山东大学学报 (工学版) ›› 2023, Vol. 53 ›› Issue (4): 30-36.doi: 10.6040/j.issn.1672-3961.0.2022.139
• 交通工程——智慧交通专题 • 上一篇
周勇1,兰晓伟2,吕斌2*,栗剑1
ZHOU Yong1, LAN Xiaowei2, LÜ Bin2*, LI Jian1
摘要： 为提高恶劣天气下路侧激光雷达的感知能力,提出一种基于路侧激光雷达的雪天点云降噪算法。去除空间中的静态冗余数据,根据噪声点分布划分不同强度的反射区域;对不同类型的噪声点采用条件滤波、统计滤波、半径滤波的方式,滤除数据中的雪花噪声;通过全卷积神经网络在降噪后的数据上进行目标检测,采用多项指标评估降噪效果。试验结果表明,采用本研究提出的叠加滤波算法可大幅减少噪声点数量,在有效检测范围内,目标检测的准确率达到98.2%,误检率降低至17.8%。该算法可提高雪天点云的数据质量,对智能车路协同系统的建设具有一定的指导意义和实践价值。
中图分类号:
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