Estimation of mean and covariance of stochastic multi-class OD demands from classified traffic counts

dc.contributor.authorShao, Hu
dc.contributor.authorLam, William H.K.
dc.contributor.authorSumalee, Agachai
dc.contributor.authorHazelton, Martin L.
dc.date.accessioned2026-08-06T10:12:15Z
dc.date.available2026-08-06T10:12:15Z
dc.date.issued2015-10-01
dc.description.abstractThis 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.
dc.identifier.citationTransportation Research Part C Emerging Technologies, 59, 92-110, 2015
dc.identifier.doi10.1016/j.trc.2015.05.017
dc.identifier.issn0968090X
dc.identifier.other2-s2.0-84942989782
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/6429
dc.sourceTransportation Research Part C Emerging Technologies
dc.subjectClassified traffic counts
dc.subjectCovariance matrix
dc.subjectMultiple vehicle class
dc.subjectOD demand estimation
dc.titleEstimation of mean and covariance of stochastic multi-class OD demands from classified traffic counts
dc.typeArticle

Files

Collections