Clothoid-based Lane Change Trajectory Computation for Self-Driving Vehicles

Abstract

The subject of this paper is the efficient computation of lane change trajectories for self-driving vehicles. The paper first identifies that a certain type of clothoid-based bi-elementary paths can be used to represent lane change trajectories for vehicles. It is further highlighted that the curvature of such trajectories must be adjusted to the driving situation in order to obtain feasible lane change trajectories. Accordingly, the paper establishes an analytical relation between the maximum admissible curvature of the lane change trajectory and the velocity profile during a lane change. Using this relation, the paper proposes an efficient Newton iteration for computing the parameters of bi-elementary paths for lane changes. The resulting lane change trajectories are as short as possible, while meeting the constraint on the maximum curvature. Simulation experiments for various driving situations show that the computed bi-elementary paths can be computed efficiently and constitute suitable lane change trajectories.