Despite technological advances, the Air Traffic Management system is still, to a large extent, built around a rigidly structured airspace and a centralized, mostly human-operated system architecture. Even though this system has operated reliably for a many years, the increasing demand for air travel is beginning to stress it to its limits. Air-Traffic in Europe is projected to double every 10 to 14 years; even higer rates of growth are expected in the U.S., Asia and for trans-oceanic flights. This increase is likely to cause both safety and performance degradation in the near future, and place an additional burden on the already overloaded human operators. Increase workload is believed, for example, to be one of the major causes that contributed to a 33% increase in controller errors in the U.S. over the period 1996-2000.
This video is to demonstrate the workload of an Air Traffic Controller in Heathrow.
In the current organization of the Air Traffic Management (ATM) system the centralized Air Traffic Control (ATC) is in complete control of air traffic and ultimately responsible for safety. Before take off, aircraft file flight plans which cover the entire flight. During the flight, ATC sends additional instructions to them, depending on the actual traffic, to improve traffic flow and avoid dangerous encounters. The primary concern of ATC is to maintain safe separation between the aircraft.
The main aim of our research is to facilitate the work of ATC by automation. Towards this direction, our research can be divided in the following areas:
In this area, our goal is to produce an accurate model (from the point of view of the air traffic controller) to simulate aircraft flights.
In this area, methods for predicting accurately the future position of aircraft are developed.
This refers to control imperceptible from the Air Traffic Controller (ATCo), mainly focused to reduce ATCo's workload.
In this area, automated methods for resolving conflicts in ATC are developed.
In this area methods for tracking '4D' constraints and conflict resolution algorithms that respect these constraints will be developed.