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

Type de document

COMMUNICATION AVEC ACTES INTERNATIONAL (ACTI)

Langue

anglais

Auteur

LEITAO ; TILIE ; MANGEAS ; TAREL ; VIGNERON ; LELANDAIS

Résumé / Abstract

We propose a detection and classification system for various road situations, which is robust to light changes and different road markings. The road curves in an image are described with a Hough Transform, where histograms accumulate the contrast lines for each pixel. The resulting 2D histograms are used to train a Kohonen Neural Network. The final output classification can be used to improve road security, indicating dangerous situations to the driver or feeding a driving control system.