Abstract:Base on the rapid development of intelligent transportation, this work studies lane departure detection and vehicle forward safety distance detection technology under high-speed section based on the machine vision. First fix the car camera, obtain the camera's internal and external parameters through camera calibration, and then design the distance detection model which can not only detect the distance between the front vehicle and the unmanned vehicle, but also calculate the deflection angle of the front vehicle relative to the optical axis of the camera. Secondly, based on the CCP (The Car's Current Position) deviation detection algorithm, the safety and alarm zones are set to establish lane departure models, and the algorithm judges whether the current vehicle is deviated or not. Finally, the algorithm is transplanted to the embedded platform DSP-DM3730 by TI's DVSDK(Digital Video SDK). Experiments show that the vehicle distance detection model and lane departure model designed in this work have good reference value in solving the problems of forward collision detection and lane departure detection of unmanned vehicles.