下一代碎石路剖面测量--先进无人机与路面测试仪和旋转式激光水平仪的潜力比较

Q1 Engineering
Dina Kuttah , Andreas Waldemarson
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引用次数: 0

摘要

在过去的几十年里,瑞典在有效收集路况数据方面取得了重大进展,并提出了新的方法。砂石路是瑞典连接城市和农村地区的重要道路,在道路网络中占很大比重。因此,本研究探讨了如何使用已开发的基于无人机 (UAV) 的数字成像系统,重点是有效收集砾石路表面状况数据。研究重点是使用三种不同的剖面测量方法,对位于瑞典特罗莎的一条砾石路进行原位剖面测量:研究重点是使用三种不同的剖面测量方法:采用 RTK 技术的无人机、路面测试仪(RST)和旋转激光水平仪(RLL),以探索这些方法之间的一致性。无人机配备了实时运动学(RTK)技术,可捕捉高分辨率图像,生成详细的三维表面模型,克服了恶劣天气条件带来的挑战。显著的成果显示了 RTK 技术的稳定性,它能保持稳定的 3D 定位精度,低于 2 厘米。在无人机-RST、无人机-RLL 和 RST - RLL 方法的比较中,所有剖面(道路中心线左侧 1 米至右侧 1 米)的最小平均绝对差值分别为 1.1 厘米、1 厘米和 0.7 厘米。这凸显了无人机技术的巨大进步,尽管无人机在高空作业,但仍能非常精确地测量垂直偏移量,对测试的碎石路进行剖面测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Next generation gravel road profiling – The potential of advanced UAV drone in comparison with road surface tester and rotary laser levels

Over the last decades, significant progress has been made and new approaches have been proposed for efficient collection of road condition data. Gravel roads are crucial for connecting urban and rural areas in Sweden, constituting a significant portion of the road network. Therefore, this study addresses the use of a developed Unmanned Aerial Vehicle (UAV)-based digital imaging system focusing on efficient collection of surface condition data over gravel roads.

The study focuses on in-situ profile measurements of a gravel road located in Trosa, Sweden, using three different profiling methods: UAV drone with RTK technology, Road Surface Tester (RST), and Rotary Laser Level (RLL) to explore the agreement between these methods.

The UAV drone, equipped with Real-Time Kinematic (RTK) technology, captures high-resolution images to produce detailed 3D surface models, overcoming the challenges posed by adverse weather conditions. Notable outcomes reveal RTK technology's stability, maintaining a steady 3D position accuracy below 2 cm. To enhance synchronization and comparison between different profiling methods, efforts should be made to standardize coordinate systems and measurement analysis software.

Minimum average absolute differences of 1.1 cm, 1 cm, and 0.7 cm were recorded for all profiles (from 1 m left to 1 m right of the road centerline) in the comparisons between UAV drone – RST, UAV drone – RLL, and RST – RLL methods, respectively. This underlines the significant advancement in UAV drone technology, enabling remarkably accurate measurements of vertical offsets for profiling the tested gravel road despite the high altitude at which the UAV drone operates.

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来源期刊
Transportation Engineering
Transportation Engineering Engineering-Automotive Engineering
CiteScore
8.10
自引率
0.00%
发文量
46
审稿时长
90 days
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