This paper presents a Linear Parameter Varying (LPV) based approach to handle different steering scenarios for autonomous vehicles. The proposed methodology consists of the design of a fast and performant LPV/LFT controller which can track the generated yaw rate reference, for speed operating range, for lane tracking and smooth/fast lane changes. The handling of a dynamic maneuver is achieved by a Command Governor (CG), which feeds the updated LPV/LFT closed loop system with a "virtual" yaw rate reference. This virtual signal is the solution of an online receding horizon optimization problem, meeting simultaneously safety bounds for the steering of the vehicle. The efficiency of the suggested methodology is illustrated by simulation results for parameters of an automated Renault Zoe.