Path tracking for electric vehicles with multiple chassis actuators based on classical control techniques

Path tracking is a fundamental component of autonomous vehicle control, respon- sible for ensuring that a vehicle follows a predefined path with high precision. With the rapid advancement of enabling technologies such as sensor systems, real- time data processing, and vehicle-to-everything (V2X) communication, modern autonomous systems can now perceive complex environments and adapt their be- havior accordingly. These innovations have significantly improved motion planning, environmental awareness, and overall driving performance. However, accurate and robust path tracking remains a critical challenge, particularly in dynamic or uncertain scenarios. This work focuses on the design and evaluation of path tracking strategies based on different linear controllers. In particular, the study explores how they can be effectively integrated with different vehicle actuation mechanisms, such as Four-Wheel Steering (4WS) and Torque Vectoring (TV), to enhance lateral and yaw control during path following. These actuation strategies offer additional degrees of freedom that can be leveraged to improve trajectory adherence, stability, and manoeuvrability, especially at higher speeds or under demanding conditions. Through simulation and experimental analysis, the proposed control frameworks have been fine tuned in order to guarantee a fair comparison and understand how, with these innovative technologies it is possible to increase the level of precision of the path tracking strategies.