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

Author:

Zhou Xuesong1,Qin Xiao1,Mahmassani Hani S.1

Affiliation:

1. Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn L. Martin Hall, College Park, MD 20742

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.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference13 articles.

1. Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts

2. TavanaH. Internally Consistent Estimation of Dynamic Network Origin–Destination Flows from Intelligent Transportation Systems Data Using Bi-Level Optimization. Ph.D. dissertation. University of Texas at Austin, 2001.

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