Road vanishing point detection is an important part of blind zone monitoring in advanced driver assistance systems. In view of the problems of low accuracy and large computation of existing vanishing point detection methods, a road vanishing point detection algorithm based on in-vehicle video images is proposed. The algorithm detects the image feature points based on Harris corner point detection by optimizing the score function to reduce the amount of operations in the tracking stage; tracks the motion feature points by the pyramid optical flow method and frame difference distance, and accurately obtains the position of each feature point on the end frame; after removing the outlying points from the feature points, the K-Means clustering algorithm that optimizes the initial clustering center is used to obtain the road vanishing point of the in-vehicle video image. Finally, the algorithm is applied to various vehicle driving scenes for testing, and it can accurately detect the road vanishing points in the in-vehicle video images within a short running time, which proves that the algorithm is robust, simple and easy to implement.