Urban Air Mobility

Urban Air Mobility (UAM) aims to revolutionize urban transportation by integrating electric vertical takeoff and landing (eVTOL) aircraft into existing infrastructure. Current research heavily focuses on optimizing fleet scheduling and air traffic management using techniques like reinforcement learning (particularly graph neural networks and Markov Decision Processes), auction-based mechanisms for vertiport allocation, and multi-agent systems for cooperative control. These advancements are crucial for ensuring safe, efficient, and economically viable UAM operations, impacting both the development of advanced air traffic control systems and the design of future urban transportation networks.