Dynamic Origin-Destination Demand Estimation with Multiday Link Traffic Counts for Planning Applications

Xuesong Zhou, Xiao Qin, Hani S. Mahmassani

Research output: Contribution to journalArticle

50 Scopus citations

Abstract

A dynamic origin-destination demand estimation model for planning applications with real-time link counts from multiple days is presented. Based on an iterative bilevel estimation framework, the upper-level problem is to minimize both the deviation between estimated link flows and real-time link counts and the deviation between estimated time-dependent demand and given historical static demand. These two types of deviations are combined into a weighted objective function, where the weighting value is determined by an interactive approach to obtain the best compromise solution. The single-day formulation is further extended to use link counts from multiple days to estimate the variation in traffic demand over multiple days. A case study based on the Irvine test bed network is conducted to illustrate the methodology and estimate day-to-day demand patterns. The application illustrates considerable benefits in analyzing the demand dynamics with multiday data.

Original languageEnglish (US)
Pages (from-to)30-38
Number of pages9
JournalTransportation Research Record
Issue number1831
DOIs
StatePublished - Jan 1 2003

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering

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