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Road Traffic Congestion and Public Information: An Experimental Investigation

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  • Anthony Ziegelmeyer
  • Frédéric Koessler
  • Kene Boun My
  • Laurent Denant-Boèmont

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. © 2008 LSE and the University of Bath

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  • 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, University of Bath, vol. 42(1), pages 43-82, January.
  • Handle: RePEc:tpe:jtecpo:v:42:y:2008:i:1:p:43-82
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    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    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. Andre de Palma & Moshe Ben-Akiva & Claude Lefevre & Nicolaos Litinas, 1983. "Stochastic Equilibrium Model of Peak Period Traffic Congestion," Transportation Science, INFORMS, vol. 17(4), pages 430-453, November.
    4. 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.
    5. 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.
    6. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-260, May.
    7. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1990. "Economics of a bottleneck," Journal of Urban Economics, Elsevier, vol. 27(1), pages 111-130, January.
    8. David Levinson, 2003. "The Value of Advanced Traveler Information Systems for Route Choice," Working Papers 200307, University of Minnesota: Nexus Research Group.
    9. Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
    10. 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 848-881, September.
    11. 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.
    12. Moshe Ben-Akiva & Andre de Palma & Pavlos Kanaroglou, 1986. "Dynamic Model of Peak Period Traffic Congestion with Elastic Arrival Rates," Transportation Science, INFORMS, vol. 20(3), pages 164-181, August.
    13. 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.
    14. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945.
    15. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
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    2. 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.
    3. 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 1-3.
    4. Rey, David & Dixit, Vinayak V. & Ygnace, Jean-Luc & Waller, S. Travis, 2016. "An endogenous lottery-based incentive mechanism to promote off-peak usage in congested transit systems," Transport Policy, Elsevier, vol. 46(C), pages 46-55.
    5. 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, University of Bath, vol. 46(1), pages 139-155, January.
    6. Laurent Denant-Boemont & Sabrina Hammiche, 2009. "Public Transit Capacity and Users Choice: AnExperiment on Downs-Thomson Paradox," Working Papers halshs-00405501, HAL.
    7. Nicholas Janusch & Stephan Kroll & Christopher Goemans & Todd L. Cherry & Steffen Kallbekken, 2021. "Learning to accept welfare-enhancing policies: an experimental investigation of congestion pricing," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 59-86, March.
    8. Vinayak Dixit & Laurent Denant-Boemont, 2014. "Is Equilibrium in Transport Pure Nash, Mixed or Stochastic? Evidence from Laboratory Experiments," Post-Print halshs-01103472, HAL.
    9. Chidambaram, Bhuvanachithra & Janssen, Marco A. & Rommel, Jens & Zikos, Dimitrios, 2014. "Commuters’ mode choice as a coordination problem: A framed field experiment on traffic policy in Hyderabad, India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 9-22.
    10. Emmanuel Dechenaux & Shakun Mago & Laura Razzolini, 2014. "Traffic congestion: an experimental study of the Downs-Thomson paradox," Experimental Economics, Springer;Economic Science Association, vol. 17(3), pages 461-487, September.
    11. Morgan, John & Orzen, Henrik & Sefton, Martin, 2009. "Network architecture and traffic flows: Experiments on the Pigou-Knight-Downs and Braess Paradoxes," Games and Economic Behavior, Elsevier, vol. 66(1), pages 348-372, May.
    12. Sun, Xiaoyan & Han, Xiao & Bao, Jian-Zhang & Jiang, Rui & Jia, Bin & Yan, Xiaoyong & Zhang, Boyu & Wang, Wen-Xu & Gao, Zi-You, 2017. "Decision dynamics of departure times: Experiments and modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 74-82.
    13. Hamed Alibabai & Hani S. Mahmassani, 2016. "Foxes and sheep: effect of predictive logic in day-to-day dynamics of route choice behavior," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 53-67, March.
    14. 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.
    15. Li, Zhi-Chun & Huang, Hai-Jun & Yang, Hai, 2020. "Fifty years of the bottleneck model: A bibliometric review and future research directions," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 311-342.
    16. Guo, Ren-Yong & Yang, Hai & Huang, Hai-Jun & Li, Xinwei, 2018. "Day-to-day departure time choice under bounded rationality in the bottleneck model," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 832-849.
    17. Wijayaratna, Kasun P. & Dixit, Vinayak V., 2016. "Impact of information on risk attitudes: Implications on valuation of reliability and information," Journal of choice modelling, Elsevier, vol. 20(C), pages 16-34.
    18. Rapoport, Amnon & Gisches, Eyran J. & Daniel, Terry & Lindsey, Robin, 2014. "Pre-trip information and route-choice decisions with stochastic travel conditions: Experiment," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 154-172.
    19. 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.

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    More about this item

    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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