An integrated, robust approach to lane marking detection and lane tracking

Abstract

Lane Detection is a difficult problem because of the varying road conditions that one can encounter while driving. We propose a method for lane detection using steerable filters. Steerable filters provide robustness to lighting changes and shadows and perform well in picking out both circular reflector road markings as well as painted line road markings. The filter results are then processed to eliminate outliers based on the expected road geometry and used to update a road and vehicular model along with data taken internally from the vehicles. Results are shown for a 9000-frame image sequence that include varying lane markings, lighting conditions, showing, and occlusion by other vehicles.