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First published online January 1, 2012

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

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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References

1. Fu H., and Wilmot C.G. Sequential Logit Dynamic Travel Demand Model for Hurricane Evacuation. In Transportation Research Record: Journal of the Transportation Research Board, No 1882, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 19–26.
2. Wilmot C., and Mei B. Comparison of Alternative Trip Generation Models for Hurricane Evacuation. Natural Hazards Review, Vol. 5, No. 4, 2004, pp. 170–178.
3. Hasan S., Ukkusuri S., Gladwin H., and Tuite P. Behavioral Model to Understand Household-Level Hurricane Evacuation Decision Making. ASCE Journal of Transportation Engineering, Vol. 137, 2011, pp. 341–348.
4. Wolshon B., Urbina E., Wilmot C., and Levitan M. Review of Policies and Practices for Hurricane Evacuation. I: Transportation Planning Preparedness, and Response. Natural Hazards Review, Vol. 6, Aug. 2005, pp. 143–161.
5. Gudishala R. Development of a Time-Dependent, Audio-Visual, Stated Choice Method of Data Collection for Hurricane Evacuation Behavior. PhD dissertation. Louisiana State University, Baton Rouge, 2011.
6. Liu Y., Lai X., and Chang G. Two-Level Integrated Optimization System for Planning of Emergency Evacuation. ASCE Journal of Transportation Engineering, Vol. 32, No. 10, 2006, pp. 800–807.
7. Yuan F., Han L. D., Chin S., and Hwang H. Proposed Framework for Simultaneous Optimization of Evacuation Traffic Destination and Route Assignment. In Transportation Research Record: Journal of the Transportation Research Board, No. 1964, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 50–58.
8. Cova T.J., and Johnson J.P. Microsimulation of Neighborhood Evacuations in the Urban–Wildlife Interface. Environment and Planning A, Vol. 34, No. 12, 2002, pp. 2211–2229.
9. Jonkman S. N. Loss of Life Estimation in Flood Risk Assessment: Theory and Applications. Dissertation. Delft University of Technology, Netherlands, 2007.
10. Lindell M. K. EMBLEM2: An Empirically Based Large Scale Evacuation Time Estimate Model. Transportation Research Part A, Vol. 42, 2008, pp. 140–154.
11. Kalafatas G., and Peeta S. Planning for Evacuation: Insights from an Efficient Network Design Model. Journal of Infrastructure Systems, Vol. 15, No. 1, 2009, pp. 21–30.
12. Xie C., Lin D. Y., and Waller S. T. A Dynamic Evacuation Network Optimization Problem with Lane Reversal and Crossing Elimination Strategies. Transportation Research Part E, Vol. 46, 2010, pp. 295–316.
13. Post, Buckley, Schuh, and Jernigan, Inc. Evacuation Travel Demand Forecasting System. Technical report. PBS&J, Inc., Tallahassee, Fla., 2000.
14. Post, Buckley, Schuh, and Jernigan, Inc. Southwest Louisiana Hurricane Evacuation Study: Transportation Model Support Document. PBS&J, Inc., Tallahassee, Fla., 2000.
15. Fu H., and Wilmot C.G. Static Versus Dynamic and Aggregate Versus Disaggregate: A Comparison Between Practice and Research in Hurricane Evacuation Travel Demand Modeling. Presented at 86th Annual Meeting of the Transportation Research Board, Washington, D.C., 2007.
16. Fu H., Wilmot C. G., and Zhang H. Modeling the Hurricane Evacuation Response Curve. In Transportation Research Record: Journal of the Transportation Research Board, No. 2022, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 94–102.
17. Ben-Akiva M., and Lerman S. Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press, Cambridge, Mass., 1985.
18. Train K. Discrete Choice Methods with Simulation. Cambridge University Press, Cambridge, United Kingdom, 2003.
19. Rust J. Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurchner. Econometrica, Vol. 55, 1987, pp. 993–1033.
20. Gudishala R., and Wilmot G. Development of a Time-Dependent, Audio-Visual, Stated Choice Method of Data Collection for Hurricane Evacuation Behavior. Journal of Transportation Safety and Security, Vol. 2, 2010, pp. 171–183.
21. Baker E. Hurricane Evacuation Behavior. International Journal of Mass Emergencies and Disasters, Vol. 9, No. 2, 1991, pp. 287–310.

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Article first published online: January 1, 2012
Issue published: January 2012

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© 2012 National Academy of Sciences.
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Authors

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Ravindra Gudishala
Department of Civil and Environmental Engineering, Louisiana State University, 3418 Patrick F. Taylor Hall, Baton Rouge, LA 70803.
Chester Wilmot
Department of Civil and Environmental Engineering, Louisiana State University, 3418 Patrick F. Taylor Hall, Baton Rouge, LA 70803.

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