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Aiming at the occlusion problem in the trajectory tracking control of moving vehicles, this paper innovatively proposes a SVM classification detector optimized stable tracking algorithm to ensure that the target can be re searched and located when the target exits the occlusion; at the same time, the color histogram and hog algorithm are improved to improve the efficiency of feature extraction; finally, vot2016 international standard sequence set is selected to optimize the sta Ple tracking algorithm is verified. The results show that the improved cascade algorithm can capture the target position more quickly after the target exits the occlusion; the tracking accuracy of the improved algorithm for the target center reaches 0.81, and the tracking accuracy of the target frame reaches 0.89; when the target enters the occlusion state, the improved algorithm has the highest tracking accuracy. The stable optimization algorithm proposed in this study shows good tracking effect, and its tracking ability in the face of long-term occlusion has high application value.