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Network Architecture and Traffic Flows: Experiments on the Pigou-Knight-Downs and Braess Paradoxes

Listed author(s):
  • John Morgan

    ()

    (University of California, Berkeley)

  • Henrik Orzen

    ()

    (School of Economics, University of Nottingham)

  • Martin Sefton

    ()

    (School of Economics, University of Nottingham)

This paper presents theory and experiments to investigate how network architecture influences route-choice behavior. We consider changes to networks that, theoretically, exhibit the Pigou- Knight-Downs and Braess Paradoxes. We show that these paradoxes are specific examples of more general classes of network change properties that we term the “least congestible route” and “size” principles, respectively. We find that technical improvements to networks induce adjustments in traffic flows. In the case of network changes based on the Pigou-Knight-Downs Paradox, these adjustments undermine short-term payoff improvements. In the case of network changes based on the Braess Paradox, these adjustments reinforce the counter-intuitive, but theoretically predicted, effect of reducing payoffs to network users. Although aggregate traffic flows are close to equilibrium levels, we see some systematic deviations from equilibrium. We show that the qualitative features of these discrepancies can be accounted for by a simple reinforcement learning model.

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Paper provided by The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham in its series Discussion Papers with number 2007-05.

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Date of creation: Aug 2007
Handle: RePEc:not:notcdx:2007-05
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Web page: http://www.nottingham.ac.uk/economics/cedex/

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  1. Penchina, Claude M., 1997. "Braess paradox: Maximum penalty in a minimal critical network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 31(5), pages 379-388, September.
  2. Hartman, John Lawrence, 2007. "The Relevance of Heterogeneity in a Congested Route Network with Tolls: An Analysis of Two Experiments Using Actual Waiting Times and Monetized Time Costs," University of California at Santa Barbara, Economics Working Paper Series qt22b46341, Department of Economics, UC Santa Barbara.
  3. Erel Avineri & Joseph Prashker, 2006. "The Impact of Travel Time Information on Travelers’ Learning under Uncertainty," Transportation, Springer, vol. 33(4), pages 393-408, July.
  4. 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.
  5. Pas, Eric I. & Principio, Shari L., 1997. "Braess' paradox: Some new insights," Transportation Research Part B: Methodological, Elsevier, vol. 31(3), pages 265-276, June.
  6. Iida, Yasunori & Akiyama, Takamasa & Uchida, Takashi, 1992. "Experimental analysis of dynamic route choice behavior," Transportation Research Part B: Methodological, Elsevier, vol. 26(1), pages 17-32, February.
  7. Hartman, John Lawrence, 2007. "A Route Choice Experiment With an Efficient Toll," University of California at Santa Barbara, Economics Working Paper Series qt4s1116mv, Department of Economics, UC Santa Barbara.
  8. Glenn Ellison & Drew Fudenberg & Markus Möbius, 2004. "Competing Auctions," Journal of the European Economic Association, MIT Press, vol. 2(1), pages 30-66, March.
  9. 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.
  10. 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.
  11. Milchtaich, Igal, 1996. "Congestion Games with Player-Specific Payoff Functions," Games and Economic Behavior, Elsevier, vol. 13(1), pages 111-124, March.
  12. 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.
  13. Horowitz, Joel L., 1984. "The stability of stochastic equilibrium in a two-link transportation network," Transportation Research Part B: Methodological, Elsevier, vol. 18(1), pages 13-28, February.
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