Accurate physical modeling of vehicle dynamics requires extensive a priori knowledge of the
studied vehicle. In contrast, data-driven modeling approaches require only a set of data that …

Obtaining accurate vehicle driving state and road adhesion coefficient information is of great
significance to many aspects of the vehicle. This paper takes distributed drive electric …

An accurate vehicle driving state observer is a necessary condition for a safe automotive
electronic control system. Vehicle driving state observer is challenged by unknown …

The paper deals with a robust autonomous path-following functionality, in which the safe
velocity and the motion profile of the vehicle with varying tyre-road contact must be …

Intelligent vehicle safety systems are based on the awareness of vehicle's dynamics states.
In this article, we propose the development of an onboarded software (called virtual sensor) …

In order to enhance the estimation accuracy of vehicle sideslip angle, a comprehensive
Strong Tracking Unscented Kalman Filter (STUKF) algorithm is herein proposed to estimate …

The paper presents an additive unscented Kalman filter (AUKF) based modular approach to
estimate lateral vehicle dynamics and tyre forces. In this approach, a simplified single-track …

Vehicle driving states in a dynamic vehicle model are with strong uncertainty and
nonlinearity. Simply applying traditional Unscented Kalman Filter (UKF) or Neural Network …

Background: The development of the tire/road friction coefficient measurement and
estimation system has far-reaching significance for the active electronic control safety …

Le travail abordé dans ces travaux de thèse se place dans le contexte de la conduite
autonome. Plus particulièrement, l'objectif est le développement d'une loi de commande …