Accuracy of 3D Point-Cloud and Photo-Based Models of City Street Intersections

Abstract

From Georgia Southern University’s Built Environment and Modeling lab, this study compares point positions and distance measurements completed with state-of-the-art instruments and equipment. A modern, 12-second, laser scanner, a modern unmanned aerial vehicle and a highly accurate, 1-second robotic total station were employed for this study. The latter serving as the benchmark instrument. The main objective of this quantitative comparison is to explore the accuracy and usability of a relatively large point-cloud model, as a virtual surveying tool for redesign/reconstruction purposes. This project involves the generation of large, 3D, point-cloud models of two busy and complex city street intersections. One intersection encompasses an approximate area of 300 ft × 750 ft and containing five converging elements: three streets and two railroads. It is an accident-prone location requiring redesign. The second street intersection encompasses an approximate area of 1,500 ft × 2,500 ft, containing two streets intersecting at an approximate 45-degree angle. The resulting computer model has been geo-referenced in the Georgia East State Plane Coordinate System (SPCS) using control points with coordinates established by GPS (Global Positioning System) via a rapid, network-based, Real-Time Kinematic (RTK) approach. These city street intersections are within the Blue-Mile corridor in Statesboro, GA. Along with the Statesboro city engineering, the Blue-Mile corridor has plans to enhance and improve the traffic flow of the Blue-Mile corridor, which contains many businesses and restaurants. The final point-cloud models are to be donated to the city engineers to assist in the redesign of the intersections. A full analysis of the referred discrepancies is presented and recommendations on improving the overall current accuracies are provided

    Similar works