MPC Research Reports
Report Details

Title:	Image-Based 3D Reconstruction of Utah Roadway Assets
Authors:	Mohammad Farhadmanesh, Chandler Cross, and Abbas Rashidi
University:	University of Utah
Publication Date:	Aug 2022
Report #:	MPC-22-479
Project #:	MPC-606
TRID #:	01864873
Keywords:	asset management, data collection, highways, image analysis, three dimensional displays

Abstract

Understanding the condition of roadway assets is important for transportation agencies to plan for future improvements and asset management purposes quantitatively. Since these assets are distributed across the country, a manual data collection system falls short of the automated methods due to time and cost issues. Some pioneer departments of transportation in the United States use mobile Light Detection and Ranging (LiDAR) to monitor highway assets and pavement condition data. However, LiDAR is expensive and not affordable for every maintenance agency. Additionally, special technical knowledge is required to perform this method, which may not be accessible to the maintenance agency staff. Recently, image-based 3D reconstruction has been shown to be a cheaper and simpler technology than LiDAR. In this report, we assess the alternative method (image-based) for reconstructing 3D models (virtual 3D point clouds) of transportation agencies. The analysis of the data quality and associated costs holds the promise for conducting a feasible roadway asset inventory.

How to Cite

Farhadmanesh, Mohammad, Chandler Cross, and Abbas Rashidi. Image-Based 3D Reconstruction of Utah Roadway Assets, MPC-22-479. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2022.