High Definition Map Based Motion Plan and Control of Autonomous Vehicle on Structured Road

Abstract

A high definition (HD) map based motion plan and control method of autonomous vehicle on structured road is proposed in this paper. The system is designed in a multi-layer structure: A motion planner and a motion controller, furthermore, the motion planner is consisted of a global path planner and a local trajectory planner. The inputs of the global path planner are HD map, start and goal state, Dynamic Program (DP) is used to plan a global path that connect these two states based on the lane-level structures and traffic rules extracted from HD map. The inputs of local motion planner are the planned global path, current host vehicle state and the surrounding dynamic object information, several candidate trajectories are generated in Frenet frame, and then the optimal one is chosen by a multi-Term cost function calculation. Taking the vehicle dynamics under high speed into consideration, Model Predictive Control (MPC) is used in motion controller to track the planned target trajectory. Results of the conducted simulation tests show that the designed motion plan and control method works well in velocity keeping, vehicle following, stopping and going, and vehicle passing scenarios.