IMPLEMENTING A KALMAN FILTERING DYNAMIC O-D ALGORITHM WITHIN PARAMICS : ANALYSING QUADSTONE WON EFFORTS FOR THE DYNAMIC O-D ESTIMATION PROBLEM

This paper describes research in which a Kalman filtering (KF) algorithm was implemented for the dynamics and prediction of network origin destination (OD) matrices with only the traffic simulator Paramics. The paper describes the four advanced programming interfaces (APIs) that were developed in order to implement the KF algorithm within Paramics. The paper also discusses the proposed Quadstone (developer of Paramics) approach for developing a dynamic origin destination (O-D) estimation procedure.

  • Availability:
  • Supplemental Notes:
    • Publication Date: May 2003. California PATH Program, Institute of Transportation Studies University of California, Berkeley CA. Remarks: Also available online through the PATH Web site <www.path.berkeley.edu>. Format: website
  • Corporate Authors:

    University of California, Irvine

    Institute of Transportation Studies
    4000 Anteater Instruction and Research Building
    Irvine, CA  United States  92697

    University of California, Berkeley

    California PATH Program, Institute of Transportation Studies
    Richmond Field Station, 1357 South 46th Street
    Richmond, CA  United States  94804-4648

    California Department of Transportation

    1120 N Street
    Sacramento, CA  United States  95814
  • Authors:
    • Garcia, Reinaldo C
  • Publication Date: 2003

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 00962380
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Report/Paper Numbers: UCB-ITS-PWP-2003-8
  • Files: PATH, STATEDOT
  • Created Date: Sep 2 2003 12:00AM