Title: Design of unknown inputs robust fuzzy observer for lane departure detection

Authors: Mohammed Chadli; Hamid Dahmani; H. Dahmani; M. Chadli; A. Rabhi; A. El Hajjaji

Addresses: 7 Rue Moulin Neuf 80000, Amiens, France ' 7 Rue Moulin Neuf 80000, Amiens, France ' University of Picardie Jules Verne, UPJV-MIS (EA 4290), 7 Rue Moulin Neuf, 80000 Amiens, France. ' University of Picardie Jules Verne, UPJV-MIS (EA 4290), 7 Rue Moulin Neuf, 80000 Amiens, France. ' University of Picardie Jules Verne, UPJV-MIS (EA 4290), 7 Rue Moulin Neuf, 80000 Amiens, France. ' University of Picardie Jules Verne, UPJV-MIS (EA 4290), 7 Rue Moulin Neuf, 80000 Amiens, France

Abstract: A lane departure detection method is proposed using Takagi-Sugeno (T-S) fuzzy approach in this paper. To deal with this problem, a nonlinear model deduced from a vehicle lateral dynamic and a vision system is represented by an uncertain T-S fuzzy model affected by unknown inputs. The developed lane departure detection technique is based on an unknown inputs fuzzy observer. Design conditions of such observers are expressed in terms of Linear Matrix Inequalities (LMI). Indeed, the road curvature considered as unknown input is estimated and compared to the vehicle trajectory curvature. The proposed algorithm allows to reduce false alarms and to integrate the driver corrections by taking the steering dynamics into account. In order to show the ef?ciency of the given method, simulations with different driving scenarios are proposed.

Keywords: vehicle dynamics; lane departure detection; T-S fuzzy model; T-S observer; unknown inputs; LMI; linear matrix inequalities; Takagi-Sugeno; robust fuzzy observers; nonlinear modelling; vehicle lateral dynamics; vision systems; road curvature; vehicle trajectory; steering dynamics; simulation.

DOI: 10.1504/IJVD.2011.043267

International Journal of Vehicle Design, 2011 Vol.56 No.1/2/3/4, pp.186 - 202

Received: 02 Nov 2009
Accepted: 19 Jun 2010
Published online: 10 Apr 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article