Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux

Type de document

ARTICLE A COMITE DE LECTURE NON REPERTORIE DANS BDI (ACLN)

Langue

anglais

Auteur

SEBSADJI ; BENMANSOUR ; NDJENG NDJENG ; GLASER ; MAMMAR ; LABAYRADE ; GRUYER ; AUBERT

Résumé / Abstract

Driving safety enhancement could be achieved by better understanding of risky situations from the knowledge of vehicle dynamic state as well as the road geometry. Among the attributes of the road that have an impact on vehicle dynamics, we can find the bank and the slope angles, the road width and curvature Actually, these attributes cannot be measured by mean of low cost,onboard sensors. However, if one uses the available onboard sensors of the ABS and ESP systems, cameras and virtual sensors, it is possible to achieve a good estimation of these attributes. In this paper, three algorithms are developed for estimate these attributes and then to localize the vehicle. The road slope and bank angles are estimated using a combination of extended Kalman filter (EKF) and a Proportional Integral (PI) observer with unknown inputs. It is particularly assumed that the road curvature and width are estimated by video processing through a frontal monocular camera mounted behind the windscreen of the vehicle. The vehicle localization is performed at each time sample using an algorithm based on the IMM technique (Interacting Multiple Models) which uses the GPS, the inertial unit and ABS sensors. When it is associated to a simple Kalman filter, it allows to reconstruct the road 3D coordinates. Various tests on real measurements obtained with a prototype vehicle show the good behavior of the proposed estimation scheme.

Source

IEEE Transactions on Control System Technology, p1-31 p.

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