A Practical Proposal for Using Origin-Destination Matrices in the Analysis, Modeling and Simulation for Traffic Management

Dealing with traffic demand trip matrices to feed models that support traffic management decisions is still a problem that deserves research into finding practical solutions in the short term horizon, before future developments become available. This paper analyzes the role of OD (Origin and Destination) matrices in the framework of Analysis, Modeling and Simulation (AMS), namely when moving from static OD matrices to the time-sliced OD matrices required by (AMS) applications. The paper reviews some of the time-slicing approximations used in practice to estimate OD matrices in adjustment procedures, and it proposes an improvement to the bilevel approach by solving the lower level problem through Dynamic User Equilibrium. A practical framework is defined, where the off-line procedure is incorporated to efficiently initialize on-line Kalman filter approaches that exploit measurements from Information and Communication Technologies (ICT). The computational performance of the resulting Kalman models makes them capable of real-time applications.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB40 Transportation Demand Forecasting. Alternate title: Practical Proposal for Use of Origin-Destination Matrices in Analysis, Modeling, and Simulation Framework for Traffic Management
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Barceló, J
    • Montero, L
    • Bullejos, M
    • Linares, M P
  • Conference:
  • Date: 2014


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References;
  • Pagination: p14
  • Monograph Title: TRB 93rd Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01520046
  • Record Type: Publication
  • Report/Paper Numbers: 14-3793
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 26 2014 10:13AM