01698090

Component

Predicting evacuation-related choices of households during a hurricane is of paramount importance to any emergency management system. Central to this problem is the identification of socio-demographic factors and hurricane characteristics that influence an individual's decision to stay or evacuate. However, decision makers in such conditions do not make a single choice but constantly evaluate current and anticipated conditions before opting to stay or evacuate. The authors model this behavior using a finite-horizon dynamic discrete choice framework in which households may choose to evacuate or wait in time periods prior to a hurricane's landfall. In each period, an individual's utility depends not only on his/her current choices and the present values of the influential variables, but also involves discounted expected utilities from future choices should one decide to postpone their decision to evacuate. Assuming generalized extreme value (GEV) errors, a nested algorithm involving a dynamic program and a maximum likelihood method is used to estimate model parameters. Panel data on households affected by Hurricane Gustav (collected by the Public Policy Research Lab, Louisiana State University) was fused together with the National Hurricane Center's forecasts on the trajectory and intensity for the case study in the paper.

This paper was sponsored by TRB committee ABR30 Standing Committee on Emergency Evacuations.

19-06045

English

5p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

References; Tables

Algorithms; Behavior; Case studies; Choice models; Decision making; Evacuation; Households; Hurricanes

Hurricane Gustav, 2008

Planning and Forecasting; Security and Emergencies; Transportation (General)

Transportation Research Board Annual Meeting 2019 Paper #19-06045

TRIS, TRB, ATRI

Dec 7 2018 9:46AM