Urban air mobility is a rapidly growing field of research. While drones or unmanned aerial vehicles have been operated mainly in the private and military sector in the past, an increasing range of opportunities is opening up for commercial applications. A new multitude of passenger-carrying drone or air taxi concepts promises to fulfill the dream of flying above congested urban areas. While early research has been focusing on vehicle development, solutions for urban air traffic management are lagging behind. This paper collects and reviews the main findings of past urban-air-mobility-related research projects at the German Aerospace Center (DLR) to serve as a basis for ongoing research from an air traffic management perspective.

International parcel services as well as online retailers are planning to install their own delivery drone fleets in the foreseeable future. Given the typical volumes of such businesses it is likely that this poses huge demands on the urban airspace in terms of capacity and conflict resolution. Current UTM concepts devise means to automatically detect and solve conflicts in smaller scales. However, it is yet unanswered to what degree a conflict-free operation of hundreds or thousands of drones occupying the same airspace is possible. In this paper we present a generic simulation framework that can load a given urban airspace with a specified demand or frequency of delivery drones. Based on actual street map data the user can specify a delivery area, a regular or randomized delivery schedule and a number of logistic centers to start from. Random destinations are then picked from the street maps and drones are scheduled to service these destinations. Further, the system analyzes the pre-planned drone schedule for conflicts and tries to resolve these conflicts without delaying individual drones too much. We detail statistics on how responsive the system is to unexpected events like emergency helicopters. The results give first insights, to what degree automatic de-conflicting solutions may work in urban areas.