Image-Based 3D Reconstruction of Utah Roadway Assets

Details

• Creators:
  Farhadmanesh, Mohammad ; Cross, Chandler ; Rashidi, Abbas
• Corporate Creators:
  University of Utah. Department of Civil and Environmental Engineering
• Corporate Contributors:
  Mountain-Plains Consortium ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Asset management
  • Data collection
  • Evaluation and assessment
  • Feasibility analysis
  • Highways
  • Laser radar
  • Photogrammetry
  • Software
• Publication/ Report Number:
  MPC-606
• Resource Type:
  Tech Report
• Geographical Coverage:
  Utah;United States
• Edition:
  Final Report
• Corporate Publisher:
  Mountain-Plains Consortium
• 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.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/64749/dot_64749_DS1.pdf
• File Type:
  [PDF - 5.53 MB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:584ca2273bb216c786d9a5ab9db07557f9b6fdf52b5cd3356f609ab081b6a82081730d8a9b22836618ba518912b87648bb1da72f1e75c465a1d0738dd32e6a27