I. Introduction
The electronic systems of modern vehicles are becoming more and more complex with an increase of complexity and the number of electronic control units (ECUs). Modern cars may count tens of ECUs, while embedded software in ECUs continues to increase in length, complexity, and sophistication [1]. In fact, various electrical systems and subsystems have been recently introduced in automobiles, and more will be in the near future. In particular, one of them regards the security of the vehicle, an aspect that has become even more important nowadays with the progressive increase of the vehicle autonomy degree. Modern vehicles already include many sensors and actuators to achieve high performances. The enhancement of security, comfort, passenger confidence during hazardous situations, and performance can be obtained with various subsystems. One of them is the active front steering (AFS), which consists of imposing an additional angle to the front tires. Another one is the rear torque vectoring (RTV), which imposes a yaw torque to the vehicle [2]–[13]. This technical development goes hand in hand with the increase in the complexity of the control algorithms implemented on the ECUs that are necessary to control these subsystems. Such microprocessors constitute a software solution to the implementation of a controller. They ensure low cost, design flexibility, and the ability to implement complex algorithms. However, such software solutions also present some limitations, due to its fixed internal architecture, which leads to a full serialization of the data treatment. The more complex is the control algorithm, the longer is the control algorithm execution time. This, in turn, constitutes a lower bound for the sampling time that can be used in the specific application. Clearly, longer sampling times determine worse controller performances. On the other hand, the complexity of the control algorithms of the various subsystems has sensibly increased in order to face more challenging performances.