Overtaking on two-lane two-way rural roads: A personalized and reactive approach for automated vehicle

Abstract

Research on Connected and Automated Vehicles (CAV) has primarily focused on highway and urban environments, neglecting the significance and dangers of two-lane two-way rural roads. However, CAV driving strategies have the potential to improve significantly this network safety, particularly in critical maneuvers such as overtaking. This paper proposes an overall safety autonomous driving architecture particularly adapted to overtaking maneuver in a two-lane two-way rural road context. The proposed architecture considers vehicle connectivity to share their ego speeds and positions, enabling a rule-based decision-making process coupled with a Fuzzy Inference Systems (FIS) to manage the maneuver’s tasks and to ensure the feasibility of the maneuver. A safety-oriented abort task facilitates a return to the starting lane in case of potential collisions improving maneuver reactivity. Additionally, an original driving personalization is proposed through one driving style parameter modifying the trajectory shape and the maneuver initiation. Two low level controllers handle the vehicle control signals for braking, throttle, and steering wheel angle completing the architecture and allowing full autonomous driving. The algorithm is evaluated using a high fidelity simulation environment in different driving situations. The obtained results demonstrate its reliability and consistency in producing safe overtaking maneuvers regardless the generated situation. A Monte Carlo test highlights the correlation between driving style and comfort in most cases. However, the algorithm limited to two vehicles in the surrounding environment needs improvement to cope with more diverse driving situations.