Car accidents can cause tremendous traffic delays while also presenting a dangerous situation for police officers working to clear the scene.
In major metropolitan areas across the United States, delays related to traffic incidents are estimated to account for more than half of all congestion-related delays. The traffic delay associated with major accidents is one of the most commonly cited concerns related to traffic incident management.
For police officers, “struck-by” incidents — when an officer is struck by a passing vehicle while doing their job at a crash scene — is one of the leading causes of accidental death among law enforcement and fire and rescue personnel. In 2016, 12 police officers were killed in struck-by accidents, the most since 2008, according to the FBI.
A recent NIJ-funded study found that using Unmanned Aircraft Systems (UAS) can reduce the amount of time taken to clear a crash scene, thereby reducing the time officers are at risk of injury in the roadway. Additionally, the study compared the accuracy of measurements made using different methods and found that UAS slightly reduced some measurement errors.
UAS are already being used in a variety of law enforcement investigations, predominantly for scenarios where they can help to keep officers out of harm’s way. For example, they are being used in crime scene investigations, missing persons cases, SWAT team hostage scenarios, natural disasters, and fire scene and crash scene investigations.
Several agencies across the country are currently using UAS in crash investigations to take aerial photographs to complement other methods of investigation. See “Investigation Tasks” in the full report for a detailed list and description of all the elements of a crash scene investigation.
In a recent study, researchers compared the use of UAS with established methods used in crash scene investigations. Using a mock crash scene, the researchers found that, with the support of UAS, the time taken to clear the scene was reduced by 35-45 minutes.
Furthermore, the time that officers were at risk in the roadway was reduced by approximately 28 minutes.
Finally, the study shows that data collection by UAS took, on average, one hour less than data collection by a robotic station and two hours less than data collection by a manual or robotic total station. (See What Is a Total Station.)
Although UAS were shown to be beneficial in the investigation of mock crash scenes, operational conditions in actual situations can impact their effectiveness. In a real-life setting, factors that may hinder the use of UAS include the time it may take to deploy the UAS if operators are far from the scene, adverse weather conditions, low light, Federal Aviation Administration regulations on UAS use, obstacles on or near the roadway that block the view of UAS or prevent their use, and the presence of other tasks that can add significantly to the time it takes to capture aerial images.
What Is a Total Station
A total station is an instrument used to take measurements at the crash scene. It measures distances and angles and also is used in surveying and building construction. It combines a precision instrument for measuring angles (an electronic theodolite or transit) with an electronic distance measuring device and is operated by an external computer. The station can be either manual — it requires a person to site and align the station to the target — or robotic — it is guided by sensors and automatically turns to take in multiple measurements.
About This Article
The research described in this article was supported by NIJ grant number 2013-MU-CX-K111, awarded to The Johns Hopkins University.
This article is based on the grant report "Operational Evaluation of Unmanned Aircraft Systems for Crash Scene Reconstruction" (pdf, 78 pages).
[note 1] “Best Practices for Traffic Incident Management in Florida,” University of South Florida, Center for Urban Transportation Research, April 2005.
[note 2] “Crash Investigation and Reconstruction Technologies and Best Practices,” US DOT Federal Highway Administration, Task Order DTFH61-12-D-00037-T-5009, December 2015.