基于LiDAR的城市三维铁路区域提取用于改进火车碰撞警告
Tuo Shen1,2, Jinhuang Zhou2, Tengfei Yuan3
1School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Sensors (Basel, Switzerland)
|August 10, 2024
概括
城市轨道交通中的障碍物检测通过基于LiDAR的新方法得到了改进. 这种方法在较长距离上准确地提取轨道区域,通过识别潜在的轨道入侵来提高安全性.
科学领域:
- 城市轨道交通安全城市轨道交通安全.
- 基于LiDAR的障碍物检测系统可以检测障碍物.
背景情况:
- 物体侵入轨道区域对城市铁路运输构成重大安全风险.
- 目前基于LiDAR的障碍物检测方法在稀疏的数据上扎,将轨道区域细分限制在短距离上.
研究的目的:
- 从LiDAR数据中开发一种用于精确和远程轨道区域提取的新方法.
- 克服现有方法的局限性,为城市铁路安全划分轨道区域.
主要方法:
- 通过检测平行参考结构 (例如墙壁) 来间接提取轨道区域.
- 使用参考点选择和曲线拟合生成轨道参考曲线.
- 推断一个中心线,将其扩展到一个2D区域,并通过地面检测和点过获取3D区域.
主要成果:
- 与传统算法相比,拟议的技术成功地从LiDAR数据中提取了与传统算法相比更长距离的轨道区域.
- 在各种城市铁路环境中展示了有效的性能,包括道,高架段和平面轨道.
结论:
- 开发的方法为城市铁路运输中远程轨道面积提取提供了强大的解决方案.
- 这一进步对于提高障碍物检测和避免碰撞系统的可靠性至关重要.
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