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Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/D29409BD-0AB7-477A-9310-ACBCA2E94796 | ||
| Year | 2018 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
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| Bibliographic Citation | V. 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.2018.2865610 https://doi.org/10.1109/TITS.2018.2865610 | ||
| Appears in Collections |
This 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.
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