In order to determine fault following traffic accidents, authorities must gather an extensive amount of spatial information from the scene. Everything from precise vehicle locations to skid marks must be documented and measured to provide accurate information about the nature of the collision for subsequent analysis and reference in legal proceedings, which could take place months later.
While crucial, acquiring these minute details can be time-consuming and, in many cases, dangerous. According to a study by the Virginia Transportation Research Council, for every 2-3 minutes at the scene of an accident in a high- traffic area, the likelihood of a secondary crash increases by 1 percentage point. This means that the longer a roadway is blocked off to preserve the crash site, the higher the chances of pedestrians or on-the-ground personnel being injured in another accident. These dangers make it imperative for investigators to collect spatial information as quickly as possible to clear the roadway of obstructions faster and minimize time on site.
Traditional methods require investigators to lay out measuring tape and document the scene using digital cameras, a process that might take up to six hours on its own. While modern investigators have begun using technology such as laser scanners and total stations to record distances and map the scene, the process still takes two to three hours.
Solution
With the number of traffic incidents expected to increase as urban growth pushes road infrastructure and traffic congestion to critical capacity, authorities have begun to add unmanned aerial technology to their toolkits. Using drones, first responders are able map the scene and gather all the data needed to build comprehensive 3D models in as little as 15-20 minutes. The technology means less time and less risk for those at the scene, and the ability to build 3D models gives investigators the opportunity to analyze the scene from every angle and viewpoint during post- examination. With the addition of an RTK module, drones can easily capture centimeter-accurate location data to ensure each 3D rendering mirrors the scene precisely.