VICTOR, Stéphane; RECEVEUR, Jean-Baptiste; MELCHIOR, Pierre; LANUSSE, Patrick

doi:10.1109/TITS.2020.3045917

Métadonnées

Afficher la notice complète

Licence d’utilisation du document

VICTOR, Stéphane

Laboratoire de l'intégration, du matériau au système [IMS]

RECEVEUR, Jean-Baptiste
Laboratoire de l'intégration, du matériau au système [IMS]

MELCHIOR, Pierre
Laboratoire de l'intégration, du matériau au système [IMS]

Langue

Article de revue

Ce document a été publié dans

IEEE Transactions on Intelligent Transportation Systems. 2022-05, vol. 23, n° 5, p. 1-14

Résumé en anglais

This article deals with the issue of tracking a reference optimal trajectory for an autonomous nonlinear vehicle model by designing both lateral and longitudinal robust feedback control and a suited feedforward control. In previous works, a strategy based on a human-driver field of view was used to plan an optimal trajectory reference. The optimization has been made using a Genetic Algorithm (GA), and the obtained trajectory has been injected into a Potential Field (PF) so as to be reactive to unforeseen events by using a point mass model. Here, the previously developed GA-PF planification process is integrated in a new complete global planning and tracking method and applied to a validation nonlinear vehicle model. This control tracking method is developed in two strategies: a bicycle model is used as model inversion for feedforward design and a robust control is designed as feedback control in order to take the vehicle (mass and velocity) and road (slope and adherence) parameter variations into account. A lateral nonlinear control and a longitudinal robust control are designed. Realistic autonomous car simulation results are provided on an overtaking scenario and a round-about scenario.< Réduire

Mots clés en anglais

Autonomous vehicles

trajectory planning

trajectory tracking

optimization

bicycle model

model inversion

robust control

Métadonnées

Partager cette publication !

Licence d’utilisation du document

Optimal Trajectory Planning and Robust Tracking Using Vehicle Model Inversion

Langue

Ce document a été publié dans

Résumé en anglais

Mots clés en anglais

URI

DOI

Unités de recherche