A statistical analysis of the dynamics of household hurricane-evacuation decisions
A statistical analysis of the dynamics of household hurricane-evacuation decisions
复制标题
家庭飓风疏散决策动态的统计分析
DOI：
--
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
F. Mannering
中科院分区：
文献类型：
--
作者：
Md Tawfiq Sarwar;Panagiotis Ch. Anastasopoulos;S. Ukkusuri;Pamela M. Murray;F. Mannering
随着过去十年飓风次数的增加，有效和及时的疏散仍然是一个重大关切。住户撤离/留下的决定和离开时间的选择是复杂的现象。这项研究确定了影响决策过程的不同因素，如果一个家庭决定撤离，是什么影响了执行该决定的时间。在开发疏散/停留决策的随机参数二元logit模型时，考虑了几个因素，如社会经济特征、当局行动和地理位置，沿着飓风本身的动态性质。此外，以台风登陆为基准，严格分析了台风登陆前的疏散时间和时间的变化。联合模型中的影响因素包括飓风登陆的相对时间、沿海洪水的高度和飓风的接近速度;家庭的地理位置（州）;家中有一个以上的孩子，车辆所有权和教育水平;以及收到的疏散通知的类型（自愿或强制）。两个时间间隔从30至42小时和42至66小时登陆前导致随机参数，反映混合效应的可能性疏散/停留。由随机参数捕获的未观察到的异质性的可能来源包括受访者的风险感知或与受访者如何理解飓风威胁相关的其他未观察到的生理和心理因素。因此，该模型的目的是估计疏散决策和时间，同时使用飓风伊万的数据。
With the increasing number of hurricanes in the last decade, efficient and timely evacuation remains a significant concern. Households’ decisions to evacuate/stay and selection of departure time are complex phenomena. This study identifies the different factors that influence the decision making process, and if a household decides to evacuate, what affects the timing of the execution of that decision. While developing a random parameters binary logit model of the evacuate/stay decision, several factors, such as, socio-economic characteristics, actions by authority, and geographic location, have been considered along with the dynamic nature of the hurricane itself. In addition, taking the landfall as a base, how the evacuation timing varies, considering both the time-of-day and hours before landfall, has been analyzed rigorously. Influential factors in the joint model include the relative time until the hurricane’s landfall, height of the coastal flooding, and approaching speed of the hurricane; household’s geographic location (state); having more than one child in the household, vehicle ownership, and level of education; and type of evacuation notice received (voluntary or mandatory). Two time intervals from 30 to 42 h and 42 to 66 h before landfall resulted in random parameters, reflecting mixed effects on the likelihood to evacuate/stay. Possible sources of the unobserved heterogeneity captured by the random parameters include the respondents’ risk perception or other unobserved physiological and psychological factors associated with how respondents comprehend a hurricane threat. Thus, the model serves the purpose of estimating evacuation decision and timing simultaneously using the data of Hurricane Ivan.