Print Email Facebook Twitter An algorithm for estimating the generalized fundamental traffic variables from point measurements using initial conditions Title An algorithm for estimating the generalized fundamental traffic variables from point measurements using initial conditions Author Jamshidnejad, A. (TU Delft Delft Center for Systems and Control) De Schutter, B.H.K. (TU Delft Team Bart De Schutter) Department Delft Center for Systems and Control Date 2017 Abstract Fundamental macroscopic traffic variables (flow, density, and average speed) have been defined in two ways: classical (defined as either temporal or spatial averages) and generalized (defined as temporal-spatial averages). In the available literature, estimation of the generalized variables is still missing. This paper proposes a new efficient sequential algorithm for estimating the generalized traffic variables using point measurements. The algorithm takes into account those vehicles that stay between two consecutive measurement points for more than one sampling cycle and that are not detected during these sampling cycles. The algorithm is introduced for single-lane roads first, and is extended to multi-lane roads. For evaluation of the proposed approach, Next Generation SIMulation (NGSIM) data, which provides detailed information on trajectories of the vehicles on a segment of the interstate freeway I-80 in San Francisco, California is used. The simulation results illustrate the excellent performance of the sequential procedure compared with other approaches. Subject Generalized traffic variablespoint measurementssequential procedure To reference this document use: http://resolver.tudelft.nl/uuid:0916bbce-caec-4392-b841-d3020b6e09cb DOI https://doi.org/10.1080/21680566.2017.1279991 ISSN 2168-0566 Source Transportmetrica B: Transport Dynamics, 6 (2018) (4), 251-285 Part of collection Institutional Repository Document type journal article Rights © 2017 A. Jamshidnejad, B.H.K. De Schutter Files PDF An_algorithm_for_estimating_....pdf 3.72 MB Close viewer /islandora/object/uuid:0916bbce-caec-4392-b841-d3020b6e09cb/datastream/OBJ/view