Dynamic Evolutionary Game on Travel Mode Choices Among Buses, Ride-Sharing Vehicles, and Driving Alone in Shared Bus Lane Scenarios

Sharing bus lanes with ride-sharing vehicles is beneficial for improving the utilization efficiency of these lanes and alleviating urban traffic pressure. This paper applies evolutionary game theory to explore the evolutionary game dynamics of three travel modes—buses, ride-sharing vehicles, and driving alone—under different sharing strategy scenarios for bus lanes. Before constructing the game model, various influencing factors such as travel costs, time costs, and the combined costs of ride-sharing are quantified to calculate the cumulative prospect values before travel. The gains and losses in the cumulative prospect values are defined as parameter variables in the game model, establishing a payoff matrix for the three travel modes: buses, ride-sharing vehicles, and private cars. During the model-solving process, the Lyapunov first method is used for stability analysis of the equilibrium points, resulting in three groups of asymptotically stable equilibrium points. By rotating the parameter values according to the actual circumstances of different sharing strategies, the model simulates and evaluates the impact of various sharing policies on the travel mode choices among the three options. The results indicate that the gain and loss values in the cumulative prospect values of travel modes are key factors influencing travelers’ mode choices. Under the synergistic effects of urban ride-sharing policies and traffic system optimization, when the cumulative prospect value of ride-sharing is a gain, travelers recognize its advantages and are willing to choose it. Conversely, when the cumulative prospect value indicates a loss, travelers are more inclined to choose bus travel or driving alone. This paper provides a theoretical foundation for the formulation of sharing policies for bus lanes with ride-sharing, contributing to improved utilization efficiency of these lanes and alleviating urban traffic pressure.