Estimation of Mean and Covariance of Stochastic Multi-class OD Demands from Classified Traffic Counts

Hu Shao, Hing Keung William Lam, Agachai Sumalee, Martin L. Hazelton

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Published by Elsevier B.V. This paper proposes a new model to estimate the mean and covariance of stochastic multi-class (multiple vehicle classes) origin-destination (OD) demands from hourly classified traffic counts throughout the whole year. It is usually assumed in the conventional OD demand estimation models that the OD demand by vehicle class is deterministic. Little attention is given on the estimation of the statistical properties of stochastic OD demands as well as their covariance between different vehicle classes. Also, the interactions between different vehicle classes in OD demand are ignored such as the change of modes between private car and taxi during a particular hourly period over the year. To fill these two gaps, the mean and covariance matrix of stochastic multi-class OD demands for the same hourly period over the year are simultaneously estimated by a modified lasso (least absolute shrinkage and selection operator) method. The estimated covariance matrix of stochastic multi-class OD demands can be used to capture the statistical dependency of traffic demands between different vehicle classes. In this paper, the proposed model is formulated as a non-linear constrained optimization problem. An exterior penalty algorithm is adapted to solve the proposed model. Numerical examples are presented to illustrate the applications of the proposed model together with some insightful findings on the importance of covariance of OD demand between difference vehicle classes.
Original languageEnglish
Pages (from-to)192-211
Number of pages20
JournalTransportation Research Procedia
Volume7
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • classified traffic counts
  • covariance matrix
  • multiple vehicle class
  • OD demand estimation

ASJC Scopus subject areas

  • Transportation

Cite this