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.
Physics enhanced residual policy learning (perpl) for safety cruising in mixed traffic platooning under actuator and communication delay,
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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.