Reconstruction of 3D Accident Sites Using USGS LiDAR, Aerial Images, and Photogrammetry

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 was 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.