Multi-Agent Autonomous On-Demand Free Flight Operations in Urban Air Mobility

In urban air mobility (UAM), flying with electrical vertical takeoff and landing (eVTOL) aircraft will bring fundamental changes to city infrastructures and daily commutes. In order to enable safe and efficient autonomous on-demand free flight operations for the eVTOL aircraft in UAM, a centralized computational guidance algorithm is proposed and analyzed for multi cooperative aircraft. The approach proposed in this paper is to formulate this problem as a MarkovDecisionProcess (MDP) and solve it using anonline algorithmMonteCarloTree Search (MCTS). A coordination mechanism is designed to manage multiple cooperative aircraft. By generating real-time actions for all the cooperative aircraft to follow, the algorithm can guide all the aircraft to their respective destinations while avoiding potential conflicts between them. For the sake of illustration, a free flight airspace simulator is created to test the performance of this algorithm. Results show that this algorithm can help all the aircraft reach their trip destinations while only having 0.2% conflicts during the flights.