Institutional Repository
Technical University of Crete
EN  |  EL

Search

Browse

My Space

A Kalman filter for quasi-dynamic o-d flow estimation/updating

Marzano Vittorio, Papola Andrea, Simonelli Fulvio, Papageorgiou Markos

Simple record


URIhttp://purl.tuc.gr/dl/dias/D29409BD-0AB7-477A-9310-ACBCA2E94796-
Identifierhttps://doi.org/10.1109/TITS.2018.2865610-
Identifierhttps://ieeexplore.ieee.org/document/8454761-
Languageen-
Extent9 pagesen
TitleA Kalman filter for quasi-dynamic o-d flow estimation/updatingen
CreatorMarzano Vittorioen
CreatorPapola Andreaen
CreatorSimonelli Fulvioen
CreatorPapageorgiou Markosen
CreatorΠαπαγεωργιου Μαρκοςel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryThis paper proposes an extended Kalman filter for quasi-dynamic estimation/updating of o-d flows from traffic counts. The quasi-dynamic assumption-that is considering constant o-d shares across a reference period, whilst total flows leaving each origin may vary for each sub-period within the reference period-has been proven already realistic and effective in off-line o-d flows estimation using generalized least squares estimators. The specification of the state variables and of the corresponding transition and measurement equations of a quasi-dynamic extended Kalman filter are illustrated, and a closed-form linearization is presented under the assumption of an uncongested network and error-free assignment matrix. Results show satisfactory performance and parsimonious computational burden on real-size networks.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2019-05-27-
Date of Publication2018-
SubjectKalman filteren
SubjectO-d estimation/updatingen
SubjectQuasi-dynamic estimationen
SubjectExtended Kalman filtersen
SubjectIntelligent systemsen
SubjectInteractive computer systemsen
Bibliographic CitationV. Marzano, A. Papola, F. Simonelli and M. Papageorgiou "A Kalman filter for quasi-dynamic o-d flow estimation/updating," IEEE Trans. Intell. Transp. Syst., vol. 19, no. 11, pp. 3604-3612, Nov. 2018. doi: 10.1109/TITS.2018.2865610el

Services

Statistics