A Trajectory Planning Method for Proactive Driving Support Systems in Urban Areas Based on An Inverse Collision Probability Model

Abstract

This paper presents a path planning method for driver assistance systems in mixed urban scenarios. We proposed an inverse collision probability model based motion planner to generate the trajectory, including the positions to path through multiple traffic participants. To design the probabilistic models which represent an obstacle avoidance maneuver, we collect and analyze driving data of expert driver. Then, we conceder the direction and the value of time to collision of the target traffic participant. Then, we show the difference of driving behaviors of the expert drivers according to the difference of the direction of the target. The proposed method generates the optimal trajectory plan by using the global optimization algorithm named Belief Propagation. Finally, we show the evaluation experiment that compares the difference between the trajectories generated by the proposed method and natural driving data.