Trajectory Planning for Autonomous Ground Vehicles Driving in Structured Environments

To solve the problem of trajectory planning for Autonomous Ground Vehicles (AGVs) in structured environments, a kinematically-feasible trajectory planning approach based on road models is proposed. In order to cope with obstacle avoidance on roads, we develop an efficient path generation method, using the piecewise spiral curve to generate a set of continuous curvature paths which satisfy the constraints of the start and end point boundaries. Based on the proposed optimization function, the optimal path is selected. Compared with the model-based predictive trajectory planner, the method proposed in this paper can effectively avoid the problem of slow convergence or no feasible solution. The experimental results show that: The proposed method not only retains most of the advantages of model-based predictive trajectory planning, but also reduces the computational complexity to meet the real-time requirements. The curvature of the generated path is continuous and is suitable for the actual control of the vehicle. Simulation results show that the proposed method can track the reference path smoothly and avoid static obstacles successfully.