Traffic signal detection and recognition is an important research content in the field of manless-driving and driving-assist system. And the system can avoid traffic accident in intersection

improve the security of driving.However

exist various complicated natural scene factors increase the difficulty of recognition algorithm. The proposed alogrithm realizes traffic light detection and identification based on Faster-RCNN. Acquire traffic scene data and annotate

fill the blank of traffic lights public datasets. By experimental comparision

the optimal feature extraction network is chosed

the effectiveness of the method is verified on experimental platform of intelligent vehicle.