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Sensor occluded scenes is one of the main causes of intelligent vehicle traffic accidents. In order to reduce the impact of sensor occluded scenes on active safety performance of intelligent cars, the control of intelligent car active braking system under sensor occluded scenes conditions was studied. Firstly, a database and a convolution neural network were specially established to recognize sensor occluded scenes. Secondly, different types of sensor occluded scenes were classified according to their motion characteristics. Then, a safe distance model under the condition of sensor occluded scenes was established. Finally, based on the abovementioned safe distance model, the speed of potential obstacles in sensor occluded scenes were controlled to achieve the purpose of active collision avoidance. According to simulation test and real vehicle test, the sensor occluded scenes classification proposed can better express the motion characteristics of potential obstacles in sensor occluded scenes. The active collision avoidance safety distance model under sensor occluded scenes conditions had good preventive effects on potential obstacles, and the active safety performance of intelligent vehicle in sensor occluded scenes was improved. 