
A deep reinforcement learning-based approach is proposed to enable self-organized and safe arrival of urban air mobility vehicles at vertiports, without the need for centralized control.


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self-organized-arrival-system-for-urban-air-mobility-vehicles-using-deep-reinforcement-learning


Self-Organized Arrival System for Urban Air Mobility Vehicles Using Deep Reinforcement Learning


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The author proposes a reconfigurable intelligent surface (RIS) empowered distributed learning approach to optimize convergence and transmission delay in urban air mobility. By leveraging RIS, the communication network is reshaped to enhance distributed federated learning performance.


ris-empowered-topology-control-for-distributed-learning-in-urban-air-mobility


RIS-empowered Topology Control for Distributed Learning in Urban Air Mobility
