The monocular vision pedestrian detection can not obtain the depth information, so detection efficiency and accuracy are limited. Firstly, in the image preprocessing, the disparity information optimization analysis is proposed to simplify the expression of dynamic programming stixelworld in complex scenes based on stereo vision. Then, at the stage of pedestrian target detection, this paper analyzes the influence of the block scale on the detection effect in the traditional HOG feature, and obtains the multiHOG feature which is suitable for the road environment using the fisher criterion. The multiHOG feature is integrated with the LUV color channel feature. Finally, the hikSVM is used for pedestrian target classification. The experimental results show that the improved Stixelworld algorithm for image preprocessing greatly reduces the computation time and reduces the candidate region of pedestrian detection, target detection algorithm based on feature fusion and hikSVM has good realtime and robustness under the premise of guaranteeing the detection accuracy.