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Road Traffic Congestion and Public Information: An Experimental Investigation

Author

Listed:
  • 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))

Abstract

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.

Suggested Citation

  • Anthony Ziegelmeyer & Frédéric Koessler & Kene Boun My & Laurent Denant-Boèmont, 2007. "Road Traffic Congestion and Public Information: An Experimental Investigation," Thema Working Papers 2007-05, THEMA (Théorie Economique, Modélisation et Applications), CY Cergy-Paris University, ESSEC and CNRS.
  • Handle: RePEc:ema:worpap:2007-05
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    References listed on IDEAS

    as
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    Keywords

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    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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