Efficient Extraction and Evaluation of Complex Pavement Markings from Mobile Laser Scan Data

Recently, in their research with the Oregon Department of Transportation (ODOT), the research team developed an automated method for extracting linear lane markings from mobile laser scan (MLS) data as well as evaluating the retroreflectivity of those markings. In the current Pactrans project the team is building upon that effort to develop advanced techniques to handle more complex markings (e.g., pedestrian crosswalks, chevrons, and arrows) that were not considered in the prior project, but important to support mobility for multi-modal transportation. First, the team projects the MLS data into 2D to generate an intensity image and segment high intensity pixels, likely representing various road markings. Subsequently, a deep learning neural network approach, which is known for its high performance for object recognition in many applications, is used to classify various types of markings. This research will enable performance-based procedures for transportation agencies to evaluate pavement marking quality by providing detailed information, including retroreflectivity and types of markings, ranging from high resolution data on a single stripe to aggregated data and analyses statewide. This, in turn, supports informed decision making by DOT management for effective resource allocation. Improved maintenance of pavement markings will also lead to improved mobility with technologies such as autonomous vehicles.

Language

  • English

Project

  • Status: Active
  • Funding: $60000
  • Contract Numbers:

    69A3551747110

  • Sponsor Organizations:

    Pacific Northwest Transportation Consortium

    University of Washington
    More Hall Room 112
    Seattle, WA  United States  98195-2700

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Oregon State University, Corvallis

    Department of Civil Engineering
    202 Apperson Hall
    Corvallis, OR  United States  97331-2302
  • Project Managers:

    Olsen, Michael

  • Performing Organizations:

    Oregon State University, Corvallis

    Department of Civil Engineering
    202 Apperson Hall
    Corvallis, OR  United States  97331-2302
  • Principal Investigators:

    Olsen, Michael

  • Start Date: 20180816
  • Expected Completion Date: 20200815
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01701479
  • Record Type: Research project
  • Source Agency: Pacific Northwest Transportation Consortium
  • Contract Numbers: 69A3551747110
  • Files: UTC, RiP
  • Created Date: Apr 5 2019 3:55PM