SOME STATISTICAL PROBLEMS IN CONNECTION WITH TRAFFIC ASSIGNMENT

This paper gives the approximate joint probability distribution function of the link traffic flows on a network. The knowledge of such distribution function enables us to derive the log-likelihood function for the estimation (with link data) of the traffic diversion parameter, theta, that appears in most stochastic assignment models. It also enables us to perform goodness to fit statistical tests for the validation of traffic assignment methods. Both of these procedures are illustrated with a small numerical example. It is also pointed out that it is possible to calibrate and/or validate a traffic assignment model with incomplete data bases (i.e. When traffic counts are only available on a few of the links of the network).(a) /TRRL/

• Corporate Authors:

  Pergamon Press, Incorporated

  Maxwell House, Fairview Park
  Elmsford, NY  United States  10523
• Authors:
  • Daganzo, C F
• Publication Date: 1977-12

Language

• English

Media Info

• Features: Figures; References;
• Pagination: p. 385-389
• Serial:
  • Transportation Research /UK/
  • Volume: 11
  • Issue Number: 6
  • Publisher: Pergamon Press, Incorporated

Subject/Index Terms

• TRT Terms: Calculation; Distributions (Statistics); Mathematical models; Methodology; Networks; Statistics; Stochastic processes; Traffic assignment; Traffic diversion; Traffic flow
• Uncontrolled Terms: Models; Transportation networks
• ITRD Terms: 6464: Calculation; 6473: Mathematical model; 9102: Method; 6555: Statistics; 679: Traffic assignment; 671: Traffic flow
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I71: Traffic Theory;

Filing Info

• Accession Number: 00174155
• Record Type: Publication
• Source Agency: Transport and Road Research Laboratory (TRRL)
• Report/Paper Numbers: ANALYTIC
• Files: ITRD, TRIS
• Created Date: Jun 28 1978 12:00AM