Improvement of the Autodriver Algorithm for Autonomous Vehicles Using Roll Dynamics

Abstract

The autodriver algorithm was introduced as a path-following algorithm for autonomous vehicles, which uses road geometry data and planar vehicle dynamics. In this paper, the autodriver algorithm is improved according to practical implications, and a more realistic vehicle model (roll mode) is used, which considers roll degree of freedom in addition to a planar motion. A Ghost-Car path-following approach is introduced to define the desired location of the car at every instance. Key steady-state characteristics of turning vehicles, namely the curvature, yaw rate, and side-slip responses, are discussed and used to construct a feed-forward component of a path-following controller based on the autodriver algorithm. Feedback control loops are designed and applied to minimise transient errors between the road and vehicle positions. Finally, simulations are performed to analyse the path-following performance of the proposed scheme. The results show promising performance of the controller both in terms of error minimisation and passenger comfort.