Investigating the impact of connected and autonomous vehicles on a grid urban network considering different driving behaviors

In recent years, the utilization of intelligent transportation systems (ITS) has been significantly augmented due to advancements in the fields of computer science and information technology. Connected and autonomous vehicle (CAV) technology has gained a significant amount of attention in the research community. The advancements in connected and autonomous vehicle technology are expected to have an influence on the current transportation networks in the near future. The main purpose of this study is to investigate the influence of different driving behaviors of CAVs, namely defensive, normal, and aggressive, on a grid urban network consisting of unsignalized intersections in terms of traffic efficiency, traffic emissions, fuel consumption, and traffic safety by utilizing an open-source simulation tool called SUMO. Three different demand configurations and varying penetration rates of different behaviors for CAVs were taken into account in the scope of this study. According to the findings of the study, while CAVs with defensive behavior lead to an increase in average time loss, CAVs with aggressive behavior reduce the average time loss with increased penetration rates. The reduction in vehicle emissions and fuel consumption is not valid for all driving behaviors of CAVs. It was observed that it depends on the driving behavior of CAVs, penetration rates, and demand configurations. In terms of traffic safety, the worst performance was obtained by CAV-aggressive behavior. Furthermore, it was found that there is a trade-off between traffic efficiency and traffic safety metrics regarding the driving behavior of CAVs.