Mitigating social dilemmas in public transport choice through autonomous vehicles on a homogeneous road link

This paper investigates the impact of autonomous vehicles (AVs) operating in adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) modes on social dilemmas arising in public transport mode choice. Building upon previous studies of mixed traffic flows with buses and privately operated cars, we extend the model by incorporating connected AVs and analyzing their influence under various road configurations, including dedicated lanes for buses and AVs. We model traffic dynamics using a multi-lane cellular-automaton framework with revised S-NFS rules for human-driven vehicles and ACC/CACC protocols for AVs. The study focuses on a homogeneous multi-lane link with periodic boundary conditions, without intersections or traffic signals. The system is analyzed from the perspective of agent-based decision-making: agents choose between cooperative behavior (using buses) and defection (using private vehicles). The social efficiency of each configuration is assessed using the Social Efficiency Deficit (SED), a measure of the gap between the socially optimal and the Nash equilibrium state. Our simulations reveal that the introduction of AVs significantly alters the structure of social dilemmas. In scenarios with no dedicated lanes, increasing the AV fraction reduces the strength of the Prisoner’s Dilemma and eventually eliminates it. In scenarios with a dedicated bus lane, the system exhibits a chicken-type dilemma, whose equilibrium point shifts as the AV fraction increases. When AVs are allowed to use the bus lane, their strategic dominance leads to the disappearance of the dilemma and convergence toward a fully AV-based flow. A sensitivity analysis with respect to bus capacity confirms that the main results are robust, with the qualitative structure of social dilemmas remaining unchanged across different parameter values. These findings highlight the dual role of AVs as both disruptive and potentially cooperative agents shaping future urban mobility.