Travel Time Reliability during Evacuation: Impact of Heterogeneous Driving Behavior
Abstract
Earlier studies have shown that driving behavior differs strongly in emergency conditions compared with behavior in normal traffic conditions. In this paper, these findings are followed up with an investigation of how these differences in driving behavior affect travel time reliability. In particular, the focus is on the effect of relatively strong heterogeneity in driving behavior. The microscopic simulation framework S-PARAMICS is adapted accordingly and applied to the emergency evacuation network of the Dutch city of Almere. This experimental setup allows a structured and in-depth analysis of the relationship between a number of driving behavior parameters and the emergent travel time reliability. The main findings from this study are thus insightful and directly applicable to evacuation planning and management studies. For instance, it is found that although a reduction in drivers’ mean time headway and minimum gap acceptance typically improves the overall evacuation time, travel times are simultaneously less reliable. Also, the reliability of travel times decreases over time and results in much less reliable travel times for those travelers who depart later. And finally, in general, heterogeneity in driving behavior strongly reduces travel time reliability.
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References
1. Plowman T. Danger! Hurricane Coming. Planning, Vol. 67, No. 12, 2001, pp. 16–21.
2. Barrett B., Ran B., and Pillai R. Developing a Dynamic Traffic Management Modeling Framework for Hurricane Evacuation. In Transportation Research Record: Journal of the Transportation Research Board, No. 1733, TRB, National Research Council, Washington, D.C., 2000, pp. 115–121.
3. Dash N., and Gladwin H. Evacuation Decision Making and Behavioral Responses: Individual and Household. Natural Hazards Review, Vol. 8, No. 3, 2007, pp. 69–77.
4. Lindell M.K., and Prater C.S. Critical Behavioral Assumptions in Evacuation Time Estimate Analysis for Private Vehicles: Examples from Hurricane Research and Planning. Journal of Urban Planning and Development, Vol. 133, No. 1, 2007, pp. 18–29.
5. Pel A. J. Transportation Modelling for Regional Evacuations. Doctoral dissertation. Delft University of Technology, Delft, Netherlands, 2011.
6. Pel A.J., Bliemer M. C. J., and Hoogendoorn S. P. A Review on Travel Behaviour Modelling in Dynamic Traffic Simulation Models for Evacuations. Transportation, Vol. 39, No. 1, 2011, pp. 97–123.
7. Wolshon B. Empirical Characterization of Mass Evacuation Traffic Flow. In Transportation Research Record: Journal of the Transportation Research Board, No. 2041, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 38–48.
8. Pel A.J., Hoogendoorn S. P., and Bliemer M. C. J. Impact of Variations in Travel Demand and Network Supply Factors for Evacuation Studies. In Transportation Research Record: Journal of the Transportation Research Board, No. 2196, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 45–55.
9. Tu H., Tamminga G., Drolenga H., De Wit J., and Van der Berg W. Evacuation Plan of the City of Almere: Simulating the Impact of Driving Behaviors on Evacuation Clearance Time. 1st International Conference on Evacuation Modeling and Management, Elsevier Procedia Engineering, Vol. 3 (Hoogendoorn S. P., Pel A. J., Taylor M. A. P., and Mahmassani H., eds.), 2010, pp. 67–75.
10. Tu H., Tamminga G., Pel A. J., and Drolenga H. Sensitivity Analysis on Heterogeneity of Driving Behavior for Evacuation Studies and Its Impacts on Traffic Safety. Proc., 13th IEEE Intelligent Transportation Systems Conference, Madeira, Portugal, 2010.
11. Cova T.J., and Johnson J.P. Microsimulation of Neighborhood Evacuations in the Urban–Wildland Interface. Environment and Planning A, Vol. 34, 2002, pp. 2211–2229.
12. Chiu Y.C., and Mirchandani P.B. Online Behavior—Robust Feedback Information Routing Strategy for Mass Evacuation. IEEE Transactions on Intelligent Transportation Systems, Vol. 9, No. 2, 2008, pp. 264–274.
13. Dow K., and Cutter S.L. Emerging Hurricane Evacuation Issues: Hurricane Floyd and South Carolina. Natural Hazards Review, Vol. 3, No. 1, 2002, pp. 12–18.
14. Lindell M.K., and Prater C.S. Evacuation from Hurricane Katrina: Jefferson and St. Charles Parishes. Proc., National Hurricane Conference, Orlando, Fla., 2006.
15. Li H., Bliemer M. C. J., and Bovy P. H. L. Modeling Departure Time Choice Under Stochastic Networks Involved in Network Design. In Transportation Research Record: Journal of the Transportation Research Board, No. 2091, Transportation Research Board of the National Academies, Washington, D.C., 2009, pp. 61–69.
16. Tamminga G., Tu H., Daamen W., and Hoogendoorn S. Influence of Departure Time Spans and Corresponding Network Performance on Evacuation Time. In Transportation Research Record: Journal of the Transportation Research Board, No. 2234, Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 89–96.
17. Fosgereau M., and Karlstrom A. The Value of Reliability. Transportation Research Part B: Methodological, Vol. 44, No. 1, 2010, pp. 38–49.
18. Ni D. Challenges and Strategies of Transportation Modeling and Simulation under Extreme Conditions. International Journal of Emergency Management, Vol. 3, No. 4, 2006, pp. 298–312.
19. Hamdar S.H., and Mahmassani H.S. From Existing Accident-Free Car-Following Models to Colliding Vehicles: Exploration and Assessment. In Transportation Research Record: Journal of the Transportation Research Board, No. 2088, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 45–56.
20. Hoogendoorn R. G. State-of-the-Art Driving Theory and Modeling in Case of Adverse Conditions. Internal report. Delft University of Technology, Netherlands, 2010.
21. Knoop V.L., Van Zuylen H. J., and Hoogendoorn S. P. Microscopic Traffic Behaviour near Accidents. Proc., 18th International Symposium of Transportation and Traffic Theory (Lam W. H. K., Wong S. C., and Lo H. K., eds.), Hong Kong, China. Springer, New York, 2009, pp. 75–97.
22. Hoogendoorn R.G., Hoogendoorn S. P., Brookhuis K., and Daamen W. Mental Workload, Longitudinal Driving Behavior and Adequacy of Car-Following Models in Case of Incidents in Other Driving Lane. In Transportation Research Record: Journal of the Transportation Research Board, No. 2188, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 64–73.
23. Goodwin L. Weather Impacts on Arterial Traffic Flow. Technical report. Mitretek Systems, Inc., Falls Church, Va., 2004.
24. Van Lint J. W. C., Van Zuylen H. J., and Tu H. Travel Time Un reliability on Freeways: Why Measures Based on Variance Tell Only Half the Story. Transportation Research Part A: Policy and Practice, Vol. 42, 2008, pp. 258–277.
25. Tu H. Monitoring Travel Time Reliability on Freeways. Doctoral dissertation. Delft University of Technology, Netherlands, 2008.
26. Polus A. A Study of Travel Time and Reliability on Arterial Routes. Transportation, Vol. 8, 1979, pp. 141–151.
27. Herman R. and Lam T. Trip Time Characteristics of Journeys to and from Work. Proc., 5th International Symposium of Transportation and Traffic Theory (Buckley D. J., ed.), Sydney, Australia. Springer, New York, 1974, pp. 57–85.
28. Richardson A.J., and Taylor M. A. P. Travel Time Variability on Commuter Journeys. High Speed Ground Transportation Journal, Vol. 6, 1978, pp. 77–79.
29. Al-Deek H., and Emam E.B. New Methodology for Estimating Reliability in Transportation Networks with Degraded Link Capacities. Journal of Intelligent Transportation Systems, Vol. 10, 2006, pp. 117–129.
30. Pu W. Analytic Relationships between Travel Time Reliability Measures. Presented at 89th Annual Meeting of the Transportation Research Board, Washington, D.C., 2010.
31. Druitt S. An Introduction to Microsimulation. Traffic Engineering and Control, Vol. 39, No. 9, 1998, pp. 480–483.
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Article first published online: January 1, 2012
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