Trajectory Planning with Comfort and Safety in Dynamic Traffic Scenarios for Autonomous Driving

Abstract

Trajectory planning is one of the most important modules of the Autonomous Driving Systems (ADSs), which aims to achieve a safe and comfortable interaction between the ADSs and obstacles. Currently, it remains a challenging issue to simultaneously ensure the comfort and safety of the planned trajectory, especially in dynamic traffic scenarios. In this paper, a trajectory planning method is proposed for autonomous vehicles to drive in dynamic traffic scenarios considering both comfort and safety. First, trajectory candidates are generated through the separation of path generation and velocity generation, and then some cost functions are constructed to evaluate each trajectory candidate to obtain the final trajectory. The proposed trajectory generation method guarantees the continuity of generated trajectory in both curvature and jerk, and the cost functions are proposed with the Trajectory Comfort Evaluation Model (TCEM) and Trajectory Safety Evaluation Model (TSEM), which balance the comfort and safety of a trajectory. Experiments prove the effectiveness of the proposed trajectory planner and its robustness in dynamic traffic scenarios.