Research on Lane Detection and Tracking Algorithm Based on Improved Hough Transform

The driverless technology has developed rapidly in recent years. Unmanned vehicles need to learn to observe the road from the visual point of view if they want to achieve automatic driving, which specifically is the detection of lane lines. This includes identifying the positional relationship between the lane line and the car, whether it is a solid line or a dotted line. The detection of lanes is an important part of the vehicle-aided driving system. In view of this feature, this paper proposes the use of improved Hough transform to achieve straight-track detection of lane detection, while for the detection of curved sections, the tracking algorithm is studied. By controlling the slope of the lane lines in the two frames before and after comparison, a limitation is made near the previously detected lane line area, ie, a region of interest (ROI) is set, and a search for a corner pixel is performed in the direction, for the corner portion Rebuild. The experimental results show that the algorithm has the characteristics of fast operation speed, high accuracy and good robustness.