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- W1915536038 abstract "In this paper, we develop a data-assimilation algorithm for a macroscopic model of traffic flow. The algorithm is based on the Discontinuous Galerkin Method and Minimax Estimation, and is applied to a macroscopic model based on a scalar conservation law. We present numerical results which demonstrate the shock-capturing capability of the algorithm under high uncertainty in the initial traffic condition, using only sparse measurements, and under time-dependent boundary conditions. The latter makes it possible for estimation to be performed on merge/diverge sections, allowing the possibility of the deployment of the algorithm to road networks." @default.
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- W1915536038 date "2015-09-01" @default.
- W1915536038 modified "2023-09-24" @default.
- W1915536038 title "Robust Traffic Density Estimation Using Discontinuous Galerkin Formulation of a Macroscopic Model" @default.
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- W1915536038 doi "https://doi.org/10.1109/itsc.2015.347" @default.
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