Estimation of dynamic assignment matrices and OD demands using adaptive Kalman filtering

Shou Ren Hu, Samer M. Madanat, James V. Krogmeier, Srinivas Peeta

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this research was to develop a dynamic model for the on-line estimation and prediction of freeway users' origin-destination (OD) matrices. In this paper, we present a Kalman Filtering algorithm that uses time-varying assignment matrices generated by using a mesoscopic traffic simulator. The use of a traffic simulator to predict time-varying travel time model parameters was shown to be promising for the determination of dynamic OD matrices for a freeway system. Moreover, the issues of using time-varying model parameters, effects of incorporating different sources of measurements and the use of adaptive estimation are addressed and investigated in this research.

Original languageEnglish (US)
Pages (from-to)281-300
Number of pages20
JournalITS Journal
Volume6
Issue number3
StatePublished - 2001

Keywords

  • Adaptive filters
  • Kalman Filtering
  • Optimal estimation
  • Origin-destination demands
  • Traffic simulator

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Strategy and Management
  • Management Science and Operations Research

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