A closed-loop state-centric multi-agent framework for robust passenger load estimation from heterogeneous data streams using physical feasibility enforcement and dynamic trust allocation.
On the limitations of physics-informed deep learning: Illustrations using first-order hyperbolic conservation law-based traffic flow models,
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A Closed-loop, State-centric, Multi-agent Framework for Passenger Load Estimation from Heterogeneous Data Streams
A closed-loop state-centric multi-agent framework for robust passenger load estimation from heterogeneous data streams using physical feasibility enforcement and dynamic trust allocation.