Practically, the Accident Reconstruction works in reverse – documenting and analysing evidence at the scene to draw conclusions about the cause of the accident and how it occurred. Reconstruction may reveal a host of factors that led to the accident, including Speeding, Running into signs and red lights, errors in turning and lane changes, loss of driver control, visibility issues and poor road conditions.
Traditionally, investigators used pencils and tape measures to manually identify skid marks and other crucial elements of the scene in order to recreate the cause of an accident. And it goes without saying the amount of time required for these manual procedures caused considerable traffic delays on the roads where the accident occurred. Accident mappings used to take two to three hours to complete even after these traditional technologies were replaced by laser scanners.
With the innovative Drone Technology, Accident Reconstruction is now simpler and more efficient. One of the major factors that sets apart the Drones for Accident Reconstruction is the significant reduction of time required to map out the scene for an investigation, and bring the road-life back to normal.
While first responders try to preserve the accident scene and collect enough evidence to reconstruct the accident, law enforcement will be clearing the areas promptly to prevent further accidents. According to Purdue University research, investigators can map an accident site in just five to eight minutes using drones. It goes without saying that the time saved here translates to saving lives at the earliest and reducing the probability of secondary crashes as well.
The most dangerous time to be on the road is right after a car accident! Research shows that the longer the road is blocked, the more probable another accident would occur owing to a sudden stop in traffic, such as a pileup, or unexpected debris in the road. Moreover, accuracy cannot be compromised in data collection especially when it is for Accident Reconstruction. Even a minor data inaccuracy could make it look like a different situation caused the accident.
Drones provide us with visual data, from different angles and heights, that we may use to generate actionable insights – orthomosaic maps or 3D models, using a mapping software.
Insurance companies are now using drones to better evaluate insurance claims made by people involved in car crashes. In addition, legal firms that specialise in personal injury law related to crashes have begun to use drones in accident investigations in order to provide better and clear visuals for juries as well as maps for accident reconstruction purposes.
It is amazing to see how drones are adding value to various industries at various levels previously unattainable otherwise; and DJI drones are at the forefront of driving this transformation!
The latest firmware update for DJI Enterprise drones says it all – DJI has consolidated months of user feedback and testing into an update that packs in loads of new features for their most powerful enterprise drones. For instance, the Point of Interest feature (POI mode) in the DJI Mavic 3 Enterprise drones – It is an intelligent flight mode that will allow you to quickly orbit a point of interest and collect comprehensive data with a 360-degree view of the target. This has been one of the most requested features by first responders and public safety agencies who want to easily add an orbit to their accident reconstruction data capture or orbit a scene. Vertical structures like telecom towers can also be captured utilising this tool.
Accident reconstruction is one of the top applications of LiDAR drones, such as the DJI Zenmuse L1. As LiDAR does not require light to work, personnel are not constrained by poor visibility at night. After mapping the scene, personnel can seamlessly clear the the wreckage – this is critical especially when an accident site is impeding traffic, that too in unfavourable weather conditions.
If you’d like to find out more on how drones can help with accident reconstruction, please get in touch.