Finite-time variable gains super-twisting control for lane-changing of autonomous vehicles

Uncertainties, parameters variations and external disturbances may affect highly the task of lane-keeping, lane-changing and path-tacking autonomous vehicles. This paper presents a novel variable gains second-order sliding mode algorithm for en-hanced path tracking performance of autonomous vehicles subject to uncertainties and disturbances. The used algorithm is a modified super-twisting with both nonlinear and linear correction terms. Hence, the proposed method doesn’t suffer from the chattering phenomenon, ensures high order precision and guarantees both the robustness against perturbations and the convergence in finite-time during the reaching phase. To evaluate the efficiency of the developed approach, a double lane-changing scenario is considered in simulation for an uncertain autonomous vehicle and the results are compared with the first-order sliding mode.