Cooperative Path Planning Using Responsibility-Sensitive Safety (RSS)-based Potential Field with Sigmoid Curve

Potential field (PF)-based path planning is reported to be highly efficient for autonomous vehicles because it performs risk-aware computation and has a simple structure. However, the inherent limitations of the PF make it vulnerable in some specific traffic scenarios, such as local minima and oscillations in close obstacles. Therefore, a hybrid path planning with the sigmoid curve has recently been presented to generate better trajectories than those generated by the PF for collision avoidance. However, it is time-consuming and less applicable in complex dynamic environments, especially in traffic emergencies. To address these limitations, we propose a cooperative hybrid path planning (CHPP) approach that involves collaboration with adjacent vehicles for emergency collision avoidance via V2V communication. Moreover, the responsibility-sensitive safety (RSS) model is introduced to enhance the PF and sigmoid curve for safe-critical and time-saving requirements. The effectiveness of the proposed CHPP method compared with the state-of-the-art methods is studied through simulation of both static and dynamic traffic emergency scenarios. The simulation results prove that the CHPP approach performs better in terms of computation time (0.02 s faster) and driving safety (avoiding collision) than other methods, which are more supportive for emergency cooperative driving.