Statistical Analysis of the Number of Household Vehicles Used for Hurricane Ivan Evacuation

Abstract

The objectives of this paper are to identify the contributing factors to households’ choice of the number of vehicles used for evacuation and to develop predictive models of this choice that explicitly consider the constraint imposed by the number of vehicles owned by the household. This constraint is not accommodated by regular ordered response logit models. Data comes from a poststorm survey for Hurricane Ivan. Two models that are variants of the regular Poisson regression model are developed: a Poisson model with exposure and right-censored Poisson regression. The right-censored Poisson model is preferred due to its inherent capabilities, better fit to the data, and superior predictive power. The model and individual variable analyses indicate that households traveling longer distances or evacuating later are more likely to use fewer vehicles. Households with prior hurricane experience and pet owners are more likely to use a greater number of vehicles. Income and distance from the coast are insignificant in the multivariable models, although the individual effect of distance from the coast has a statistically significant bivariate relationship with vehicle usage choice based on the Pearson correlation measure. A method for using the right-censored Poisson model to produce the desired share of vehicle usage is also discussed for generating individual predictions for hurricane evacuation demand simulation.