Pothole Detection and Classification Using 3D Technology and Watershed Method

Potholes are one of the roadway distresses that negatively impact roadway safety. With emerging sensing technology, three-dimensional (3D) pavement data, derived using 3D laser technology, have become available for detecting cracking and rutting. This paper presents a pothole detection method using 3D pavement data and a watershed method. Tests using the 3D data collected on 10th Street, Atlanta, Georgia and 6 mi of roadway on U.S. 80, Savannah, Georgia, has shown a 94.97% accuracy, 90.80% precision, and 98.75% recall. It has been demonstrated that the proposed method is promising for pothole detection and can provide a reliable method for pothole detection, especially when 3D pavement data have been collected for crack detection and already available.

• Record URL:
  https://doi.org/10.1061/(ASCE)CP.1943-5487.0000726
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/08873801
• Supplemental Notes:
  • © 2018 American Society of Civil Engineers.
• Authors:
  • Tsai, Yi-Chang
  • Chatterjee, Anirban
• Publication Date: 2018-3

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 04017078
• Serial:
  • Journal of Computing in Civil Engineering
  • Volume: 32
  • Issue Number: 2
  • Publisher: American Society of Civil Engineers
  • ISSN: 0887-3801

Subject/Index Terms

• TRT Terms: Classification; Detection and identification; Highway safety; Image processing; Pavement cracking; Potholes; Rutting; Sensors; Watersheds
• Geographic Terms: Atlanta (Georgia); Savannah (Georgia)
• Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Pavements;

Filing Info

• Accession Number: 01678990
• Record Type: Publication
• Files: TRIS, ASCE
• Created Date: Aug 27 2018 2:05PM