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Congestion in a city with a central bottleneck

  • Fosgerau, Mogens
  • de Palma, André

We consider dynamic congestion in an urban setting where trip origins are spatially distributed. All travelers must pass through a downtown bottleneck in order to reach their destination in the CBD. Each traveler chooses departure time to maximize general concave scheduling utility. We find that, at equilibrium, travelers sort according to their distance to the destination; the queue is always unimodal regardless of the spatial distribution of trip origins. We construct a welfare maximizing tolling regime, which eliminates congestion. All travelers located beyond a critical distance from the CBD gain from tolling, even when toll revenues are not redistributed, while nearby travelers lose. We discuss our results in the context of acceptability of tolling policies.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 42270.

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Date of creation: 2012
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Handle: RePEc:pra:mprapa:42270
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  1. Arnott, Richard & DePalma, Elijah, 2011. "The corridor problem: Preliminary results on the no-toll equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 743-768, June.
  2. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-60, May.
  3. van den Berg, Vincent & Verhoef, Erik T., 2011. "Winning or losing from dynamic bottleneck congestion pricing?: The distributional effects of road pricing with heterogeneity in values of time and schedule delay," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 983-992, August.
  4. 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.
  5. de Palma, André & Fosgerau, Mogens, 2013. "Random queues and risk averse users," European Journal of Operational Research, Elsevier, vol. 230(2), pages 313-320.
  6. Geroliminis, Nikolas & Daganzo, Carlos F., 2008. "Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 759-770, November.
  7. Daganzo, Carlos F., 2007. "Urban gridlock: Macroscopic modeling and mitigation approaches," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 49-62, January.
  8. Richard Arnott, 1990. "A Temporal and Spatial Equilibrium Analysis of Commuter Parking," Discussion Papers 884, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  9. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1999. "Information and time-of-usage decisions in the bottleneck model with stochastic capacity and demand," European Economic Review, Elsevier, vol. 43(3), pages 525-548, March.
  10. Mun, Se-il, 1999. "Peak-Load Pricing of a Bottleneck with Traffic Jam," Journal of Urban Economics, Elsevier, vol. 46(3), pages 323-349, November.
  11. Nikolas Geroliminis & David Levinson, 2008. "Cordon pricing consistent with the physics of overcrowding," Working Papers 000038, University of Minnesota: Nexus Research Group.
  12. Richard Arnott & Andre de Palma & Robin Lindsey, 1993. "The Welfare Effects Of Congestion Tolls With Heterogeneous Commuters," Boston College Working Papers in Economics 231, Boston College Department of Economics.
  13. Fosgerau, Mogens & Engelson, Leonid, 2010. "The value of travel time variance," MPRA Paper 42272, University Library of Munich, Germany.
  14. Mogens Fosgerau & Kenneth Small, 2013. "Endogenous Scheduling Preferences and Congestion," Working Papers 131403, University of California-Irvine, Department of Economics, revised May 2014.
  15. Tseng, Yin-Yen & Verhoef, Erik T., 2008. "Value of time by time of day: A stated-preference study," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 607-618, August.
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