A Kalman filter for quasi-dynamic o-d flow estimation/updatingA Kalman filter for quasi-dynamic o-d flow estimation/updating Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2019-05-272018enThis 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.http://creativecommons.org/licenses/by/4.0/IEEE Transactions on Intelligent Transportation Systems19113604-3612 Marzano Vittorio Papola Andrea Simonelli Fulvio Papageorgiou Markos Παπαγεωργιου Μαρκος Institute of Electrical and Electronics Engineers Kalman filter O-d estimation/updating Quasi-dynamic estimation Extended Kalman filters Intelligent systems Interactive computer systems