A Sliding Mode Control Architecture for Autonomous Driving in Highway Scenarios Based on Quadratic Artificial Potential Fields

Abstract

An approach for automated driving in highway scenarios based on Super-Twisting (STW) Sliding Mode Control (SMC) methodologies supported by the use of Artificial Potential Fields (APF) is presented. The use of APF allows us to propose an effective SMC solution based on the gradient tracking (GT) principle. In this regard, a novel formulation of the APF functions is introduced that exploits a sequence of attractive quadratic functions. This solution simplifies the computation of the fields and allows for trajectory generation with improved regularity properties. Extensive simulation tests, as well as comparisons with baseline and state of the art solutions, show the effectiveness of the proposed approach.