Real-Time Lane Detection and Tracking for Advanced Driver Assistance Systems

• Published in: Chinese Control Conference pp. 6772 - 6777
• Main Authors: Bilal, Hazrat, Yin, Baoqun, Khan, Jawad, Wang, Luyang, Zhang, Jing, Kumar, Aakash
• Format: Conference Proceeding
• Language: English
• Published: Technical Committee on Control Theory, Chinese Association of Automation 01.07.2019
• Subjects: Advanced Driver Assistance System (ADAS); Edge Detection; Filtering algorithms; Fuzzy Noise Reduction Filter (FNPF); Hough Transform; Image color analysis; Image edge detection; Image sequences; Lane Detection; Low pass filters; Noise reduction; Transforms
• ISSN: 1934-1768
• DOI: 10.23919/ChiCC.2019.8866334

Due to the fast-growing industry of intelligent vehicles the advanced driver assistance system (ADAS) has engrossed a lot of attention of the scholars. One of the biggest hurdles for new autonomous vehicles is to detect curvy lanes, multiple lanes, and lanes with a lot of discontinuity and noise. The purpose of this paper is to analyze the possibilities of image processing techniques for a computer vision application focusing on the problem of lane detection to enable traffic safety and driving comfort. The proposed algorithm is a combination of two sub-algorithms. The first sub-algorithm called Fuzzy Noise Reduction Filter (FNPF); removes the noise and smoothen the sequences of images received by the camera. While the second sub-algorithm aims to detect lane in normal as well as challenging scenarios by applying the concept of Hough Transform (HT) with a capable region of interest. The novelty of the proposed research study is the tracking of the lanes under inclement weather and challenging lightening conditions with improved computational time. The result achieved through our proposed algorithm is satisfactory in video sequences captured on several road types and under very challenging lighting and weather conditions.