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.
Traffic state estimation on highway: A comprehensive survey
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.