A driver support system should provide assistance and security to the driver. For navigaton tasks it is neccessary to determine position of the ego vehicle relative to the road. One of the principal approaches is to detect road boundaries and lanes using a vision system in the vehicle. Within the European research project 'Secure Propulsion using Advanced Redundant Control (SPARC)' different approaches of lane detection are developed to meet the needs of real traffic situations. The vision module presented here is based on several image filters that provide diverse information about the environment. A set of hypotheses about the state of the system is generated by a probabilistic particle filter. Assuming a predefined model of the road the particles are tested according to image filters to infere the best belief vehicle position. Emphasis was placed on extracting relevant information from the scene and efficient testing. In particular, a new testing module based on Canny edge filter and Hough transform increased the accuracy and robustness of estimation. Perfomance of the vision module was tested under various real-road conditions.
A lane detection vision module for driver assistance
Bildmodul zur Fahrbahnerkennung für die Fahrerassistenz
MechRob, Mechatronics and Robotics, 2004 ; 913-918
2004
6 Seiten, 21 Bilder, 13 Quellen
Aufsatz (Konferenz)
Englisch
Vision-Based Lane Detection for Advanced Driver Assistance Systems
Springer Verlag | 2020
|Computer Vision Based Driver Assistance Drowsiness Detection
Springer Verlag | 2021
|Performance Evaluation of a Vision Based Lane Tracker Designed for Driver Assistance Systems
British Library Conference Proceedings | 2005
|Lane Departure Identification for Advanced Driver Assistance
Online Contents | 2015
|