Active Collision Avoidance Strategy Considering Motion Uncertainty of the pedestrian
Jian Feng, Chunyan Wang, Can Xu, Dengming Kuang, Wanzhong Zhao
Abstract
This work proposes an active collision avoidance between autonomous driving vehicle and pedestrian with motion uncertainty under urban road. A candidate trajectory planning method considering spatial and time sequences is proposed, which combines the polynomial path planning and the velocity planning with variable safety velocity. Then, a pedestrian-vehicle interaction model is constructed, which takes the pedestrian’s uncertain motion as a superposition of the Markov process without interference and the motion caused by the vehicle, and predicts the pedestrian’s motion probabilistically. On these bases, the optimal trajectory is evaluated from the candidate trajectories by safety, stability, and efficiency, as well as different driving styles. The proposed collision avoidance strategy is verified in conventional and emergency simulation scenarios. Simulation results show that it can effectively plan a safe, stable and efficient trajectory under normal and emergency conditions.