How do you reconstruct an accident using USGS LiDAR?
Kineticorp Photogrammetry Expert, Toby Terpstra, discusses our latest research “Reconstruction of 3D Accident Sites Using USGS Lidar, Aerial Images, and Photogrammetry.” Toby presented the findings at SAE International’s 2019 World Congress Event (WCX). A special thanks to Stephen Fenton and Alireza Hashemian for their involvement with the project.
Publication Introduction:
The accident reconstruction community has previously relied upon photographs and site visits to recreate a scene. This method is difficult in instances where the site has changed or is not accessible. In 2017 the United States Geological Survey (USGS) released historical 3D point clouds (LiDAR) allowing for access to digital 3D data without visiting the site. This offers many unique benefits to the reconstruction community including: safety, budget, time, and historical preservation. This paper presents a methodology for collecting this data and using it in conjunction with aerial imagery, and camera matching photogrammetry to create 3D computer models of the scene without a site visit. To determine accuracies achievable using this method, evidence locations solved for using only USGS LiDAR, aerial images and scene photographs (representative of emergency personnel photographs) were compared with known locations documented using total station survey equipment and ground-based 3D laser scanning. The data collected from three different site locations were analyzed, and camera matching photogrammetry was performed independently by 5 different individuals to locate evidence. On average, the resulting evidence for all three test sites was found to be within 3.0 inches (8cm) of known evidence locations with a standard deviation of 1.7 inches (4cm). To further evaluate the quality of the USGS LiDAR, a comparative point cloud analysis of the roadway surfaces was performed. On average, 85% of the USGS LiDAR points were found to be within .5 inches of the ground-based 3D scanning points. ….. Purchase Full Publication
Full Publication:
Authors:
Toby Terpstra, Alireza Hashemian, Stephen Fenton
Related Case Studies, Content & Research:
SAE 2019-01-0424 – The Application of Augmented Reality to Reverse Camera Projection
SAE 2016-01-1475 – A Survey of Multi-View Photogrammetry Software for Documenting Vehicle Crush
SAE 2013-01-0788 – Video Projection Mapping Photogrammetry through Video Tracking
SAE 2011-01-0286 – Photogrammetric Measurement Error Associated with Lens Distortion
SAE 2010-01-0292 – Evaluation of Photometric Data Files for Use in Headlamp Light Distribution
SAE 2009-01-0110 – Simulating Headlamp Illumination Using Photometric Light Clusters
SAE 2006-01-0723 – Image Analysis of Rollover Crash Tests Using Photogrammetry
SAE 2001-01-3313 – Determining Crash Data Using Camera Matching Photogrammetric Technique
I CRASH 2000 – Using Digital Photogrammetry to Determine Crash Severity
SAE 1997-970944 – Accident Scene Diagramming Using New Photogrammetric Technique
Comments are closed.