Robust Lane Detection and Tracking Algorithm for Steering Assist Systems

Machines

Costin-Anton Boiangiu¹  Mihail-Alexandru Andrei¹  Mihai-Lucian Voncilă¹  Nicolae Tarbă¹ 

[1] Computer Science and Engineering Department, Faculty of Automatic Control and Computers, Politehnica University of Bucharest, 060042 Bucharest, Romania;

关键词: computer vision;    steering assist systems;    lane detection;    autonomous driving;    Hough transform;   

DOI  :  10.3390/machines10010010

来源: DOAJ

【 摘 要 】

Modern vehicles rely on a multitude of sensors and cameras to both understand the environment around them and assist the driver in different situations. Lane detection is an overall process as it can be used in safety systems such as the lane departure warning system (LDWS). Lane detection may be used in steering assist systems, especially useful at night in the absence of light sources. Although developing such a system can be done simply by using global positioning system (GPS) maps, it is dependent on an internet connection or GPS signal, elements that may be absent in some locations. Because of this, such systems should also rely on computer vision algorithms. In this paper, we improve upon an existing lane detection method, by changing two distinct features, which in turn leads to better optimization and false lane marker rejection. We propose using a probabilistic Hough transform, instead of a regular one, as well as using a parallelogram region of interest (ROI), instead of a trapezoidal one. By using these two methods we obtain an increase in overall runtime of approximately 30%, as well as an increase in accuracy of up to 3%, compared to the original method.

【 授权许可】

Unknown