Abstract:
Dynamic Demand and Capacity Balancing (dDCB) focuses on reducing the
existent gap between the Air Traffic Flow and Capacity Management (ATFCM)
and the Air Traffic Control (ATC) activities by introducing a more dynamic
management of the airspace resources. This dynamism could be achieved by the
application of Short-Term ATFCM Measures (STAM) that consists of detecting
potential hotspots, identifying the flights producing the complexity, and applying
minor changes to selected flights.
This thesis presents a research about the application of STAM in a Multi-Airport
System (MAS). Firstly, it is proposed an Operational Concept (OpsCon) designed
to apply those STAMs that suggest changes in the take-off time of selected flights
(temporal displacements in the planned trajectory).
The operational concept is tested by real-time simulations (including the human-
in-the-loop) with the objective of evaluating the performance of the ground
ATCOs while dealing with most of the uncertainties produced before take-off.
Subsequently, it is proposed a methodology that characterizes and evaluates the
performance of the aircraft operation in a complex systemized TMA based on the
study of its standard routes and their actual traffic in order to reduce the
uncertainties after take-off.
The process is composed of two main components. The first component identifies
recurrent deviation patterns by comparing the Spatio-Temporal (S-T) differences
between the actual and planned trajectories.
The second component identifies and characterizes concurrence events based
on the analysis of the standard routes and the along-track deviation derived from
the first component with the objective to analyse the causes that produce
recurrent patterns in the terminal airspace.
The developed framework is applied to a study case of a representative MAS.
The quantitative effectiveness of the framework is derived by simulations using
historical traffic data samples of the London TMA.
