Nash Equilibrium Analysis Based on a Generalized Travel Cost

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To explore travel options and travel equilibrium problem in urban traffic, the traditional research mainly focuses on the degree of association & mechanism between the travelers' choice behavior and influence factors. A generalized travel cost model is constructed based on the analysis of the main factors affecting travel behavior in the paper, the Nash equilibrium theory is introduced to analyze the best travel combinations between travel routes and transportation modes during to the travel cost matrix based on generalized travel cost, and Nash equilibrium cost matrix can be get. In this equilibrium condition, the generalized travel cost of each travel route and transportation mode becomes more balanced, which benefit distribution equilibrium; and no operator can obtain higher profits by changing the price strategy unilaterally, which ensure the stability of the cost matrix. The example and conclusion shows that the Nash equilibrium is existed in the analysis of cost in travel choice, and confirms that a better balanced travel can be obtained by adjusting the travel cost.

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2205-2212

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July 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] T. Gärling, D. Eek and P. Loukopoulos, et al. A conceptual analysis of the impact of travel demand management on private car use., Transport Policy, 9, 59-70(2002).

DOI: 10.1016/s0967-070x(01)00035-x

Google Scholar

[2] M. Kuby, A. Barranda and C. Upchurch, Factors influencing light-rail station boardings in the United States., Transportation Research Part A: Policy and Practice, 38, 223-247(2004).

DOI: 10.1016/j.tra.2003.10.006

Google Scholar

[3] H.F. Jia, B.W. GONG and F. ZONG, Disaggregate modeling of traffic mode choice and its application, Journal of Jilin University: Engineering and Technology Edition, 37, 1289-1293(2007).

Google Scholar

[4] B.E. Liu, Z.C. Jun and Y.L. LI, et al. Development of a Multinomial Logit Model for Trave Mode Choice of Residents, [J]. Journal of Highway and Transportation Research and Development, 25, 116-120(2008).

Google Scholar

[5] L.Y. Yang, C.F. SHAO and X. LI. Structural equation model analysis of travel mode choice for urban residents, Journal of Beijing Jiaotong University, 35, 1-6(2011).

Google Scholar

[6] C.W. Yuan, X.X. YU and H.P. LU, et al. Road Network Equilibrium Traffic Assignment Method Based on Stackelberg Game, China Journal of Highway and Transport, 22, 89-93(2009).

Google Scholar

[7] P.K. Bhaumik, Regulating the domestic air travel in India: an umpire's game, Omega, 30, 33-44(2002).

DOI: 10.1016/s0305-0483(01)00050-0

Google Scholar

[8] J. Zhou, W.H.K. Lam and B.G. Heydecker, The generalized Nash equilibrium model for oligopolistic transit market with elastic demand, Transportation Research Part B: Methodological, 39, 519-544(2005).

DOI: 10.1016/j.trb.2004.07.003

Google Scholar

[9] H. Peng, Z.F. XU and Y.Q. HAN, et al. Sharing ratios model of passenger flows in intercity transportation structure configuration among urban agglomeration" Journal of Chang, an University: Natural Science Edition, 32, 91-95(2012).

Google Scholar

[10] H. Song, C.C. Liu and J. Lawarrée, Nash equilibrium bidding strategies in a bilateral electricity market, Power Systems, 17, 73-79(2002).

DOI: 10.1109/59.982195

Google Scholar

[11] N. Adler, E. Pels, and C. Nash, High-speed rail and air transport competition: Game engineering as tool for cost-benefit analysis, Transportation Research Part B: Methodological, 44, 812-833(2010).

DOI: 10.1016/j.trb.2010.01.001

Google Scholar