In this paper, we consider the design of a multi-objective lateral controller for highly automated vehicles. Higher levels of automation require vehicles to resolve complex situations and orchestrate the underlying vehicle controllers such that in the event of a conflicting situation, the car is able to make the appropriate decision on which controller/objective to prioritize. We formulate the problem as hybrid switched system where event-triggered decision-making algorithms can be considered together with the lower-level dynamics and control-related objectives. To this end, a model regulator-based yaw rate controller and a path following controller are orchestrated through hybrid model predictive control (HMPC). We demonstrate the validity and robustness of the presented method through simulations where the automated vehicle is subjected to various scenarios with conflicting objectives and operating conditions. We show that robustness against model uncertainty is achieved by the yaw dynamic regulator and we also demonstrate that the hybrid controller orchestrates the switched modes provided by the regulator to achieve path tracking under conflicting objectives.