Tarun Rambha, Modeling Departure Time Decisions During Hurricanes
Dr. Tarun Rambha, Assistant Professor in the Department of Civil Engineering at the Indian Institute of Science (IISc) Bengaluru, presents a seminar on modeling departure time decisions during hurricanes using a dynamic discrete choice framework.
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. We 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 this research. This work was jointly carried out with Linda Nozick (Cornell University) and Rachel Davidson (University of Delaware).
Tarun Rambha is an assistant professor at the Indian Institute of Science (IISc) Bengaluru and an affiliate faculty at the Center for infrastructure, Transportation and Sustainable Urban Planning (CiSTUP). He received his PhD from the University of Texas at Austin where he worked on network equilibrium, congestion pricing, and adaptive routing in stochastic transit and traffic networks. He was also involved in the development of dynamic traffic assignment (DTA) models for Austin, TX which were used for Texas Department of Transportation (TxDOT)projects on bottleneck analysis and active traffic management strategies. Prior to joining IISc, he was also a post-doctoral researcher at Cornell University where he studied hospital evacuations and demand estimation during hurricanes.