摘要
针对现有车道线检测技术依赖霍夫检测导致的速率过慢问题,提出了一种基于平行坐标系的车道线检测算法。基于平行坐标系将直线可视化,并对其检测速率加以对比和分析。结果表明,在仿真环境下基于平行坐标系的车道线检测算法,其准确性与霍夫检测相仿,且速率有很大的提升。
A lane detection algorithm based on parallel coordinate system is proposed to solve the problem of slow detection rate caused by the Hough detection. The lane is visualized based on the parallel coordinate system and its detection rate are compared and analyzed. In the simulation environment, the results show that the accuracy of lane detection algorithm based on parallel coordinates is similar to that of the Hoough detection, and the speed is greatly improved.
作者
王旭宸
卢欣辰
张恒胜
肖亚敏
解梅
WANG Xu-chen;LU Xin-chen;ZHANG Heng-sheng;XIAO Ya-min;and XIE Mei(School of Information and Communication Engineering, University of Electronic Science and Technology of China Chengdu 611731)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2018年第3期362-367,共6页
Journal of University of Electronic Science and Technology of China
基金
教育部高等学校博士学科点专项科研基金(20130185130001)
关键词
人工智能
无人驾驶车
HOUGH变换
道线检测
平行坐标系
artificial intelligence
autonomous driving
Hough transform
lane detection
parallel coordinate system
