Spatio-temporal Motion Planning for Autonomous Vehicles with Trapezoidal Prism Corridors and Bézier Curves

作     者：Deolasee, Srujan Lin, Qin Li, Jialun Dolan, John M. 

作者机构：Department of Computer Science & Information Systems Birla Institute of Technology and Science Rajasthan Pilani India Department of Electrical Engineering and Computer Science Cleveland State University ClevelandOH United States Dajiang Innovation Technology Co. Ltd Shenzhen China Robotics Institute Carnegie Mellon University PittsburghPA United States 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2022年

核心收录：

主　　题：Motion planning 

摘      要：Safety-guaranteed motion planning is critical for self-driving cars to generate collision-free trajectories. A layered motion planning approach with decoupled path and speed planning is widely used for this purpose. This approach is prone to be suboptimal in the presence of dynamic obstacles. Spatial-temporal approaches deal with path planning and speed planning simultaneously;however, the existing methods only support simple-shaped corridors like cuboids, which restrict the search space for optimization in complex scenarios. We propose to use trapezoidal prism-shaped corridors for optimization, which significantly enlarges the solution space compared to the existing cuboidal corridors-based method. Finally, a piecewise Bézier curve optimization is conducted in our proposed corridors. This formulation theoretically guarantees the safety of the continuous-time trajectory. We validate the efficiency and effectiveness of the proposed approach in numerical and CommonRoad simulations. © 2022, CC BY.