Work

A fault adaptive LPV shared control for driver assistance using advanced fault estimators

Year: 2026

Type: article

Abstract: • Estimating driver performance from steering behavior. • Observer-based methods for dedicating and reconstructing time-varying driver faults. • Adaptive shared control scheduled by real-time driver performance monitoring • Improving Lane keeping through linear parameter-varying control function of vehicle speed and driver performance. • Simulations and experiments results validate the proposed shared-control strategy. This paper introduces a fault-adaptive shared control approach for driver assistance in semi-automated vehicles. The difference between an ideal and an actual driver is estimated using two methods: a descriptor H ∞ filter and a cascaded Luenberger observer with a linear filter. Unlike related works, the proposed estimation strategies accurately reconstruct the time-varying deviations, considered as a fault, without using restrictive assumptions. The estimated driver deviation is then used in a linear parameter-varying controller scheduled by longitudinal velocity and driver performance, improving steering assistance and overall tracking accuracy. The proposed methods are validated using simulations and in an experimental scaled platform.

Source: Control Engineering Practice

DOI: 10.1016/j.conengprac.2026.106963

Authors: Lama Hammoud, Nacim Meslem, Olivier Sename

Institutions: Institut polytechnique de Grenoble, Centre National de la Recherche Scientifique, GIPSA-Lab

Language: English

Topic: Vehicle Dynamics and Control Systems

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,010

Funder: Agence Nationale de la Recherche