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Experiments and Simulations on Day-to-Day Route Choice-Behaviour

  • Reinhard Selten
  • M. Schreckenberg
  • Thomas Pitz
  • T. Chmura
  • S. Kube

The paper reports laboratory experiments on a day-to-day route choice game with two routes. Subjects had to choose between a main road M and a side road S. The capacity was greater for the main road. 18 subjects participated in each session. In equilibrium the number of subjects is 12 on M and 6 on S. Two treatments with 6 sessions each were run at the Laboratory of Experimental Economics at Bonn University using RatImage. Feedback was given in treatment I only about own travel time and in treatment II on travel time for M and S. Money payoffs increase with decreasing time. The main results are as follows. 1. Mean numbers on M and S are very near to the equilibrium. 2. Fluctuations persist until the end of the sessions in both treatments. 3. Fluctuations are smaller under treatment II .The effect is small but significant. 4. The total number of changes is significantly greater in treatment I. 5. Subjects’ road changes and payoffs are negatively correlated in all sessions. 6. A direct response mode reacts with more changes for bad payoffs whereas a contrary response mode shows opposite reactions. Both response modes can be observed. 7. The simulation of an extended payoff sum learning model closely fits the main results of the statistical evaluation of the data.

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Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 900.

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Date of creation: 2003
Date of revision:
Handle: RePEc:ces:ceswps:_900
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  1. Abbink, Klaus & Abdolkarim Sadrieh, 1995. "RatImage - research Assistance Toolbox for Computer-Aided Human Behavior Experiments," Discussion Paper Serie B 325, University of Bonn, Germany.
  2. 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.
  3. A. Roth & I. Er’ev, 2010. "Learning in Extensive Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Run," Levine's Working Paper Archive 387, David K. Levine.
  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 848-81, September.
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