DGAE is a new inductive graph model using directed DEFP, latent encoding, and physics-guided pattern-specific propagation to outperform prior methods on sparse-sensor freeway traffic estimation.
Physics-informed deep learning for traffic state estimation: A hybrid paradigm informed by second-order traffic models
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Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach
DGAE is a new inductive graph model using directed DEFP, latent encoding, and physics-guided pattern-specific propagation to outperform prior methods on sparse-sensor freeway traffic estimation.