Is equilibrium in transport pure Nash,mixed or Stochastic? |
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| Institution: | 1. Research Centre for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, University of New South Wales, Australia;2. Department of Economics, CREM Université de Rennes 1, Rennes, France;1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, 100044 Beijing, PR China;2. College of Transportation, Shandong University of Science and Technology, 266590 Qingdao, PR China;3. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, 100044 Beijing, PR China;4. College of Economics and Management, Shandong University of Science and Technology, 266590 Qingdao, PR China;5. School of Traffic and Transportation Engineering, Central South University, 410075 Changsha, PR China;1. Department of Industrial Engineering, Tsinghua University, Beijing 100084, PR China;2. Department of Civil and Coastal Engineering, University of Florida, Gainesville, FL 32611, United States;3. School of Management and Engineering, Nanjing University, Nanjing 210093, PR China;1. Finnish Environment Institute (SYKE), Freshwater Centre, P.O. Box 140, FI-00251 Helsinki, Finland;2. Finnish Environment Institute (SYKE), Freshwater Centre, P.O. Box 413, FI-90014 Oulu, Finland;3. University of Oulu, Department of Ecology, FIN-90014 Oulu, Finland;1. Technical University of Denmark, Denmark;2. Royal Institute of Technology, Sweden;1. Beijing Key Laboratory of Transportation Engineering, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China;2. College of Urban Construction, Hebei Normal University of Science and Technology, 360 Western Section of Hebei Avenue, Haigang District, Qinhuangdao, Hebei 066004, China;3. Institute of Industrial Science, The University of Tokyo, Komaba 4-6-1, Meguro-ku, Tokyo 153-8505, Japan;4. Graduate School of Information Sciences, Tohoku University, Aramaki Aoba 6-3-09, Aoba-ku, Sendai, Miyagi 980-8579, Japan;5. Graduate School of Engineering, Tohoku University, Aramaki Aoba 6-6, Aoba-ku, Sendai, Miyagi 980-8579, Japan |
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| 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. |
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| Keywords: | Experimental economics Traffic equilibrium Stochastic User Equilibrium Fechner error Scale parameter |
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