Road Traffic Congestion and Public Information: An Experimental Investigation
AbstractThis 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise in its series THEMA Working Papers with number 2007-05.
Date of creation: 2007
Date of revision:
Contact details of provider:
Postal: 33, boulevard du port - 95011 Cergy-Pontoise Cedex
Phone: 33 1 34 25 60 63
Fax: 33 1 34 25 62 33
Web page: http://thema.u-cergy.fr
More information through EDIRC
Travel behavior; Congestion; Information in intelligent transportation systems; Laboratory experiments.;
Other versions of this item:
- Anthony Ziegelmeyer & Frédéric Koessler & Kene Boun My & Laurent Denant-Boèmont, 2008. "Road Traffic Congestion and Public Information: An Experimental Investigation," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 42(1), pages 43-82, January.
- Kene Boun My & Laurent Denant-Boèmont & Frédéric Koessler & Marc Willinger & Anthony Ziegelmeyer, 2006. "Road Traffic Congestion and Public Information: An Experimental Investigation," Papers on Strategic Interaction 2006-20, Max Planck Institute of Economics, Strategic Interaction Group.
- 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, and Information
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-03-17 (All new papers)
- NEP-GEO-2007-03-17 (Economic Geography)
- NEP-URE-2007-03-17 (Urban & Real Estate Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-60, May.
- Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-79, June.
- 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.
- Drew Fudenberg & David K. Levine, 1998.
"Learning in Games,"
Levine's Working Paper Archive
2222, David K. Levine.
- 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.
- 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.
- 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.
- Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1990.
"Economics of a bottleneck,"
Journal of Urban Economics,
Elsevier, vol. 27(1), pages 111-130, January.
- Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
- 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.
- David Levinson, 2003. "The Value of Advanced Traveler Information Systems for Route Choice," Working Papers 200307, University of Minnesota: Nexus Research Group.
- 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.
- Caspar G. Chorus & Benedict G. C. Dellaert, 2012.
"Travel Choice Inertia: The Joint Role of Risk Aversion and Learning,"
Journal of Transport Economics and Policy,
London School of Economics and University of Bath, vol. 46(1), pages 139-155, January.
- Chorus, C.G. & Dellaert, B.G.C., 2010. "Travel Choice Inertia: The Joint Role of Risk Aversion and Learning," ERIM Report Series Research in Management ERS-2010-040-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
- Ramadurai, Gitakrishnan & Ukkusuri, Satish V. & Zhao, Jinye & Pang, Jong-Shi, 2010. "Linear complementarity formulation for single bottleneck model with heterogeneous commuters," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 193-214, February.
- Laurent Denant-Boemont & Sabrina Hammiche, 2009.
"Public Transit Capacity and Users Choice: AnExperiment on Downs-Thomson Paradox,"
- Laurent Denant-Boèmont & Sabrina Hammiche, 2009. "Public Transit Capacity and Users' Choice: AnExperiment on Downs-Thomson Paradox," Post-Print halshs-00406223, HAL.
- Otsubo, Hironori & Rapoport, Amnon, 2008. "Vickrey's model of traffic congestion discretized," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 873-889, December.
- Rapoport, Amnon & Stein, William E. & Mak, Vincent & Zwick, Rami & Seale, Darryl A., 2010. "Endogenous arrivals in batch queues with constant or variable capacity," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1166-1185, December.
- de Jong, Gerard, 2012. "Application of experimental economics in transport and logistics," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 50, pages 3.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marion Oury).
If references are entirely missing, you can add them using this form.