Trajectory Planning for Autonomous Vehicles at Urban Intersections Based on Reachable Sets

In urban intersection scenarios, the traditional reachable set-based planning lacks the capability to account for traffic rules, while the spatiotemporal coupling characteristics lead to poor trajectory tracking performance during sharp turns. To address these issues, this paper introduces traffic rule semantics to constrain the coarse trajectories and drivable corridors during the reachable set-based coarse planning stage. Additionally, a decoupled planning approach is adopted to replace the coupled optimization method for fine planning in curved sections. The simulation results demonstrate that the proposed method could make autonomous vehicle almost in accordance with the traffic rules at urban intersections. Furthermore, the deviation error from the lane centerline during sharp turns is reduced by at least 46% compared to the coupled approach.