Recent progress in road and lane detection: a survey

• Published in: Machine vision and applications Vol. 25; no. 3; pp. 727 - 745
• Main Authors: Bar Hillel, Aharon, Lerner, Ronen, Levi, Dan, Raz, Guy
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2014; Springer Nature B.V
• Subjects: Advanced driver assistance systems; Blocking; Breaking down; Communications Engineering; Computer Science; Gaps; Image Processing and Computer Vision; Inspection; Lanes; Networks; Pattern Recognition; Perception; Roads; Special Issue Paper; Tasks; Vision systems; Road detection; Road segmentation; Lane detection; Advanced driver assistance systems
• ISSN: 0932-8092; 1432-1769
• DOI: 10.1007/s00138-011-0404-2

The problem of road or lane perception is a crucial enabler for advanced driver assistance systems. As such, it has been an active field of research for the past two decades with considerable progress made in the past few years. The problem was confronted under various scenarios, with different task definitions, leading to usage of diverse sensing modalities and approaches. In this paper we survey the approaches and the algorithmic techniques devised for the various modalities over the last 5 years. We present a generic break down of the problem into its functional building blocks and elaborate the wide range of proposed methods within this scheme. For each functional block, we describe the possible implementations suggested and analyze their underlying assumptions. While impressive advancements were demonstrated at limited scenarios, inspection into the needs of next generation systems reveals significant gaps. We identify these gaps and suggest research directions that may bridge them.