate the feasibility of the proposed method. The simulation results showed that the pre-evacuation times have significant impacts on the simulation procedure, including the total evacuation time, the congestion time and the congestion degree. This study can help to gain a deeper understanding of residents’ behaviors under emergencies and improve emergency managements of urban communities.

Keywords: pre-evacuation time; predictive model; evacuation simulation; residential community; Random Forest algorithm (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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