A Macroscopic Traffic Data-Assimilation Framework Based on the Fourier–Galerkin Method and Minimax Estimation

@article{Tchrakian2013AMT,
  title={A Macroscopic Traffic Data-Assimilation Framework Based on the Fourier–Galerkin Method and Minimax Estimation},
  author={Tigran T. Tchrakian and Sergiy Zhuk},
  journal={IEEE Transactions on Intelligent Transportation Systems},
  year={2013},
  volume={16},
  pages={452-464}
}
In this paper, we propose a new framework for macroscopic traffic state estimation. Our approach is a robust “discretize” then “optimize” strategy, based on the Fourier-Galerkin projection method and minimax state estimation. We assign a Fourier-Galerkin reduced model to a macroscopic model of traffic flow, described by a hyperbolic partial differential equation. Taking into account a priori estimates for the projection error, we apply the minimax method to construct the state estimate for the… CONTINUE READING
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