The objective of this research is to develop a systematic methodology to understand overall demand, destination type choice, and route choice decisions in the aftermath of a hurricane. It will consider both transportation and social and other relevant factors such as actions of agencies dealing with emergency operations. Original data from past hurricanes will be used to estimate and calibrate the models, as well as new traffic data from Hurricane Irene in 2011. This research is focused on the New York/New Jersey metropolitan area, and will utilize available data sources in this area to conduct the proposed work.

The research team proposes a data-driven research approach that will “piggy-back” on newly available social media and other electronic data, in addition to survey data. Major steps of our research methodology are:

1. Review literature related to hurricane demand with a focus on the choices of individuals in terms of departure time, destination, and mode.

2. Identify the effects of previous evacuation experience and familiarity with the transportation system, in addition to other more commonly used factors such as socio-economic and demographic characteristics of evacuees.

3. Identify data sources, especially rare data such as traffic data from recent hurricanes, which can be used to capture the impact of traditional and nontraditional factors on complex evacuee behavior.

4. Acquire data and estimate “agent based models” that can capture individual level interactions and homogeneities in the presence of rare yet catastrophic event of hurricanes.

5. Compare the prediction of this new model with more traditional models of hurricane demand prediction.

This is the first model of its type found in hurricane evacuation modeling literature as such it is expected to have a high impact.