Evolutionary Game Model of Civil Aviation and High-Speed Rail Interaction Strategies Based on the Passenger Ticket and Carbon Trading Prices

Abstract

This study elaborated an evolutionary game model to optimize the decision-making process on the interaction between civil aviation and high-speed rail under alternative passenger ticket prices (PTPs) and carbon trading prices (CTPs). First, a logit model was used to calculate the passenger flow distribution rate in civil aviation and HSR, and their revenue loss function was determined according to varying PTPs and CTPs. Second, an evolutionary game model with incomplete information was developed to assess the respective revenues. Third, the stable strategy solution of the game model was derived from replicator dynamics, and an investigation of stable conditions under variable cases was performed. Finally, the simulation of a case study on the Beijing–Shanghai corridor was conducted to validate the proposed model’s feasibility. The additional revenue is shown to be the key influencing factor, mainly controlling the strategic decisions of airport and high-speed rail companies. Besides, the final strategy was strongly influenced by the alteration of PTPs and CTPs: higher PTPs promoted civil aviation and high-speed rail collaboration, while increased CTPs forced their competing behavior. The results obtained are instrumental in outlining the optimal strategy range for passenger ticket and carbon trading prices, encouraging high-speed transportation system growth.