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Is Equilibrium in Transport Pure Nash, Mixed or Stochastic? Evidence from Laboratory Experiments

Author

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  • Vinayak V Dixit

    (rCITI - Research Centre for Integrated Transport Innovation (rCITI) - UNSW@ADFA - University of New South Wales - Australian Defence Force Academy - UNSW - University of New South Wales [Sydney])

  • Laurent Denant-Boemont

    (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

Abstract

The classical theory of transport equilibrium is based on the Wardrop's first principle that describes a Nash User Equilibrium (UE), where in no driver can unilaterally change routes to improve his/her travel times. A growing number of economic laboratory experiments aiming at testing Nash-Wardrop equilibrium have shown that the Pure Strategy Nash Equilibrium (PSNE) is not able to explain the observed strategic choices well. In addition even though Mixed Strategy Nash Equilibrium (MSNE) has been found to fit better the observed aggregate choices, it does not explain the variance in choices well. This study analyses choices made by users in three different experiments involving strategic interactions in endogenous congestion to evaluate equilibrium prediction. We compare the predictions of the PSNE, MSNE and Stochastic User Equilibrium (SUE). In SUE, the observed variations in choices are assumed to be due to perception errors. The study proposes a method to iteratively estimate SUE models on choice data with strategic interactions. Among the three sets of experimental data the SUE approach was found to accurately predict the average choices, as well as the variances in choices. The fact that the SUE model was found to accurately predict variances in choices, suggests its applicability for transport equilibrium models that attempt to evaluate reliability in transportation systems. This finding is fundamental in the effort to determining a behaviourally consistent paradigm to model equilibrium in transport networks. The study also finds that Fechner error which is the inverse of the scale parameter in the SUE model is affected by the group sizes and the complexity of the cost function. In fact, the larger group sizes and complexity of cost functions increased the variability in choices. Finally, from an experimental design standpoint we show that it is not possible to estimate a noise parameter associate to Fechner error in the case when the choices are equally probable. 2

Suggested Citation

  • Vinayak V Dixit & Laurent Denant-Boemont, 2014. "Is Equilibrium in Transport Pure Nash, Mixed or Stochastic? Evidence from Laboratory Experiments," Post-Print halshs-01103472, HAL.
    • Handle: RePEc:hal:journl:halshs-01103472
    DOI: 10.1016/j.trc.2014.09.002
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01103472
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    References listed on IDEAS

    as
    1. Giovanna Devetag & Andreas Ortmann, 2007. "When and why? A critical survey on coordination failure in the laboratory," Experimental Economics, Springer;Economic Science Association, vol. 10(3), pages 331-344, September.
    2. 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.
    3. McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
    4. 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.
    5. Terry E. Daniel & Eyran J. Gisches & Amnon Rapoport, 2009. "Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks," American Economic Review, American Economic Association, vol. 99(5), pages 2149-2176, December.
    6. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1993. "A Structural Model of Peak-Period Congestion: A Traffic Bottleneck with Elastic Demand," American Economic Review, American Economic Association, vol. 83(1), pages 161-179, March.
    7. David A. Hensher, 2001. "Measurement of the Valuation of Travel Time Savings," Journal of Transport Economics and Policy, University of Bath, vol. 35(1), pages 71-98, January.
    8. Smith, Vernon L, 1976. "Experimental Economics: Induced Value Theory," American Economic Review, American Economic Association, vol. 66(2), pages 274-279, May.
    9. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    10. Noland, Robert B. & Small, Kenneth A. & Koskenoja, Pia Maria & Chu, Xuehao, 1998. "Simulating travel reliability," Regional Science and Urban Economics, Elsevier, vol. 28(5), pages 535-564, September.
    11. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-260, May.
    12. Fosgerau, Mogens, 2006. "Investigating the distribution of the value of travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 688-707, September.
    13. Goeree, Jacob K. & Holt, Charles A., 2005. "An Explanation of Anomalous Behavior in Models of Political Participation," American Political Science Review, Cambridge University Press, vol. 99(2), pages 201-213, May.
    14. Rapoport, Amnon & Mak, Vincent & Zwick, Rami, 2006. "Navigating congested networks with variable demand: Experimental evidence," Journal of Economic Psychology, Elsevier, vol. 27(5), pages 648-666, October.
    15. Hensher, David A., 2010. "Hypothetical bias, choice experiments and willingness to pay," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 735-752, July.
    16. Gary-Bobo, Robert J., 1990. "On the existence of equilibrium points in a class of asymmetric market entry games," Games and Economic Behavior, Elsevier, vol. 2(3), pages 239-246, September.
    17. Richard Mckelvey & Thomas Palfrey, 1998. "Quantal Response Equilibria for Extensive Form Games," Experimental Economics, Springer;Economic Science Association, vol. 1(1), pages 9-41, June.
    18. Frejinger, E. & Bierlaire, M., 2007. "Capturing correlation with subnetworks in route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 363-378, March.
    19. Fosgerau, Mogens & Frejinger, Emma & Karlstrom, Anders, 2013. "A link based network route choice model with unrestricted choice set," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 70-80.
    20. Bell, Michael G. H., 2000. "A game theory approach to measuring the performance reliability of transport networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(6), pages 533-545, August.
    21. Greiner, Ben, 2004. "An Online Recruitment System for Economic Experiments," MPRA Paper 13513, University Library of Munich, Germany.
    22. Robert B. Noland & John W. Polak, 2002. "Travel time variability: A review of theoretical and empirical issues," Transport Reviews, Taylor & Francis Journals, vol. 22(1), pages 39-54, January.
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    2. 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.
    3. Miguel F. Arevalo-Castiblanco & Jaime Pachon & Duvan Tellez-Castro & Eduardo Mojica-Nava, 2023. "Cooperative Cruise Control for Intelligent Connected Vehicles: A Bargaining Game Approach," Sustainability, MDPI, vol. 15(15), pages 1-21, August.
    4. Rapoport, Amnon & Qi, Hang & Mak, Vincent & Gisches, Eyran J., 2019. "When a few undermine the whole: A class of social dilemmas in ridesharing," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 125-137.

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    Keywords

    traffic equilibrium; stochastic user equilibrium; fechner error; scale parameter; Experimental economics;
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