A second-order Aw-Rascle-Zhang physics-informed model reconstructs traffic density from sparse trajectories more accurately and robustly than first-order methods in non-equilibrium conditions, though estimating equilibrium velocity causes instability in transient regimes.
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Second Order Physics-Informed Learning of Road Density using Probe Vehicles
A second-order Aw-Rascle-Zhang physics-informed model reconstructs traffic density from sparse trajectories more accurately and robustly than first-order methods in non-equilibrium conditions, though estimating equilibrium velocity causes instability in transient regimes.