Asset Characterization Using Automated Methods

This project would explore the possible ways of using existing LiDAR and/or other third-party data to identify and catalog various assets such as bridges and culverts and some additional information about them. Possibly done in 2 phases. Phase I would look at the following: (1) identify various data attributes that should be produced from the research (culvert dimensions, bridge span etc.); (2) evaluate the minimal level of accuracy of the data required for it to be usable; (3) identify first-party and third-party data that are available to produce the data; (4) develop a machine learning algorithm to extract the relevant data; and (5) test the algorithm for select locations and evaluate if the results meet the need.

Language

• English

Project

• Status: Active
• Funding: $200,000
• Contract Numbers:

  TR202311

• Sponsor Organizations:

  Missouri Department of Transportation

  1617 Missouri Boulevard
  P.O. Box 270
  Jefferson City, MO  United States  65102
• Project Managers:

  Schulte, Brent

• Performing Organizations:

  Missouri Center for Transportation Innovation

  Lafferre Hall
  416 S 6th St.
  Columbia, Missouri  United States  65201

  University of Missouri, Kansas City

  Department of Civil Engineering
  5100 Rockhill Road, Flarsheim Hall
  Kansas City, MO  United States  64110
• Principal Investigators:

  Kim, Sungyop

  Baker, Donald

• Start Date: 20230601
• Expected Completion Date: 20240830
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Asset management; Bridges; Culverts; Data collection; Data quality; Laser radar; Machine learning
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01892500
• Record Type: Research project
• Source Agency: Missouri Department of Transportation
• Contract Numbers: TR202311
• Files: RIP, STATEDOT
• Created Date: Sep 7 2023 9:25AM