基于DSP的车道偏离检测与车辆前向车距检测

基于智能交通的快速发展，研究了在高速路段下基于机器视觉的车道偏离检测与车辆前向安全车距检测技术.首先固定车载相机，通过相机标定获取相机的内参数和外参数，进而设计车距检测模型.该模型不但能够检测出前方车辆与无人车的距离，还能计算出前方车辆相对于摄像机光轴的偏转角度.接着在CCP偏离检测算法的基础上，设定安全和报警区来建立车道偏离模型，并对当前车辆的偏离结果作出正常行驶的评判.最后借助TI的DVSDK组件包将算法移植到嵌入式平台DSP-DM3730上测试.实验表明，本文设计的车距检测模型和车道偏离模型在解决无人车的前向防撞检测和车道偏离检测等问题上具有较好的参考价值.

Lane Departure Detection and Vehicle Forward Distance Detection Based on DSP

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.