Abstract:
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).
