AbstractDriving safely can be ensured by a better understanding of the risk and critical situations. This can be achieved by a good knowledge of road attributes and vehicle dynamic behaviors. This paper proposes two algorithms: the first one is dedicated to a new estimation process which was designed to estimate the vehicle roll and road bank angles, in order to make the road trajectory more realistic. This estimator is based on an unknown input sliding mode observer and a LPV model. The second concerns a robust LPV state output feedback control designed via LMI optimization and gain-scheduling method. The steering control strategy is designed to simulate the non linear four wheel vehicle model under higher dynamic demands. The steering vehicle control and the observer developed here have been validated experimentally using the data acquired on the laboratory vehicle Peugeot 307 developed by INRETS-MA. These algorithms were developed for an application known as “Itinerary Rupture Diagnosis”: to evaluate the physical limits of a vehicle negotiating a bend.