School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China.
Department of Geography, University of Connecticut, Storrs, CT 06269, USA.
Int J Environ Res Public Health. 2019 Nov 20;16(23):4599. doi: 10.3390/ijerph16234599.
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.
当紧急事件发生时,及时、安全地疏散城市住宅区的居民对居民的安全至关重要。这与疏散办公室或学校不同,住宅区的紧急疏散必须考虑到预疏散时间。大约 40 年来,人们已经认识到估计疏散时间组成部分的重要性。然而,在以前的社区规模紧急疏散研究中,很少讨论预疏散时间。本文提出了一种新的方法来估计预疏散时间,使城市住宅区的疏散模拟更加真实。该方法将通过调查获得的居民预疏散行为数据进行集成,以探索预疏散时间的影响因素,并基于随机森林算法建立预测模型来预测预疏散时间。还进行了敏感性分析,以找出疏散模拟中的关键参数。可以比较不同场景下的疏散模拟结果,以识别潜在的疏散问题。在中国上海浦东新区罗山栖村社区进行了案例研究,以验证所提出方法的可行性。模拟结果表明,预疏散时间对模拟过程有重大影响,包括总疏散时间、拥堵时间和拥堵程度。这项研究可以帮助深入了解居民在紧急情况下的行为,提高城市社区的应急管理水平。