A Lane Detection Method Based on the Double Straight-line Model

Aiming at improving the accuracy of traditional way of using monocular vision to identify the running lane ,a new method of lane detection based on the double straight line model is proposed .According to the characteristics of highways ,the method firstly builds a double straight line model ,and extracts straight lines by Hough Transformation , then detect the vanishing point of parallel lines by an improved Hough Transformation ,and finally extracts current traffic lanes through vanishing point and prior information from an image .An experiment is conducted based on 150 road images from different road sections ,with different illumination levels and different vehicle interferences .It is found out from the study results that the extraction accuracy is 88 .6% and the average detection time is 0 .24 seconds .Experimental results show that the proposed method can detect highway lanes with a good accuracy and it is also good at adapting to different illumination levels ,reducing the impact of vehicle disturbance and processing data in real-time .