  Future urban air mobility systems are expected to be operated by rideshare
companies as fleets, which will require fully autonomous air traffic control
systems and an order of magnitude increase in airspace capacity. Such a system
must not only be safe, but also highly responsive to customer demand. This
paper proposes the air traffic network problem (ATNP), which models the
optimization problem of future cooperative air taxi networks. We propose a
three-phase decision making model that efficiently assigns vehicles to
passengers, determines flight levels to reduce collision risk, and resolves
aircraft conflicts by selectively applying Monte Carlo tree search. We develop
a simulator for the ATNP and show that our approach has increased safety and
reduced passenger waiting time compared to greedy and first-dispatch protocols
over potential vertiport layouts across the Bay Area and New York City.
