Segmenting, Grouping and Tracking Vehicles in LIDAR Data

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.

• Record URL:
  http://www.purdue.edu/discoverypark/nextrans/assets/pdfs/124OSUY2.1_Summary%20and%20Final%20Technical%20Report.pdf
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/35524
• Supplemental Notes:
  • This research was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Ohio State University, Columbus

  Department of Civil, Environmental, and Geodetic Engineering
  2070 Neil Avenue
  Columbus, OH  United States  43210-1275

  NEXTRANS

  Purdue University
  3000 Kent Avenue
  Lafayette, IN  United States  47906-1075

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Coifman, Benjamin
  • Wu, Mo
  • Redmill, Keith
  • 0000-0003-1332-1332
  • Thornton, Douglas A
• Publication Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; References;
• Pagination: 33p

Subject/Index Terms

• TRT Terms: Data reduction; Laser radar; Probe vehicles; Traffic flow theory
• Uncontrolled Terms: Car following models; Microscopic traffic data
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01653363
• Record Type: Publication
• Report/Paper Numbers: NEXTRANS Project No. 124OSUY2.1
• Contract Numbers: DTRT12-G-UTC05
• Files: UTC, NTL, TRIS, RITA, ATRI, USDOT
• Created Date: Dec 11 2017 8:08PM