LANE BOUNDARY DETECTION IN DYNAMIC ENVIRONMENTS
DOI:
https://doi.org/10.59277/RRST-EE.2026.2.22Keywords:
Collision warning systems (CWS), Advanced driver assistance system (ADAS), Hough transform, TuSimple datasetAbstract
Lane detection is essential for collision warning systems. This technology helps vehicles maintain proper road position by identifying lane markings. This paper presents a method for lane detection within an ADAS using a monocular camera in real time. The approach uses the Hough Transform to detect lane lines in an image. The detected lines are filtered based on specific criteria, including angle, length, and symmetry relative to the image’s central axis, to select the best lines representing the lane boundaries. These techniques are crucial for improving the precision of driver assistance systems by ensuring reliable lane detection, even under varying conditions. Experiments were conducted in MATLAB using the publicly available TuSimple dataset, which contains diverse road scene images. The results indicate that the proposed method achieves precise lane-line detection, which is crucial for real-time monocular vision-based driver-assistance systems, thereby significantly enhancing road safety
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