Design and Implementation of Path Trackers for Ackermann Drive based Vehicles

Abstract

This article is an overview of the various literature on path tracking methods and their implementation in simulation and realistic operating environments. The scope of this study includes analysis, implementation, tuning, and comparison of some selected path tracking methods commonly used in practice for trajectory tracking in autonomous vehicles. Many of these methods are applicable at low speed due to the linear assumption for the system model, and hence, some methods are also included that consider non-linearities present in lateral vehicle dynamics during high-speed navigation. The performance evaluation and comparison of tracking methods are carried out on realistic simulations and a dedicated instrumented passenger car, Mahindra e2o, to get a performance idea of all the methods in realistic operating conditions and develop tuning methodologies for each of the methods. It has been observed that our model predictive control-based approach is able to perform better compared to the others in medium velocity ranges.

Autonomous vehicle tracking control for a curved trajectory

“…Drifting sometimes occurs when tracking a sharp bend at a high speed, so the vehicle requires to drive at a low speed when tracking this path [25]- [27]. The feedback linearization approach is appropriate to implement in a complex road scenario such as a curvature road because it considers all parameters and conditions from the system model and its environments to meet the requirement of a dynamic system's stable and robust condition [28], [29].…”