Origin destination disaggregation using fratar biproportional least squares estimation for truck forecasting.

Details

• Creators:
  Horowitz, Alan J.
• Corporate Creators:
  University of Wisconsin--Milwaukee. Center for Urban Transportation Studies
• Subject/TRT Terms:
  • Origin and destination
  • Trucking
  • Traffic forecasting
  • Least squares method
  • Mathematical models
• Publication/ Report Number:
  Paper No. 09-1
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  National Center for Freight and Infrastructure Research and Education (U.S.)
• NTL Classification:
  NTL-FREIGHT-Trucking Industry ; NTL-PLANNING AND POLICY-PLANNING AND POLICY
• Abstract:
  This working paper describes a group of techniques for disaggregating origin-destination tables ; for truck forecasting that makes explicit use of observed traffic on a network. Six models within ; the group are presented, each of which uses nonlinear least-squares estimation to obtain row and ; column factors for splitting trip totals from and to larger geographical areas into smaller ones. ; The techniques are philosophically similar to Fratar factoring, although the solution method is ; quite different. The techniques are tested on a full-sized network for Northfield, MN and are ; found to found to work effectively.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/25342/dot_25342_DS1.pdf
• File Type:
  [PDF - 332.28 KB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:a12c2320ff1f95fdc11ed560db9a0f2b7bf6728ab2f01f73a1d0c1de4683f3c536400ff0909848c398a2aa92b6594d7dce8173038c7d691c98b35b44c419b2c7