车载LiDAR-摄像机部署优化用于路面标记,应急融合检测和路面标记
Ciyun Lin1,2, Wenjian Sun1, Ganghao Sun1
1Department of Traffic Information and Control Engineering, Jilin University, Changchun 130022, China.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
本研究介绍了一种优化的车载传感器部署,用于检测路面标记处于危险状态. 该方法通过提高在阴影和变光等具有挑战性的条件下检测准确度来提高交通安全.
科学领域:
- 道路安全工程工程 道路安全工程
- 传感器融合技术传感器融合技术
- 交通运输中的人工智能
背景情况:
- 路面标记对于交通指导和安全至关重要,但随着时间的推移而退化.
- 定期检查反射和扩散照明对于维持安全标准至关重要.
- 现有的检测方法难以应对复杂的交通条件,如阴影和不断变化的光线.
研究的目的:
- 提出一个优化的车载传感器部署方法,用于路面标记应急检测.
- 提高路面标记检查系统的准确性和稳定性.
- 调整检测能力以适应动态的环境和交通条件.
主要方法:
- 评估了光检测和射程 (LiDAR) 和摄像头传感器的检测能力.
- 在数学上制定了LiDAR摄像机部署优化问题,用于应急融合检测.
- 开发了一个改进的红狐优化 (RFO) 算法,并增强了解决部署问题的机制.
主要成果:
- 在路面标记 (0.58米) 上,每个数据的密度为5217个LiDAR点.
- 在计算测量和现场测试测量之间,相对误差低于7%.
- 在现实场景中验证了该方法的稳定性,减轻了环境干扰.
结论:
- 拟议的传感器部署优化方法有效地检测了路面标记应急情况.
- 该系统表现出高精度和稳定性,即使在具有挑战性的环境条件下.
- 这种方法通过可靠的路面标记检查,有助于提高道路安全.
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