A real-time decoupling trajectory planning method for on-road autonomous driving

Trajectory planning is a core technology for autonomous vehicle directlyreflecting the driving safety and efficiency. In this paper, a spatial-speed decoupled planning method is studied for real-time trajectory generation in the on-road environment. The proposed approach mainly includes two parts: optimization-based lateral planning and selection-based longitudinal speed planning. The optimization-based lateral planning is employed to generate an optimal collision-free and smooth path by solving a quadratic programming problem. Specifically, the lateral planning first constructs a safe corridor by integrating obstacles and initial risky corridor together in the Frenet frame. The safe corridor is useful for quadratic programming problem formulation. The selecting-based longitudinal speed planning is proposed to generate a suitable and continuous velocity trajectory. The novel speed selector considering four cases is designed to select a more suitable reference velocity in different lane situations. The continuous velocity trajectory is obtained by solving piecewise continuous quartic polynomial. As a result, the combination of the spatial path and the velocity trajectory is the final planning result. The proposed algorithm is tested extensively in a simulation environment. Experimental results demonstrate that the proposed algorithm has good real-time property and practical validity.

Automated summary

This paper studies a spatial-speed decoupled planning method for real-time trajectory generation in the on-road environment. The method includes optimization-based lateral planning and selection-based longitudinal speed planning. Experimental results demonstrate that the proposed algorithm has good real-time property and practical validity.