Dynamic Capacity Management for Air Traffic Operations in High Density Constrained Urban Airspace

Unmanned Aircraft Systems (UAS) Traffic Management (UTM) is an active research subject as its proposed applications are increasing. UTM aims to enable a variety of UAS operations, including package delivery, infrastructure inspection, and emergency missions. That creates the need for extensive on how incorporate such traffic, conventional methods operations used in Air (ATM) not suitable constrained urban airspace. This paper proposes compares several traffic capacity balancing developed system designed be highly dense, very low-level Three types location-based dynamic management techniques tested: street-based, grid-based, cluster-based. The systems tested by simulating within mixed (constrained open) airspace based city Vienna at five different densities. Results show that using local, area-based clustering improves safety, efficiency, metrics, especially when simulated or historical data used.