Road Traffic Congestion and Public Information: An Experimental Investigation
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 total travel costs match the predicted ones. In other words, subjects' capacity to coordinate is neither affected by the availability of public information on past departure rates nor by the relative cost of delay. This 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 subjects’ capacity to coordinate is not affected by the size of the population.
|Date of creation:||Dec 2006|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +49-3641-68 65
Fax: +49-3641-68 69 90
Web page: http://www.econ.mpg.de/
More information through EDIRC
|Order Information:|| Web: http://www.econ.mpg.de/english/research/ESI/discuss.php Email: |
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.:
- Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1990.
"Economics of a bottleneck,"
Journal of Urban Economics,
Elsevier, vol. 27(1), pages 111-130, January.
- 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.
- 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.
- Drew Fudenberg & David K. Levine, 1998.
"Learning in Games,"
Levine's Working Paper Archive
2222, David K. Levine.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
When requesting a correction, please mention this item's handle: RePEc:esi:discus:2006-20. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Karin Richter)The email address of this maintainer does not seem to be valid anymore. Please ask Karin Richter to update the entry or send us the correct address
If references are entirely missing, you can add them using this form.