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Road traffic congestion and public information: an experimental investigation

Anthony Ziegelmeyer, Frederic Koessler, Kene Boun My () and Laurent Denant-Boèmont ()

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Abstract: This paper reports laboratory experiments designed to study the impact of public information about past departure rates on congestion levels and travel costs. Our design is based on a discrete version of Arnott et al.'s (1990) bottleneck model. In all treatments, congestion occurs and the observed travel costs are quite similar to the predicted ones. Subjects' capacity to coordinate is not affected by the availability of public information on past departure rates, by the number of drivers 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 characterises individual behaviour.

Keywords: congestion; information; travel behaviour; learning; experimental economics (search for similar items in EconPapers)
Date: 2008
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00333755
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Published in Journal of Transport Economics and Policy, University of Bath, 2008, 42 (1), pp.43-82

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Journal Article: Road Traffic Congestion and Public Information: An Experimental Investigation (2008) Downloads
Working Paper: Road Traffic Congestion and Public Information: An Experimental Investigation (2007) Downloads
Working Paper: Road Traffic Congestion and Public Information: An Experimental Investigation (2006) Downloads
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