Real time Detection of Lane Markers in Urban Streets
This addresses the problem of real-time lane detection for autonomous driving systems, though it appears incremental with a focus on speed and robustness.
The paper tackles lane marker detection in urban streets by introducing a fast RANSAC algorithm for Bezier spline fitting, achieving real-time operation at 50 Hz with results comparable to prior methods.
We present a robust and real time approach to lane marker detection in urban streets. It is based on generating a top view of the road, filtering using selective oriented Gaussian filters, using RANSAC line fitting to give initial guesses to a new and fast RANSAC algorithm for fitting Bezier Splines, which is then followed by a post-processing step. Our algorithm can detect all lanes in still images of the street in various conditions, while operating at a rate of 50 Hz and achieving comparable results to previous techniques.