Adaptative Road Lanes Detection and Classification

Abstract. This paper presents a Road Detection and Classification algorithm for Driver Assistance Systems (DAS), which tracks several road lanes and identifies the type of lane boundaries. The algorithm uses an edge filter to extract the longitudinal road markings to which a straight lane model is fitted. Next, the type of right and left lane boundaries (continuous, broken or merge line) is identified using a Fourier analysis. Adjacent lanes are searched when broken or merge lines are detected. Although the knowledge of the line type is essential for a robust DAS, it has been seldom considered in previous works. This knowledge helps to guide the search for other lanes, and it is the basis to identify the type of road (one-way, two-way or freeway), as well as to tell the difference between allowed and forbidden maneuvers, such as crossing a continuous line.

• Type: Conference
• Year: 2006
• Where: ACIVS
• Authors: Juan Manuel Collado, Cristina Hilario, Arturo de la Escalera, Jose M. Armingol
• Keywords: ACIVS 2006, Computer Vision, Lane Boundaries, Longitudinal Road Markings, Straight Lane Model