Title :
Fuzzy uncertain observer with unknown inputs for Lane departure detection
Author :
Dahmani, H. ; Chadli, M. ; Rabhi, A. ; Hajjaji, A.E.
Author_Institution :
“Lab. Modelisation, Inf. et Syst.”, UPJV, Amiens, France
fDate :
June 30 2010-July 2 2010
Abstract :
This paper presents a lane departure detection method. The road curvature is estimated and compared to the vehicle trajectory curvature. The proposed algorithm reduces false alarms and integrates the driver corrections by taking account of the steering dynamics. The used nonlinear model deduced from the vehicle lateral dynamics and a vision system is represented by a T-S fuzzy uncertain model with unknown inputs. Stability conditions of such observers are expressed in terms of linear matrix inequalities (LMI). Simulation results obtained in two various driving scenarios show the efficiency of the proposed method.
Keywords :
computer vision; fuzzy set theory; linear matrix inequalities; observers; position control; road vehicles; stability; steering systems; uncertain systems; vehicle dynamics; T-S fuzzy uncertain model; driver corrections; fuzzy uncertain observer; lane departure detection; linear matrix inequalities; nonlinear model; road curvature; stability; steering dynamics; vehicle lateral dynamics; vehicle trajectory curvature; vision system; Bicycles; Displacement measurement; Fuzzy control; Fuzzy systems; Machine vision; Nonlinear dynamical systems; Road accidents; Road safety; Road vehicles; Vehicle dynamics;
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-7426-4
DOI :
10.1109/ACC.2010.5530890