In order to enhance the control measures of the public transportation priority policy and understand the mode choice process of urban residents for travel, a research was conducted to investigate the evolutionary game model of mode choice for urban residents. The study was based on the principles of behavioral economics theory and prospect theory, and incorporated the concept of mental accounting by constructing profit and loss accounts. Using evolutionary game theory, an evolutionary game model was developed between travelers and government agencies. The dynamic evolution process and stability conditions of both parties′ strategies were analyzed using replicator dynamics equations. The research identified the constraints of the system′s optimal state and system fluctuation state. Moreover, the main reasons for the deviation from the ideal state of the evolutionary trend in reality were explained from the perspectives of government perception and traveler perception. Additionally, the study identified the main problems of the current government control measures. Numerical simulations were conducted using MATLAB, and an optimization model with a dynamic performance payment mode for government subsidies was introduced. The research findings showed that the stable probability of travelers choosing public transportation was 0.33, and the probability of government participation in control was 0.92. Sensitivity analysis of the utility parameters was also conducted. The results of the study indicate that the government should focus on optimizing its public transportation control strategy by reducing the cost of public transportation, appropriately increasing the cost of private car travel, and shortening the travel time of public transportation. This would significantly increase the probability of urban residents choosing public transportation. In summary, the research provides a theoretical basis for urban transportation planning and public transportation priority policy optimization.