Real time lane detection for autonomous vehicles

• Published in: 2008 International Conference on Computer and Communication Engineering pp. 82 - 88
• Main Authors: Assidiq, A.A.M., Khalifa, O.O., Islam, R., Khan, S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2008
• Subjects: Cameras; computer vision; Driver Assistance System; intelligent vehicles; Lane detection; Machine vision; Mobile robots; Remotely operated vehicles; Road accidents; Road safety; Road vehicles; Robustness; Testing; Vehicle detection
• ISBN: 9781424416912; 1424416914
• DOI: 10.1109/ICCCE.2008.4580573

An increasing safety and reducing road accidents, thereby saving lives are one of great interest in the context of Advanced Driver Assistance Systems. Apparently, among the complex and challenging tasks of future road vehicles is road lane detection or road boundaries detection. It is based on lane detection (which includes the localization of the road, the determination of the relative position between vehicle and road, and the analysis of the vehiclepsilas heading direction). One of the principal approaches to detect road boundaries and lanes using vision system on the vehicle. However, lane detection is a difficult problem because of the varying road conditions that one can encounter while driving. In this paper, a vision-based lane detection approach capable of reaching real time operation with robustness to lighting change and shadows is presented. The system acquires the front view using a camera mounted on the vehicle then applying few processes in order to detect the lanes. Using a pair of hyperbolas which are fitting to the edges of the lane, those lanes are extracted using Hough transform. The proposed lane detection system can be applied on both painted and unpainted road as well as curved and straight road in different weather conditions. This approach was tested and the experimental results show that the proposed scheme was robust and fast enough for real time requirements. Eventually, a critical overview of the methods were discussed, their potential for future deployment were assist.