基于无人机图像的道路标记危险检测和评估
Yunfan Nie1, Wangjie Wu2, Jinhuan Shan1
1School of Highway, Chang'an University, South 2nd Ring Road Middle Section, Xi'an 710064, China.
Materials (Basel, Switzerland)
|March 14, 2026
概括
本研究介绍了一种无人驾驶飞行器 (UAV) 框架,用于道路标志的检测和评估. 它通过有效评估车道标记状况和应急情况来提高自动驾驶的安全性.
科学领域:
- 土木工程 土木工程是指土木工程.
- 计算机视觉 计算机视觉
- 运输工程 运输工程
背景情况:
- 自动驾驶在很大程度上依赖于准确的车道标记感知.
- 道路标志因车辆负载而随着时间的推移而退化,影响安全.
- 现有的检查方法效率低下,缺乏准确性.
研究的目的:
- 开发使用无人机图像检测和评估道路标志的综合框架.
- 提高道路标记质量检查的效率和准确性.
- 为智能道路维护提供技术参考.
主要方法:
- 使用优化无人机飞行参数进行轻量级数据采集.
- 通过YOLOv8-MEB模型进行高效的标记提取,并进行实例细分和本地图像优化.
- 使用基于RANSAC的模板匹配和轮校正进行准确的应急评估.
主要成果:
- 车道分割精度和回忆率超过90%,FPS>60.
- 使用模板匹配和亲属转换恢复完整的标记形状.
- 对于不严重的损坏,在应急比率计算中大约有10%的错误.
结论:
- 拟议的基于无人机的框架为道路标志评估提供了一个低成本,灵活和安全的解决方案.
- 与传统方法相比,综合方法显著提高了检测和评估的准确性.
- 该框架为智能道路维护提供了实际的技术参考,并提高了驾驶安全.
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