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Title	Autonomous Aerial Mobility Learning For Drone-Taxi Flight Control
ID_Doc	11445
Authors	Yun W.J.; Ha Y.J.; Jung S.; Kim J.
Year	2021
Published	International Conference on ICT Convergence, 2021-October
DOI	http://dx.doi.org/10.1109/ICTC52510.2021.9620751
Abstract	In smart city scenarios, the use of unmanned aerial vehicle (UAV) networks is one of actively discussed technologies. In this paper, we consider the scenario where carpoolable UAV-based drone taxis configure their optimal routes to deliver packages and passengers in an autonomous and efficient way. In order to realize this application with drone-taxi UAV networks, a multiagent deep reinforcement learning (MADRL) based algorithm is designed and implemented for the optimal route configuration. In the corresponding MADRL formulation, the drone-taxi related states, actions, and rewards are defined in this paper. Lastly, we confirm that our proposed algorithm achieves desired results. © 2021 IEEE.
Author Keywords	Drone-Taxi; Multi-Agent Deep Reinforcement Learning (MADRL); Reinforcement Learning; Smart City; Unmanned Aerial Vehicle (UAV)

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