A Trajectory Planning Method Considering Intention-aware Uncertainty for Autonomous Vehicles
Huina Chen, Xiaonian Wang, Jun Wang · 2018
This paper presents a trajectory planning method for autonomous vehicles considering the uncertainty caused by other traffic participants. The presented method employs a two-step architecture. In the first step, Bézier curves based approach generates a set of trajectory candidates. In the second step, an online selector is used to select the most appropriate one. In this step, an uncertainty model considering the intentions of other traffic participants is used to evaluate the collision probability. The uncertainty model generates probabilistic trajectories to express the potential motions of guest vehicles under different intentions. Compared with the previous work, the uncertainty model in our trajectory planning method takes the uncertainty of guest vehicle's intentions into account rather than focusing on the current heading and velocity. Simulation results demonstrate the feasibility and safety of the proposed method in different scenarios.