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Road Traffic Congestion and Public Information: An Experimental Investigation

  • Anthony Ziegelmeyer

    (Max Planck Institute of Economics, Strategic Interaction Group, Jena (Germany))

  • Frédéric Koessler

    (THEMA, University of Cergy-Pontoise (France))

  • Kene Boun My

    (BETA-Theme, CNRS, Louis Pasteur University, Strasbourg (France))

  • Laurent Denant-Boèmont

    ()

    (CREM, University of Rennes 1 (France))

This paper reports two laboratory studies designed to study the impact of public information about past departure rates on congestion levels and travel costs. Our experimental design is based on a discrete version of Arnott, de Palma, and Lindsey’s (1990) bottleneck model where subjects have to choose their departure time in order to reach a common destination. Experimental treatments in our first study differ in terms of the level of public information on past departure rates and the relative cost of delay. In all treatments, congestion occurs and the observed travel costs are quite similar to the predicted ones. In other words, subjects’ capacity to coordinate does not seem to be affected by the availability of public information on past departure rates or by the relative cost of delay. This seemingly absence of treatment effects is confirmed by our finding that a parameter-free reinforcement learning model best characterizes individual behavior. The number of experimental subjects taking the role of drivers is four times larger in our second study than in our first study. We observe that coordination failures in our congestion situation do not become more severe when the number of drivers increases.

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Paper provided by THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise in its series THEMA Working Papers with number 2007-05.

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Date of creation: 2007
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Handle: RePEc:ema:worpap:2007-05
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  1. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-79, June.
  2. Denant-Boèmont, L. & Petiot, R., 2003. "Information value and sequential decision-making in a transport setting: an experimental study," Transportation Research Part B: Methodological, Elsevier, vol. 37(4), pages 365-386, May.
  3. Drew Fudenberg & David K. Levine, 1998. "Learning in Games," Levine's Working Paper Archive 2222, David K. Levine.
  4. Moshe Ben-Akiva & Andre de Palma & Pavlos Kanaroglou, 1984. "Dynamic Model of Peak Period Traffic Congestion with Elastic Arrival Rates," Working Papers 588, Queen's University, Department of Economics.
  5. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-60, May.
  6. Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
  7. Selten, R. & Chmura, T. & Pitz, T. & Kube, S. & Schreckenberg, M., 2007. "Commuters route choice behaviour," Games and Economic Behavior, Elsevier, vol. 58(2), pages 394-406, February.
  8. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-81, September.
  9. David Levinson, 2003. "The Value of Advanced Traveler Information Systems for Route Choice," Working Papers 200307, University of Minnesota: Nexus Research Group.
  10. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
  11. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1990. "Economics of a bottleneck," Journal of Urban Economics, Elsevier, vol. 27(1), pages 111-130, January.
  12. Mahmassani, Hani S. & Jou, Rong-Chang, 2000. "Transferring insights into commuter behavior dynamics from laboratory experiments to field surveys," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(4), pages 243-260, May.
  13. Arentze, T.A. & Timmermans, H.J.P., 2005. "Information gain, novelty seeking and travel: a model of dynamic activity-travel behavior under conditions of uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 125-145.
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