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Trip-timing decisions with traffic incidents

  • Fosgerau, Mogens
  • Lindsey, Robin

This paper analyzes traffic bottleneck congestion when drivers randomly cause incidents that temporarily block the bottleneck. Drivers have general scheduling preferences for time spent at home and at work. They independently choose morning departure times from home to maximize expected utility without knowing whether an incident has occurred. The resulting departure time pattern may be compressed or dispersed according to whether or not the bottleneck is fully utilized throughout the departure period on days without incidents. For both the user equilibrium (UE) and the social optimum (SO) the departure pattern changes from compressed to dispersed when the probability of an incident becomes sufficiently high. The SO can be decentralized with a time-varying toll, but drivers are likely to be strictly worse off than in the UE unless they benefit from the toll revenues in some way. A numerical example is presented for illustration. Finally, the model is extended to encompass minor incidents in which the bottleneck retains some capacity during an incident.

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File URL: https://mpra.ub.uni-muenchen.de/48708/1/MPRA_paper_48708.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 48708.

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Date of creation: 2013
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Handle: RePEc:pra:mprapa:48708
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  1. Mogens Fosgerau & André De Palma, 2012. "Congestion in a city with a central bottleneck," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00783803, HAL.
  2. Fosgerau, Mogens & Engelson, Leonid, 2011. "The value of travel time variance," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 1-8, January.
  3. Hall, Randolph W., 2002. "Incident dispatching, clearance and delay," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(1), pages 1-16, January.
  4. Paul Koster & Piet Rietveld, 2011. "Optimising Incident Management on the Road," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 45(1), pages 63-81, January.
  5. Noland, Robert B., 1997. "Commuter Responses to Travel Time Uncertainty under Congested Conditions: Expected Costs and the Provision of Information," Journal of Urban Economics, Elsevier, vol. 41(3), pages 377-406, May.
  6. Yin-yen Tseng & Erik Verhoef, 2007. "Value of Time by Time of Day: A Stated-Preference Study," Tinbergen Institute Discussion Papers 07-061/3, Tinbergen Institute, revised 08 Nov 2007.
  7. Léonard,Daniel & Long,Ngo van, 1992. "Optimal Control Theory and Static Optimization in Economics," Cambridge Books, Cambridge University Press, number 9780521337465.
  8. Robert B. Noland & Mohammed A. Quddus, 2003. "Congestion and Safety: A Spatial Analysis of London," ERSA conference papers ersa03p66, European Regional Science Association.
  9. Zhang, Xiaoning & Huang, Hai-Jun & Zhang, H.M., 2008. "Integrated daily commuting patterns and optimal road tolls and parking fees in a linear city," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 38-56, January.
  10. Andrew Dickerson & John Peirson & Roger Vickerman, 1998. "Road Accidents and Traffic Flows: An Econometric Investigation," Studies in Economics 9809, School of Economics, University of Kent.
  11. Schrage, Andrea, 2006. "Traffic Congestion and Accidents," University of Regensburg Working Papers in Business, Economics and Management Information Systems 419, University of Regensburg, Department of Economics.
  12. Fosgerau, Mogens, 2008. "On the relation between the mean and variance of delay in dynamic queues with random capacity and demand," MPRA Paper 11994, University Library of Munich, Germany.
  13. Richard Arnott & Andre de Palma & Robin Lindsey, 1985. "Economics of a Bottleneck," Working Papers 636, Queen's University, Department of Economics.
  14. Hall, Randolph W., 1983. "Travel outcome and performance: The effect of uncertainty on accessibility," Transportation Research Part B: Methodological, Elsevier, vol. 17(4), pages 275-290, August.
  15. Henderson, J. V., 1974. "Road congestion : A reconsideration of pricing theory," Journal of Urban Economics, Elsevier, vol. 1(3), pages 346-365, July.
  16. De Palma, André & Fosgerau, Mogens, 2010. "Random queues and risk averse users," MPRA Paper 24215, University Library of Munich, Germany.
  17. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-60, May.
  18. Börjesson, Maria & Eliasson, Jonas & Franklin, Joel, 2012. "Valuations of travel time variability in scheduling versus mean-variance models," Working papers in Transport Economics 2012:2, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
  19. Nam, Doohee & Mannering, Fred, 2000. "An exploratory hazard-based analysis of highway incident duration," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(2), pages 85-102, February.
  20. André De Palma & Robin Lindsey & Nathalie Picard, 2008. "Risk aversion, the value of information and traffic equilibrium," Working Papers hal-00349492, HAL.
  21. R. Arnott & A. de Palma & R. Lindsey, 1997. "Information and time-of-usage decisions in the bottleneck model with stochastic capacity and demand," THEMA Working Papers 97-13, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  22. Jenelius, Erik & Mattsson, Lars-Göran & Levinson, David, 2011. "Traveler delay costs and value of time with trip chains, flexible activity scheduling and information," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 789-807, June.
  23. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1993. "A Structural Model of Peak-Period Congestion: A Traffic Bottleneck with Elastic Demand," American Economic Review, American Economic Association, vol. 83(1), pages 161-79, March.
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