Modeling Risk Attitudes in Evacuation Departure Choices

被引:48
作者
Dixit, Vinayak V. [1 ]
Wilmot, Chester [2 ]
Wolshon, Brian [3 ]
机构
[1] Univ New S Wales, Sch Civil & Environm Engn, Sydney, NSW 2052, Australia
[2] Louisiana State Univ, Coll Engn, Baton Rouge, LA 70803 USA
[3] Louisiana State Univ, Gulf Coast Res Ctr Evacuat & Transportat Resilien, Baton Rouge, LA 70803 USA
关键词
HURRICANE; DECISION;
D O I
10.3141/2312-17
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The decision of whether and when to evacuate can be characterized as decision making under risk. Presently, most models assume linear utility functions through which it is impossible to disentangle factors that influence risk attitudes and other factors that affect decision making under risk. There is a need to disentangle and study factors that affect risk attitudes from factors that affect an evacuee's preparation time. The aim in doing so is to provide planners and practitioners with an ability to measure a person's risk attitude and develop appropriate strategies that could motivate people to evacuate. This study is expected to connect the theory of risk developed in economic theory with behavior under threat. The paper uses the Hurricane Andrew response data in conjunction with time-dependent data on the probability of a hurricane strike and the category of the hurricane data to develop a model for evacuation departure choice. A constant relative risk aversion specification is used to model risk attitudes. The process of an evacuation is abstracted as an individual being given a choice between two lotteries: either to stay or leave. The results show that the model is able to predict the total number of evacuees and the time varying evacuation rates with reasonable accuracy. Factors such as time of day, length of time spent in a region, and whether a mandatory evacuation order was issued affected risk attitudes. The presence of children affected the amount of time spent preparing if the family decided to stay.
引用
收藏
页码:159 / 163
页数:5
相关论文
共 21 条
[1]  
Alsnih R., 2005, 84 ANN M TRANSP RES
[2]  
Baker E.J., 1991, Int. J. Mass Emergencies Disasters, V9, P287
[3]  
Clemen R., 2004, MAKING HARD DECISION, V1 st
[4]   Understanding the impact of a recent hurricane on mobilization time during a subsequent hurricane [J].
Dixit, Vinayak V. ;
Pande, Anurag ;
Radwan, Essam ;
Abdel-Aty, Mohamed .
TRANSPORTATION RESEARCH RECORD, 2008, (2041) :49-57
[5]  
Fitzpatrick C., 1991, INT J MASS EMERGENCI, V9, P7
[6]   THE UTILITY ANALYSIS OF CHOICES INVOLVING RISK [J].
Friedman, Milton ;
Savage, L. J. .
JOURNAL OF POLITICAL ECONOMY, 1948, 56 (04) :279-304
[7]   Modeling the hurricane evacuation response curve [J].
Fu, Haoqiang ;
Wilmot, Chester G. ;
Zhang, Hong ;
Baker, Earl J. .
TRANSPORTATION RESEARCH RECORD, 2007, (2022) :94-102
[8]  
Fu HQ, 2006, TRANSPORT RES REC, P17
[9]   Sequential Logit dynamic travel demand model for hurricane evacuation [J].
Fu, HQ ;
Wilmot, CG .
TRANSPORTATION NETWORK MODELING 2004, 2004, (1882) :19-26
[10]  
Gudishala R., 2010, Journal of Transportation Safety Security, V2, P171, DOI DOI 10.1080/19439962.2010.488315