Comparison of roadway roughness derived from LIDAR and SFM 3D point clouds.

Details

• Creators:
  Alhasan, Ahmad ; Younkin, Kyle ; White, David J.
• Corporate Creators:
  Iowa State University. Earthworks Engineering Research Center
• Corporate Contributors:
  Iowa. Dept. of Transportation
• Subject/TRT Terms:
  Asphalt Concrete Evaluation Gravel Roads Laser Radar Pavements Photogrammetry Portland Cement Concrete Roughness Test Sections
• Publication/ Report Number:
  InTrans Project 15-543
• Resource Type:
  Tech Report
• Geographical Coverage:
  Iowa
• Corporate Publisher:
  Iowa State University. Institute for Transportation
• Abstract:
  This report describes a short-term study undertaken to investigate the potential for using dense three-dimensional (3D) point
  
  clouds generated from light detection and ranging (LIDAR) and photogrammetry to assess roadway roughness. Spatially
  
  continuous roughness maps have potential for the identification of localized roughness features, which would be a significant
  
  improvement over traditional profiling methods. This report specifically illustrates the use of terrestrial laser scanning (TLS) and
  
  photogrammetry using a process known as structure from motion (SFM) to acquire point clouds and illustrates the use of these
  
  point clouds in evaluating road roughness. Five roadway sections were chosen for scanning and testing: three gravel road
  
  sections, one portland cement concrete (PCC) section, and one asphalt concrete (AC) section. To compare clouds obtained from
  
  terrestrial laser scanning and photogrammetry, the coordinates of the clouds for the same section on the same date were matched
  
  using open source computer code. The research indicates that the technologies described are very promising for evaluating road
  
  roughness. The major advantage of both technologies is the large amount of data collected, which allows the evaluation of the full
  
  surface. Additional research is needed to further develop the use of dense 3D point clouds for roadway assessment.
  
  
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:3356db659d49527b787a03340a5ba7b424b07ea31770227ee5eab97b5caaa00d41bc445d64e8209ea9856bc0af120fce8995d071d5638c098bf996f11a2aa890
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/29591/dot_29591_DS1.pdf
• File Type:
  [PDF - 6.46 MB ]