用于道路事故现场调查的无人机飞行模式分析

Vehicles Pub Date : 2023-11-27 DOI:10.3390/vehicles5040093
Gábor Vida, Gábor Melegh, Árpád Süveges, Nóra Wenszky, Á. Török
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摘要

无人驾驶飞行器(UAV)为道路事故现场记录提供了一种前景广阔的解决方案。本研究旨在调查无人飞行器沿水平路段拍摄的图像生成的三维点云和正射影像图中出现的系统变形,如弓形和圆弧形,同时探索调整飞行模式如何纠正这些误差。我们部署了四架消费级无人机,均以 10 米的高度飞行,沿两条不同的路线采集图像。仅处理天底图像会导致输出结果出现明显变形。然而,当数据集中加入了以斜摄影轴拍摄的、围绕指定兴趣点(POI)进行环形飞行的附加图像时,这些误差明显减小。由此产生的测量误差保持在 0-5 厘米范围内,远远低于事故重建中的常规误差范围。值得注意的是,整个过程在 15 分钟内完成,仅为现场调查所需时间的一半。这种方法展示了无人机高效记录道路事故现场以编制官方文件的潜力,无需预先确定地面控制点(GCP),也无需采用实时运动学(RTK)无人机或后处理运动学(PPK)技术。
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Analysis of UAV Flight Patterns for Road Accident Site Investigation
Unmanned Aerial Vehicles (UAVs) offer a promising solution for road accident scene documentation. This study seeks to investigate the occurrence of systematic deformations, such as bowling and doming, in the 3D point cloud and orthomosaic generated from images captured by UAVs along an horizontal road segment, while exploring how adjustments in flight patterns can rectify these errors. Four consumer-grade UAVs were deployed, all flying at an altitude of 10 m while acquiring images along two different routes. Processing solely nadir images resulted in significant deformations in the outputs. However, when additional images from a circular flight around a designated Point of Interest (POI), captured with an oblique camera axis, were incorporated into the dataset, these errors were notably reduced. The resulting measurement errors remained within the 0–5 cm range, well below the customary error margins in accident reconstruction. Remarkably, the entire procedure was completed within 15 min, which is half the estimated minimum duration for scene investigation. This approach demonstrates the potential for UAVs to efficiently record road accident sites for official documentation, obviating the need for pre-established Ground Control Points (GCP) or the adoption of Real-Time Kinematic (RTK) drones or Post Processed Kinematic (PPK) technology.
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