In order to improve the safety of driving under different visibility meteorological conditions on the expressway, this paper analyses the composition and operation principle of the expressway lane departure warning and navigation system based on machine vision. And an effective lane mark identification algorithm suiting for different visibility situations is proposed. Firstly the image contrast between the expressway lane and its background is increased by using histogram equalization technology, improving detecting range of lanes and accuracy. Secondly the edges in the lane directions are detected by utilizing specific Sobel operator. In order to suit for different visibility situations and improve detecting efficiency, the method of maximum classes square error is applied to threshold segmentation. Finally, lane is abstracted according to expressway lane features after image Hough transform. Based on lanes identification, this paper designs a navigation algorithm of driving direction. This algorithm performs driving direction navigation decisions according to two characteristic parameters which are deviation angle and deviation distance. The experimental results indicate that the developed system exhibits good detection performances in recognition reliability and navigation decision. It has proved that this system has high accuracy, large detection range and high practicability.