Unmanned Traffic Management (UTM) describes a set of systems, services and procedures that will be developed to manage drone (unmanned aircraft systems/unmanned aerial vehicle/remotely piloted aircraft) operations in and around our cities. From surveillance tasks and package delivery through to passenger transport, UTM will be essentially in ensuring safe and efficient use of our airspace. Essentially, UTM is a new air traffic control system for drones with high levels of automation and advanced decision making and control. This research aims to develop powerful and scalable UTM technologies that allow thousands of drones to operate safely in our skies.
This research topic contains multiple areas of investigation including:
Controlling drones on aerial networks – Investigate robust and stable control algorithms that enable multiple drones to coordinate their motion. Example applications include, formation flight, collision avoidance, platooning, flight along intersecting routes and through aerial networks.
Unlocking Urban Airspace for Drone Transport (ARC DECRA) – Investigate manned and unmanned traffic modelling approaches for collision risk analysis to aid airspace design, airspace characterisation, automated flight approval, standards development and tactical mitigation performance requirements.
Near Real Time Air traffic configuration modelling and prediction – Investigate novel representations of air traffic movement, patterns and configurations using machine learning, Markov chains or other methods.