Assessing Precision and Dependability of Reconstructed Three-Dimensional Modeling for Vehicles at Crash Scenes using Unmanned Aircraft System

Akmal Jauhari Jalal, Mohd Farid Mohd Ariff, A. Razali, Razak Wong Chen Keng, Mohamad Ariff Wook, Mohamad Ikhwan Idris
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Abstract

This study focuses on the accuracy assessment of 3D reconstructions of crime scenes using Unmanned Aircraft Systems (UAS) and Terrestrial Laser Scanners (TLS) data for forensic crash investigation. Forensic crash investigation involves meticulously analyzing physical evidence, vehicles, and human factors in road collisions to determine the sequence of events. Preserving the original state of the crash scene before cleaning is essential for accurate forensic analysis. However, this preservation process can disrupt normal activities and demand considerable time. Geomatic technology, specifically UAS or drones, offers a potential solution for efficient and precise forensic mapping. The application of UAS technology enables swift data collection, leading to cost savings, enhanced safety, and data utilization. This study aims to assess the suitability of UAS techniques for forensic mapping, encompassing both relative and absolute accuracy. This research uses a UAS to rapidly and comprehensively capture evidence from a simulated crash site using predefined flight paths. The acquired image data is then processed utilizing Agisoft Metashape software, generating a detailed 3D model of the crash scene. This model can be enriched with annotations, measurements, and pertinent information. A comparative analysis is performed by preparing a table that contrasts the absolute and relative accuracy of UAS-collected data with that obtained from TLS, which serves as a benchmark. The results reveal that the UAS demonstrates a relative accuracy Root Mean Square Error (RMSE) of approximately ±4.1 cm compared to TLS. Concerning absolute precision, the UAS-produced RMSE values are determined as ±0.20719 for the X coordinate, ±0.164 for the Y coordinate, and ±0.001584 for the Z coordinate compared to GNSS data, which functions as the benchmark. The utilization of UAS technology offers a non-invasive measurement approach that eliminates direct physical contact between the operator and the documented object. This non-intrusive method ensures the preservation of the original scene characteristics and has shown its superiority over conventional approaches in managing crash scenes. Overall, this study underscores the potential of UAS technology in accurately reconstructing crime scenes for forensic investigation purposes.
基于无人机系统的碰撞现场车辆三维重建建模精度与可靠性评估
本研究的重点是使用无人机系统(UAS)和地面激光扫描仪(TLS)数据进行法医坠机调查的犯罪现场三维重建的准确性评估。法医事故调查包括仔细分析道路碰撞中的物证、车辆和人为因素,以确定事件的顺序。在清理之前保持坠机现场的原始状态对于准确的法医分析至关重要。然而,这种保存过程可能会扰乱正常的活动,并需要相当长的时间。测绘技术,特别是无人机或无人机,为高效、精确的法医测绘提供了潜在的解决方案。UAS技术的应用可以实现快速数据收集,从而节省成本,提高安全性和数据利用率。本研究旨在评估UAS技术在法医制图中的适用性,包括相对和绝对精度。本研究使用无人机从模拟坠机现场使用预定义的飞行路径快速全面地捕获证据。然后使用Agisoft Metashape软件对获取的图像数据进行处理,生成详细的碰撞现场3D模型。该模型可以通过注释、度量和相关信息进行充实。通过准备一个表来进行比较分析,该表将uas收集的数据的绝对精度和相对精度与从TLS获得的数据进行对比,这可以作为基准。结果表明,与TLS相比,UAS的相对精度为±4.1 cm。在绝对精度方面,与GNSS数据作为基准,确定了uas生成的X坐标RMSE值为±0.20719,Y坐标RMSE值为±0.164,Z坐标RMSE值为±0.001584。利用UAS技术提供了一种非侵入式测量方法,消除了操作员与记录对象之间的直接物理接触。这种非侵入性的方法保证了原始场景特征的保留,在管理碰撞场景方面显示出其优越性。总的来说,这项研究强调了无人机技术在为法医调查目的准确重建犯罪现场方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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