Using Drones in the Crash Documentation Reconstruction

AERONAUTICS

Aeronautics: Using Unmanned Aircraft in the Crash Documentation/ Reconstruction

Unmanned aircraft are air vehicles that can fly without having human pilots. They can be controlled with a ground control station or onboard electronic equipment by humans. They can be remotely operated if a powerful wireless connection is mandatory for a safe and well-controlled flight. The most common form of unmanned aerial vehicle (UAV) is completely autonomous drones but do have a controller that is to be operated by humans. UAVs are also suitable for outdoor detection of crash scenes or locations where certain accidents have occurred. The survivors could be identified and could be contacted immediately. The crew members could have a clear picture of the location and assess the seriousness of the disaster. This paper aims at devising a problem statement and mission objective for using unmanned aircraft in the crash documentation or reconstruction, which requires ultimate accuracy.

Unmanned aircraft or drones have been said to provide reconstruction benefits for the accident scene as they can collect visual data with precision. The mapping software they are equipped with changes the photos and videos in 3D models that could be recreated into maps for later accident reformation (Dukowitz, 2020). A popular technique called photogrammetry is utilized through unmanned aircraft or drones so that taking videos at angles and locations where crashes or accidents have taken place is facilitated (Almeshal, Alenezi & Alshatti, 2020). It is studied that this technique is twice as fast compared to hands-on methods for taking photos of crashes and accidents with accuracy. The reconstruction of accident scenes is convenient with this method with the visual data collected by the drones’ photogrammetry technique due to its safe flight and control when in the air.

The user-friendly apps and tools are used afterward to develop the captured visual data by the unmanned aircraft into reconstructed accident scenes so that the dynamics of the crash or calamity could be interpreted well. Aerial photography and video making through advanced drone functions are helpful in re-devising the scene for investigating the accidents. When evidence like aerial photos or videos is present, obtained through drones, the crash investigation becomes much more feasible than asking the eyewitnesses at the crash scene, which might not be available at times.

Statements from police investigators have corroborated that drones are quite efficient in collecting data for crash examination. They cited that the data collection procedure with drones takes less than five or sometimes eight minutes only, while this was not possible manually (Sequin, 2019). When police officers had to investigate around the crash scene, it took a good two to three hours for the entire process. Technology has been extensively used by the police and traffic departments, especially via drones or unmanned aircraft, for reconstructing the map crash scenes, catering to its benefits for law enforcement, and forming specialty teams for the crash location.

The image processing taken by the drones depends on the positioning of the unmanned aircraft and its control by a human. The creation of orthorectified images captured by the drones from the crash scene assists in providing the correct infrastructure of the place where the incident took place with the depiction of the placement of crash vehicles. Some drones can capture more than 100 photos at a time of the crash site through a grid-type path and recording techniques in-built within its programming software (Sequin, 2019). The abundance of photos provides adequacy for a 3D re-creation of the crash scene.

The field sketch is obtained with UAV for crash scene reconstruction, which is a rough drawing generated by the map function of the software. The crash investigator can observe various measurements of the incident place to provide enhanced calculations and analysis. The field sketch includes various items such as the position of the crash vehicles, environmental factors such as ice, water weather, etc., obstacles in vision, terrain features, dust and debris at the location, the width of lane and roads and baseline, etc. (The Johns Hopkins University, 2018, p. 12).

Problem Statement

Research has suggested certain limitations when using unmanned aircraft or drones for taking photos or recording videos for 3D crash reconstruction. For example, the quality of image capturing for a crash reconstruction would be greatly impacted by lighting and weather conditions (Almeshal, Alenezi & Alshatti, 2020). If there is fog or rain, the drone would certainly not be in the position of having a stable flight while in the air, save taking HD quality images or recording videos. Moreover, in places with dense forestation and various electrical poles, the UAVs would be unable to perform photogrammetry techniques with better quality, resulting in unsatisfactory visual data collected for crash reconstruction.

The presence of aerial barriers such as communication cables and adverse lighting could cause problems for collecting visual data for the crash scenes. The positioning of the drone and hooting viewpoints of the objects under inspection might not deliver the expected image quality, contributing to poor measurements (Wang et al., 2021). The quality of scanners and sensors in the UAV would also influence the quality of photos and the afterward 3D redrafting. There might be certain unmanned aircraft or drones that would use expensive equipment for providing a more sophisticated view. It can become costly for the user to obtain multiple photos and that too, in unmatched quality for the crash reconstruction with an assurance that the image quality would not be oblique. Minor errors could create huge differences in the remodeled and actual crash scene, causing subsequent errors in unerring prediction. The actual measurements for the visual data and re-formulation of the photos into 3D models determine the level of accuracy.

The problem statement for the current research, therefore, would be:

What factors should be considered while assessing the effectiveness of the use of unmanned aircraft, particularly drones, in crash reconstruction?

Mission Objectives

The common measurement approaches used for gathering visual data through UAVs for crash reconstruction are the total number of stations from where the data is to be taken, 3D laser scanning, and photogrammetry (The Johns Hopkins University, 2018, p. 15).

The judicial proceedings require certain criteria to be fulfilled once the evidence, which might be crash reconstruction, is submitted for further scrutiny. The validity of the technique through which the images have been captured and the maintenance of standards. At the same time, the process of visual data collection was conducted with the help of unmanned aircraft vehicles, and the potential errors in the visual data collection in which air obstacles have to be inspected closely (The Johns Hopkins University, 2018, p. 19). Besides, recent studies have now declared that Frye Standard needs to be observed when submission of evidence that is a collection with unmanned aircraft is to be done inside the courts. The standard requires the evidence to be collected via generally accepted means and by the experts of the relevant fields so that errors could be diminished to a maximized level.

With a wide usage of Global Positioning System (GPS) these days, it is now possible to reconstruct crash scenes accurately when UAV is involved. The high-resolution pictures that the drone can capture are sufficient to produce a re-enactment of the crash scene with better graphing methodologies. The processing of pictures with specialized image algorithms is done for creating models of the crash scene with precise measurements. NIJ-sponsored studies verified that the crime scene investigation was done efficiently since the time taken to clear the scene was reduced with UAV by 35-45 minutes as compared to manual methods (The Johns Hopkins University, 2018, p. 19).

Hence, the mission objectives would be:

· To check whether the factors determined in the literature are present in UAV for crash reconstruction

· The number of factors is considered the most important for obtaining the highest level of accuracy for capturing photos or recording videos