Airborne LiDAR: A New Source of Traffic Flow Data

Details

• Creators:
  Grejner-Brzezinska, Dorota A. ; Toth, Charles ; McCord, Mark
• Corporate Creators:
  Ohio State University. Center for Mapping
• Corporate Contributors:
  Ohio. Office of Aerial Engineering ; Ohio. Dept. of Transportation ; United States. Federal Highway Administration
• Subject/TRT Terms:
  • Traffic flow
  • Remote sensing
  • Optical radar
  • Traffic flow--Ohio--Remote sensing
  • Motor vehicles--Ohio--Remote sensing
  • Optical radar--Ohio
• Publication/ Report Number:
  FHWA/OH-2005/14
• Resource Type:
  Tech Report
• Geographical Coverage:
  Ohio
• OCLC Number:
  665083675
• Corporate Publisher:
  Ohio State University. Center for Mapping
• NTL Classification:
  NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Flow
• Abstract:
  LiDAR (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition to efficiently create DEM/DSM in the late '90s. With increasing point density, new systems are now able to support object extraction, such as extracting building and roads, from LiDAR data. The novel concept of this project was to use LiDAR data for traffic flow estimates. In a sense, extracting vehicles over transportation corridors represents the next step in complexity by adding the temporal component to the LiDAR data feature extraction process. The facts are that vehicles are moving at highway speeds and the scanning acquisition mode of the LiDAR certainly poses a serious challenge for the data extraction process. The OSU developed method and it implementation, the I_FLOW program, have demonstrated that LiDAR data contain valuable information to support vehicle extraction, including vehicle grouping and localizations. The classification performance showed strong evidence that the major vehicle categories can be efficiently separated. The I_FLOW program is ready for deployment.
• Format:
  PDF
• Funding:
  134145
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/5726/dot_5726_DS1.pdf
• File Type:
  [PDF - 24.08 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:67dfc0e50b36b9bb9d3d14be1a1c8b4ba632ecc3ddbf365fdfb51877cf37ac6c