基于道路特征的车道线识别算法分析及平台搭建

Analysis and Construction of Lane Recognition Algorithm Based on Road Features

基于当前智能驾驶背景下道路特征模型的车道线识别现状,对应用于智能汽车的图像预处理中的灰度化处理算法、滤波处理算法和感兴趣区域提取技术分别进行对比分析,研究不同的图像预处理方法在车道线识别算法的应用适用性。对车道线实时提取算法中的边缘检测技术原理、道路特征条件转化算法进行综合运用分析,搭建基于道路特征的车道线识别算法模型,经过在Visual Studio平台验证,算法模型满足智能驾驶汽车车道线识别要求。

Based on the current status of lane recognition based on road feature model under the background of intelligent driving,the gray processing algorithm,filtering processing algorithm,and region of interest extraction technology in image preprocessing for intelligent vehicles are compared and analyzed respectively,and the applicability of different image preprocessing methods in lane recognition algorithm is studied.The principle of edge detection technology and the conversion algorithm of road feature conditions in the real-time lane extraction algorithm are comprehensively used and analyzed.The lane recognition algorithm model based on road features is built.After verification on the Visual Studio,the algorithm model meets the lane recognition requirements of intelligent driving vehicles.