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高速公路分道线识别与重建 被引量:7

Recognition and Reconstruction for Highway Lane Line
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摘要 在智能交通系统中,自动驾驶系统是最难于实现的技术之一。许多学者努力想找到解决自动驾驶这一难题的方法。笔者介绍了一种新的思想和算法,它立足于单目视觉技术来实现高速公路的车道保持,在此基础上实现辅助导航。运用多阈值分割技术分割高速公路上当前车道的分道线,根据分道线几何投影约束跟踪提取完整的分道线,对分道线建立了圆锥曲线模型进行二维重建。本方法根据分道线模型获得保持车道所需要的车辆驾驶参数,通过这些参数实现了高速公路的车道保持。系统在四川和重庆的高速公路上以120km/h的速度进行了试验,圆满地完成了车道保持,辅助导航的任务。 In the intelligent transportation systems, maybe the automatic navigation system is the most difficult problem. Many researchers try to find a way to carry out cruise assistance. This paper describes some new thoughts and new algorithms for lane keeping with a single view. We use multi-threshold to extract the lane line. Then, geometry restriction is used to track the lane line. At last, the conic model to reconstruct lane line. We have tested the system with the algorithms on highway at 120 km/h in Sichuan province and Chongqing city in China. The result shows that the algorithms can work perfectly.
出处 《重庆大学学报(自然科学版)》 EI CAS CSCD 北大核心 2003年第8期52-55,67,共5页 Journal of Chongqing University
基金 国家自然科学基金资助项目(69674012)
关键词 单目视觉 多阈值分割 自组织聚类 HOUGH变换 圆锥曲线模型 自动驾驶系统 高速公路 分道线 monocular vision multi-threshold segmentation selforganizing data analysis hough translation conic model
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参考文献8

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