How do you use drones to map an accident scene? 

Kineticorp Principal, Neal Carter, discusses his latest research “An Optimization of Small Unmanned Aerial Systems (sUAS) Image-Based Scanning Techniques for Mapping Accident Sites.” Neal presented his findings at SAE International‘s 2019 World Congress Event (WCX). A special thanks to Alireza Hashemian, and Nathan McKelvey for their involvement with the project.

Publication Introduction:

Small unmanned aerial systems have gained prominence in their use as tools for mapping the 3-dimensional characteristics of accident sites. Typically, the process of mapping an accident site involves taking a series of overlapping, high-resolution photographs of the site, and using photogrammetric software to create a point cloud or mesh of the site. This process, known as image-based scanning, is explored and analyzed in this paper. A mock accident site was created that included a stopped vehicle, a bicycle, and a ladder. These objects represent items commonly found at accident sites. The accident site was then documented with several different unmanned aerial vehicles at differing altitudes, with differing flight patterns, and with different flight control software. The photographs taken with the unmanned aerial vehicles were then processed with photogrammetry software using different methods to scale and align the point clouds. The point cloud data produced with different vehicle / flight pattern / altitude combinations was then quantitatively compared to terrestrial LiDAR scan data. The results are presented here, as well as recommendations based on equipment and desired output. ….. Purchase Full Publication

Full Publication:

SAE 2019-01-0427 – An Optimization of Small Unmanned Aerial System (sUAS) Image Based Scanning Techniques for Mapping Accident Sites

Authors: 

Neal Carter, Alireza Hashemian, Nathan Mckelvey 

Related Case Studies, Content & Research:

SAE 2019-01-0423 – Reconstruction of 3D Accident Sites Using USGS LiDAR, Aerial Images, and Photogrammetry

SAE 2016-01-1478 – Determining Position & Speed through Pixel Tracking and 2D Coordinate Transformation in 3D Environment 

SAE 2016-01-0415 – Nighttime Videographic Projection Mapping to Generate Photo-Realistic Simulation Environments 

SAE 2013-01-0788 – Video Projection Mapping Photogrammetry through Video Tracking

FARO – Technology White Paper, 2012 – Benefits of 3D Laser Scanning in Vehicle Accident Reconstruction

SAE 2010-01-0929 – Evaluation of Photometric Data Files for Use in Headlamp Light Distribution

SAE 2006-01-0723 – Image Analysis of Rollover Crash Tests Using Photogrammetry

SAE 2004-01-1221 – A Video Tracking Photogrammetry Technique to Survey Roadways for Accident Reconstruction

SAE 2001-01-3313 – Determining Crash Data Using Camera Matching Photogrammetric Technique

I CRASH 2000 – Using Digital Photogrammetry to Determine Crash Severity

SAE 1999-01-0439 – Using Digital Photogrammetry to Determine Vehicle Crush and Equivalent Barrier Speed (EBS)

SAE 1997-970944 – Accident Scene Diagramming Using New Photogrammetric Technique

NAFE, REF:308S, Photogrammetric Accident Analysis – Forensic Engineering Comparison of Two & Three Dimensional Photogrammetric Accident Analysis

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