| Title | Autonomous Aerial Mobility Learning for Drone-Taxi Flight Control |
|---|---|
| ID_Doc | 41601 |
| Authors | Yun, WJ; Ha, YJ; Jung, S; Kim, J |
| Title | Autonomous Aerial Mobility Learning for Drone-Taxi Flight Control |
| Year | 2021 |
| Published | |
| 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 multi-agent 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. |
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