2012•Transportation Research Record Journal of the Transportation Research BoardRequires access

Comparison of Time-Dependent Sequential Logit and Nested Logit for Modeling Hurricane Evacuation Demand

Ravindra Gudishala, Chester G. Wilmot

Open publisher page 62 citations

Abstract

Models that predict hurricane evacuation demand can play a crucial role in developing and evaluating alternative evacuation policies and plans. However, to evaluate alternative policies effectively, evacuation demand models should be sensitive to time varying characteristics of a storm and the contextual conditions surrounding an evacuee. The time-dependent sequential logit is one such model, but it makes use of restrictive assumptions about the dynamic choices made by evacuees. A new model, a time-dependent nested logit model, relaxes those assumptions. It was formulated and derived in this study, and its performance was then compared with that of the time-dependent sequential logit model by applying both models to data from Hurricane Gustav. The results indicated that the time-dependent nested logit model has better predictive capability than the time-dependent sequential logit model.

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What this paper is about

Models that predict hurricane evacuation demand can play a crucial role in developing and evaluating alternative evacuation policies and plans. However, to evaluate alternative policies effectively, evacuation demand models should be sensitive to time varying characteristics of a storm and the contextual conditions surrounding an evacuee. The time-dependent sequential logit is one such model, but it makes use of restrictive assumptions about the dynamic choices made by evacuees. A new model, a time-dependent nested logit model, relaxes those assumptions. It was formulated and derived in this study, and its performance was then compared with that of the time-dependent sequential logit model by applying both models to data from Hurricane Gustav. The results indicated that the time-dependent nested logit model has better predictive capability than the time-dependent sequential logit model.

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Available abstract

Models that predict hurricane evacuation demand can play a crucial role in developing and evaluating alternative evacuation policies and plans. However, to evaluate alternative policies effectively, evacuation demand models should be sensitive to time varying characteristics of a storm and the contextual conditions surrounding an evacuee. The time-dependent sequential logit is one such model, but it makes use of restrictive assumptions about the dynamic choices made by evacuees. A new model, a time-dependent nested logit model, relaxes those assumptions. It was formulated and derived in this study, and its performance was then compared with that of the time-dependent sequential logit model by applying both models to data from Hurricane Gustav. The results indicated that the time-dependent nested logit model has better predictive capability than the time-dependent sequential logit model.

Key concepts: Logit, Nested logit, Logistic regression, Mixed logit, Econometrics, Computer science, Demand forecasting, Operations research

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