Visible to the public Low Altitude Flight ManagementConflict Detection Enabled

Low Altitude Flight Management
Prepared by Claire Tomlin, University of California, Berkeley

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Recently, there has been an immense surge of interest in using unmanned and manned autonomous vehicles, also known as drones, for civil applications. Through projects such as Amazon Prime Air, Google Project Wing, and Airbus’s Project Vahana, many companies are investing heavily into drone services such as commercial package delivery, flying taxi service, aerial surveillance, emergency supply delivery, videography, and search and rescue. Other companies involved in drone development include Airware, Iris Automation, and Uber; in addition, this movement towards drones has been happening world-wide, in the US, Canada, China, and most recently the UAE.

Since drones are envisioned to fly in the low altitude space of about 200 to 500 feet, the allocation of this airspace resource must be done carefully maximize safety, efficiency, and ease of human participation. As a result, new infrastructures are needed.  We propose to develop tools for government agencies to establish such infrastructures in a principled way. Our tools will rely on a combination of systems analysis and publicly available data from sources including NASA, FAA, ArcGIS, and NOAA.  In collaboration with NASA Ames and Armstrong Flight Research Centers in recent years, we have been involved in the design of low altitude airspace infrastructure:  we proposed the concept of air highways, or virtual pathways in the airspace. Air highways provide a scalable and intuitive way for managing a large number of drones. These paths can be updated in real-time according to changes in the airspace. Trunks and branches of air highways, similar to ground-based highway systems, naturally emerge.

For regional and city-level drone infrastructure, the next step towards a complete and practical infrastructure would be to consider multiple levels of air highways, possibly separated by altitude. The goals in the design of these highway networks include connectivity between cities, efficient and safe use of different altitude levels, and flexibility with respect to unknown or changing conditions in the airspace. Many practical details, such as the locations of and rules for intersections and exits, need to be designed.

For “last-mile” drone planning, one potential solution would be to use a priority-based method for reserving space-time for each drone. However, unlike traditional route planning methods which reserve a large block of the airspace for a long period of time, we believe that adopting a fine-grain space-time reservation would greatly improve throughput. Last-mile operations will involve drones flying in close proximity to humans and other important assets on the ground. Therefore, real-time data will be essential for assessing risks of flight routes. Data needed by drones and drone operators for planning include city zoning maps which provide priors for human occupancy, cellular traffic data which can be used to infer human occupancy, and road traffic data which is useful for predicting day-to-day human movement.

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