ESTIMATION OF PARAMETERS IN MODELS FOR TRAFFIC PREDICTION: A NON-LINEAR REGRESSION APPROACH

This paper contains some suggestions on how to use traffic counts on links in networks and non-linear regression in order to estimate parameters in models for traffic prediction, for example gravity-distribution models. The suggested method has the advantage that it is straight-forward and does not require an O-D survey which is usually very expensive.(a) /TRRL/

• Corporate Authors:

  Pergamon Press, Incorporated

  Maxwell House, Fairview Park
  Elmsford, NY  United States  10523
• Authors:
  • Hogberg, P
• Publication Date: 1976-8

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 263-2651
• Serial:
  • Transportation Research /UK/
  • Volume: 10
  • Issue Number: 4
  • Publisher: Pergamon Press, Incorporated

Subject/Index Terms

• TRT Terms: Estimates; Forecasting; Gravity models; Linear regression analysis; Links (Networks); Origin and destination; Physical distribution; Regression analysis; Traffic counting; Traffic counts; Traffic forecasting
• Uncontrolled Terms: Linkages
• ITRD Terms: 132: Forecast; 690: Gravity model; 6588: Regression analysis; 689: Traffic count
• Subject Areas: Data and Information Technology; Freight Transportation; Highways; Operations and Traffic Management; I71: Traffic Theory;

Filing Info

• Accession Number: 00149029
• Record Type: Publication
• Source Agency: Transport and Road Research Laboratory (TRRL)
• Report/Paper Numbers: Analytic
• Files: ITRD, TRIS
• Created Date: Jun 17 1977 12:00AM