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In order to extract the lane line information of the driverless car, a fast lane line recognition algorithm using the optical flow method is proposed. First, using the temporal correlation between successive video frames, the optical flow method is used to detect the relative movement of the background in front of the vehicle. Then, using the moving direction and distance of the feature points in the background of the vehicle, the position of the lane line in the frame image is roughly positioned, thereby reducing the detection area of the lane line in the frame image and accelerating the lane line recognition algorithm. Finally, the lane line type is analyzed by processing the suspected lane line pixels. The improved algorithm improves the efficiency of the lane detection algorithm and solves the problem of high time complexity of the original multi-operator lane detection algorithm. At 720*480 pixels, the processing speed of 13.5 Hz is realized, which is 39.6% faster than the processing algorithm using only the composite operator, and the algorithm detection effect is good. The real vehicle experiment proves the effectiveness and real-time of the algorithm.