Multi-criteria air traffic flow optimisation including uncertainty

Assaad, Z 2019, Multi-criteria air traffic flow optimisation including uncertainty, Doctor of Philosophy (PhD), Engineering, RMIT University.


Document type: Thesis
Collection: Theses

Attached Files
Name Description MIMEType Size
Assaad.pdf Thesis application/pdf 5.55MB
Title Multi-criteria air traffic flow optimisation including uncertainty
Author(s) Assaad, Z
Year 2019
Abstract Air Traffic Control (ATC) arose from the need to ensure safe separation between civil aircraft. Air Traffic Flow Management (ATFM) arose from the need to manage traffic flow conditions and demand. Both functions were developed in response to an arising need and not in anticipation of that need. Resultantly, the progression of the two functions has been met with significant limitations, as technology and practices fail to cope with increased demand. The increased number of aircraft movements far exceeded the development of ATFM technology, practices and procedures. The result of this is a system that delivers on passenger safety, but lacks in efficiency. Currently, civil aviation is burdened with myriad of issues including, but not limited to, high traffic demands, increased controller workload, limited available airspace capacity (the definition of airspace capacity is dependent on controller workload in addition to airspace) and dated technology. The issues that emerge from these limitations include, flight delays and uncertainty in aircraft trajectories.

This research focuses on more efficient and effective means of managing and utilising available information with the intention of reducing uncertainty in aircraft trajectories and improving decision making based on available information. This research presents a non-linear optimisation problem as an applied theory in support of the research aims. A multi-criteria weighted objective function is developed. The implementation of weights reflects a strategic prioritising approach to decision making. Dynamic re-optimisation is introduced within this research, building on the idea of incorporating more information into decision making and how information can be better utilised. Finally, a Monte Carlo simulation is explored alongside the multi criteria optimisation model in an attempt to establish a means of obtaining a statistical analysis of possible solutions within a given scenario.

This research produced results that demonstrated the benefits of the proposed theory. Fuel consumption savings were achieved when optimising for minimum overall fuel consumption independently. These savings were a result of a number of factors including changes to the flight trajectory, lower velocity during cruise and flying at higher altitudes. Once departure and arrival times were introduced into the objective function, efficiency in trajectories was evident through minimised delays in departure and arrival timings in addition to fuel consumption. Dynamic re-optimisation introduced a level of strategic decision making. The results indicated the benefits to efficiency that can be achieved from incorporating strategic decision making and reducing uncertainty. Overall, the results of this research support the research aims and objectives and provide answers to the proposed research questions.
Degree Doctor of Philosophy (PhD)
Institution RMIT University
School, Department or Centre Engineering
Subjects Aerospace Engineering not elsewhere classified
Keyword(s) Aviation
Traffic flow management
Uncertainty
Efficiency
Air traffic management
Versions
Version Filter Type
Access Statistics: 40 Abstract Views, 9 File Downloads  -  Detailed Statistics
Created: Tue, 06 Aug 2019, 16:39:42 EST by Adam Rivett
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us