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Operational Evaluation of Unmanned Aircraft Systems for Crash Scene Reconstruction, Operational Evaluation Report, Version 1.0

NCJ Number
251628
Date Published
Author(s)
Johns Hopkins University
Annotation
Findings and methodology are presented for an operational evaluation of U.S. law enforcement agencies’ use of unmanned aircraft systems (UAS) for roadway crash-scene reconstruction (CSR).
Abstract
This evaluation focuses on the effectiveness and utility of UAS in reconstructing crash scenes in an operational setting, such that they provide improvement over other methods in the context of the entire investigation. The Michigan State Police (MSP), Illinois State Police (ISP), and Arlington Police Department (Texas) participated in the interviews for this evaluation. The main finding of this study is that using UAS for CSR can significantly reduce the data-collection time at a crash scene, resulting in shorter road-closure times and officer on-scene times. This is the case, provided an agency resolves logistical, administrative, and technology challenges associated with UAS use. Operational data collected in this study show that UAS data-collection is, on average, 1 hour shorter than data collection with a robotic total station; and UAS is 2 hours shorter than data collection by a manual total station; however, these gains can be achieved only if UAS can replace total stations. Although several agencies currently use UAS in crash investigations, the main use is to obtain aerial photographs to complement total station measurements, not as a replacement for the total station. The full benefits of UAS for CSR are realized by using aerial photographs for measurements, which would negate the need for total stations, at least in some crash investigations. Even with the current use of UAS to complement total station measurements, however, the UAS provides a bird’s eye view that may encompass the entire crash scene in one photograph within an hour of the crash. 24 figures, 3 tables, 23 references, and appended technical data and methodological material
Date Created: April 22, 2018