Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17831
Title: Estimation of mean and covariance of peak hour origin-destination demands from day-to-day traffic counts
Authors: Shao, H
Lam, WHK 
Sumalee, A
Chen, A
Hazelton, ML
Keywords: Bi-level optimization problem
Least squares method
OD demand variation
OD estimation
Second-order statistical property
Traffic counts
Issue Date: 2014
Publisher: Pergamon Press
Source: Transportation research. Part B, Methodological, 2014, v. 68, p. 52-75 How to cite?
Journal: Transportation research. Part B, Methodological 
Abstract: This paper proposes a generalized model to estimate the peak hour origin-destination (OD) traffic demand variation from day-to-day hourly traffic counts throughout the whole year. Different from the conventional OD estimation methods, the proposed modeling approach aims to estimate not only the mean but also the variation (in terms of covariance matrix) of the OD demands during the same peak hour periods due to day-to-day fluctuation over the whole year. For this purpose, this paper fully considers the first- and second-order statistical properties of the day-to-day hourly traffic count data so as to capture the stochastic characteristics of the OD demands. The proposed model is formulated as a bi-level optimization problem. In the upper-level problem, a weighted least squares method is used to estimate the mean and covariance matrix of the OD demands. In the lower-level problem, a reliability-based traffic assignment model is adopted to take account of travelers' risk-taking path choice behaviors under OD demand variation. A heuristic iterative estimation-assignment algorithm is proposed for solving the bi-level optimization problem. Numerical examples are presented to illustrate the applications of the proposed model for assessment of network performance over the whole year.
URI: http://hdl.handle.net/10397/17831
ISSN: 0191-2615
EISSN: 1879-2367
DOI: 10.1016/j.trb.2014.06.002
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