Segmenting, Grouping and Tracking Vehicles in LIDAR Data

Details

• Creators:
  Coifman, Benjamin ; Wu, Mo ; Redmill, Keith ; Thornton, Douglas A
• Corporate Creators:
  Ohio State University. Department of Civil and Environmental Engineering and Geodetic Science
• Subject/TRT Terms:
  • Data reduction
  • Laser radar
  • Probe vehicles
  • Traffic flow theory Car following models
  • Microscopic traffic data
  • Research Hub
• Publication/ Report Number:
  NEXTRANS Project No. 124OSUY2.1
• Resource Type:
  Tech Report
• Geographical Coverage:
  North America
• Corporate Publisher:
  Nextrans ; United States. Dept. of Transportation. Research and Innovative Technology Administration
• Abstract:
  This report presents the methodology and results from a study to extract empirical microscopic vehicular interactions from an instrumented probe vehicle. The contributions of this work are twofold: first, the general method and approach to seek a cost-effective balance between automation and manual data reduction that transcends the specific application; and second, the resulting empirical data set is intended to help advance traffic flow theory in general and car following models in particular. Section 1 provides an introduction and reviews the history of empirical freeway traffic flow studies to place the work in context. Section 2 presents the methodology, starting with a review of the instrumentation on the probe vehicle and the route taken by the probe vehicle, then continuing into the process of extracting information from the raw data. Section 3 presents the results. The report closes in Section 4 with conclusions and a discussion of the limitations.
• Format:
  PDF
• Funding:
  DTRT12-G-UTC05
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/35524/dot_35524_DS1.pdf
• File Type:
  [PDF - 6.73 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:5a5e25eaad4ceed0f2b0d0f6d94bee62cce0fcc80ac7f86b3075ec8f734ffd04f90b2db1685d0dc0e90bca7e2e411c5fce357a90253e16aaca82d5776fc8dd94