Assessment of the autonomous air traffic control resolution tool for free flight

In order to improve air traffic coordination and planning, future ATMs need to allow various users of a particular airspace, timely access to the same data. Already, advances in technology, in the form of enhanced tools assisting airspace controllers and users, have enabled the sharing of high fidelity data across systems and improving standards in air traffic safety and throughput. To-date most of these tools are human- centered. The thesis presents a set of human-centered tools which use a common data structure for: detecting and resolving air traffic congestion, conflict detection and resolution and limiting the search space, in a ‘free-flight environment’. The chosen data-structure represents sets of discretized and indexed volumes of airspace, called ‘bins’, which store all the information necessary for operation in different airspace sectors. An algorithm using these bins has been proposed in the thesis. A large number of experiments carried out on a single purpose simulator, developed as a part of the thesis, have resulted in a set of optimized conflict free routes, which amply illustrate both medium and short-term detection of congestion and conflicts and provide solutions for their avoidance, across a large airspace volume that contains several airspace sectors, efficiently. In addition, a limited set of experiments, carried out with qualified ATCs in the loop, highlights the fact that the proposed ATM tool does assist them in better visualizing traffic flow and encounter geometry(ies).