Research On Lane Departure Warning System On The Highway

This dissertation concentrates on the lane departure warning system on the highway, which includes lane detection, vehicle trajectory prediction, TLC (Time to Lane Crossing) computing and lane departure judgement. A lane departure warning system has also been developed and tested on the HONGQI prototype.A new lane detection method has been proposed first. On the basis of the inverse perspective mapping (IPM) model, the method removed the perspective effect from the monocular image and get the structural constraint information including the parallelism and fixed-width constraint of the highway. With these constraint information, the dominant slope can be detected by means of Hough Transformation, then the position of the start-points of lane markings is found. From the start-points, The lane markings can be tracked piece by piece. Finally, lanes are presented by fitted curves.A novel time series prediction based on auto-regression (AR) model has been proposed to predict the vehicle trajectory in the future. In this method, the rank of AR model is focused. The validation of this method has been proved by the experimental results under different situations.An entire lane departure warning system based on TLC is developed. This system has been tested on HONGQI Autonomous Land Vehicle. Experiments on vehicle's running on the straight road, curved road and changing lane show that the performance of this system is satisfactory.