Extracting the topology of urban airspace through graph abstraction

Abstract

With the rapid adoption of the operational concept of Unmanned Aerial Systems (UAS) in urban airspace, there is an increased focus on the spatial extent that Unmanned Aircraft (UA) can safely navigate. Urban airspace is full of intrinsic risks associated with several factors, including but not limited to unpredictable microclimates, radio-frequency disturbances and electro-magnetic interferences. For safe and efficient use of airspace, it is imperative to proactively assess the availability of airspace volumes to accommodate large-scale operations. In this paper, we highlight that urban airspace is a unique environment where highly obstructed (complex topology) and sparsely structured (simple topology) regions coexist. The presence of static obstacles and required separation from those obstacles create particular spatial structures, such as narrow passages, islands and funnels, throughout the airspace. Considering that not only throughput capacity of airspace but also complexity of path planning is highly dependent on the topology of a navigable space, we propose a new airspace assessment approach to extract the topology of airspace using computational geometry techniques. We focus on identifying geospatial locations suitable for high density UAS operations as well as examining spatial contiguity between those locations in highly urbanized areas. In doing so, we define segment as an airspace region that is wide enough for multiple vehicles to simultaneously pass through. Low-altitude urban airspace is abstracted into a compact and informative graph structure called segment graph that summarizes segment connectivity in the horizontal and vertical dimension. The proposed method shows that the geometry of low-altitude airspace is fundamentally different from that of conventional highaltitude airspace and can provide a useful basis for airspace design and management within lowaltitude urban environments.