  This paper presents a real-time trajectory planning framework for Urban Air
Mobility (UAM) that is both safe and scalable. The proposed framework employs a
decentralized, free-flight concept of operation in which each aircraft
independently performs separation assurance and conflict resolution, generating
safe trajectories by accounting for the future states of nearby aircraft. The
framework consists of two main components: a data-driven reachability analysis
tool and an efficient Markov Decision Process (MDP) based decision maker. The
reachability analysis over-approximates the reachable set of each aircraft
through a discrepancy function learned online from simulated trajectories. The
decision maker, on the other hand, uses a 6-degrees-of-freedom guidance model
of fixed-wing aircraft to ensure collision-free trajectory planning.
Additionally, the proposed framework incorporates reward shaping and action
shielding techniques to enhance safety performance. The proposed framework is
evaluated through simulation experiments involving up to 32 aircraft in a UAM
setting, with performance measured by the number of Near Mid Air Collisions
(NMAC) and computational time. The results demonstrate the safety and
scalability of the proposed framework.
