Abstract
In this study, an artificial traffic system, which is generated on a computer by utilizing the computational technique, has been developed by establishing brilliant lane-changing criteria for the Cellular Automata (CA) traffic model to figure out adequate strategies for cooperative driving that can be implemented in actual traffic systems for optimum use of existing road facilities. We investigate the flow efficiency and social dilemma, which embody the tension between the demanded road facility and the existing road facility, that emerged due to the defector drivers in a traffic flow system, who are highly aggressive in driving and impose threatening/pushing effects on their preceding while they are tailgating. The evolutionary game theory, which is one of the most efficient tools in the decision-making process, has been utilized to identify the Social Efficiency Deficit (SED), which means the dilemma strength of those games. We introduced a new lane-changing protocol for the preceding vehicle, considering the threatening effects given by the aggressive follower. This investigation explored several case studies defining various strategies for cofactors and defectors. We conducted a series of multi-agent simulations on this traffic flow system and experienced the Prisoner's Dilemma (PD) and the Quasi-Prisoner's Dilemma game with diverse dilemma strengths for four different strategies for cooperators and defectors.