Traffic state estimation based on Eulerian and Lagrangian observations in a mesoscopic modeling framework

- The lagrangian-space formulation of the LWR model is the most appropriate for assimilating Eulerian and Lagrangian observations.
- We propose original data assimilation methodology capable of assimilating both types of data in a unique framework based on traffic flow theory fundamentals.
- We demonstrate the validity of the proposed method based on simulated scenarios.

The paper proposes a model-based framework for estimating traffic states from Eulerian (loop) and/or Lagrangian (probe) data. Lagrangian-Space formulation of the LWR model adopted as the underlying traffic model provides suitable properties for receiving both Eulerian and Lagrangian external information. Three independent methods are proposed to address Eulerian data, Lagrangian data and the combination of both, respectively. These methods are defined in a consistent framework so as to be implemented simultaneously. The proposed framework has been verified on the synthetic data derived from the same underlying traffic flow model. Strength and weakness of both data sources are discussed. Next, the proposed framework has been applied to a freeway corridor. The validity has been tested using the data from a microscopic simulator, and the performance is satisfactory even for low rate of probe vehicles around 5%.

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