Speed Planning Using Bezier Polynomials with Trapezoidal Corridors
This addresses dynamic obstacle avoidance for autonomous vehicles, but it is incremental as it builds on existing path and speed decoupled planning methods.
The paper tackled speed planning for autonomous vehicles in dynamic environments by using dynamic programming to search heuristic waypoints and constructing convex feasible spaces, then applying piecewise Bezier polynomials optimization with trapezoidal corridors to guarantee safety and optimality, with simulations verifying effectiveness.
To generate safe and real-time trajectories for an autonomous vehicle in dynamic environments, path and speed decoupled planning methods are often considered. This paper studies speed planning, which mainly deals with dynamic obstacle avoidance given the planning path. The main challenges lie in the decisions in non-convex space and the trade-off between safety, comfort and efficiency performances. This work uses dynamic programming to search heuristic waypoints on the S-T graph and to construct convex feasible spaces. Further, a piecewise Bezier polynomials optimization approach with trapezoidal corridors is presented, which theoretically guarantees the safety and optimality of the trajectory. The simulations verify the effectiveness of the proposed approach.