The invention discloses a system for real-time identifying urban traffic lights based on single eye vision and a GPS integrated navigation system. The system establishes a map of traffic lights in an off-line manner through the methods of interactive image annotation, camera calibration, 3D position recovery, etc., and provides position coordinates and semantic attributes of the traffic lights under the globally positioned GPS coordinate system. Upon online detection, with the established offline map of traffic lights as a prior, an area of interest is determined by solving the substantial scope of the traffic lights in images in combination with the pose position, and the identification of the color segmentation and shapes of the traffic lights are carried out by using form information of the traffic lights in the area of interest. The system is applicable to road conditions and scenarios of different kinds, implements stable and long-distance detection sensing of the traffic lights under various environments. Since the system adopts a low-cost and low-power consumption navigation device, an image acquisition device and a computer platform, the system can be widely applied to the fields of vision navigation of driverless vehicles, vision auxiliary driving of intelligent vehicles, etc.