基于点云数据的驾驶可见度指数,用于评估城市道路驾驶安全,以点云数据为基础
Zhirong Zhang1, Yuan Yuan1, Hailan Huang1
1School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China.
Accident; analysis and prevention
|February 28, 2026
概括
本研究引入了一种使用LiDAR数据测量3D驾驶可见度的新方法,为道路安全评估创建了驾驶可见度指数 (DVI). DVI量化了可见空间,揭示了义大道上不理想的安全条件.
科学领域:
- 运输工程 运输工程
- 地理空间分析的研究.
- 计算机视觉 计算机视觉
背景情况:
- 道路交通安全对于预防事故和支持社会经济发展至关重要.
- 目前的安全评估依赖于历史数据和道路设计,但缺乏直接可见度指标.
- 驾驶可见性是影响驾驶员感知和道路安全的一个关键因素.
研究的目的:
- 开发一种使用LiDAR点云数据量化3D驾驶可见度的新方法.
- 引入驾驶可见度指数 (DVI) 以客观,基于可见度的道路安全评估.
- 建立一个计算框架来评估驾驶员的3D可见空间.
主要方法:
- 来自LiDAR的道路点云数据的获取和预处理.
- 从驾驶员的角度计算3D驾驶可见性场.
- 开发和应用驾驶可见度指数 (DVI) 用于安全评估.
主要成果:
- 拟议的方法成功量化了3D可见空间,并生成了驾驶安全地图.
- 宜大道的驾驶可见度指数 (DVI) 范围在0.2到0.6之间,表明安全性不足.
- 对比分析证实了拟议方法与现场数据的稳定性和准确性.
结论:
- 这种新的方法为交通管理提供了3D可见空间的客观和直观量化.
- 驾驶可见度指数 (DVI) 为道路设计,交通设施布局和智能交通系统提供了新的基础.
- 这种方法通过结合关键的驾驶可见性因素来加强道路交通安全评估.
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