Evaluation of advanced Air Traffic Management concepts is a
challenging task due to the limitations in the existing scenario
generation methodologies. Their rigorous evaluation on safety
metrics, in a variety of complex scenarios, can provide an insight
into their performance, which can help improve upon them while
developing new ones. In this work, I propose an air traffic
simulation system, with a novel representation of airspace, which
can prototype advanced ATM concepts. I then propose a novel
evolutionary computation methodology to algorithmically generate
conflict scenarios of increasing complexity in order to evaluate
conflict detection algorithms. I illustrate the methodology by
quantitative evaluation of three conflict detection algorithms on
safety metrics. I then propose the use of data mining techniques
for the discovery of interesting relationships, that may exist
implicitly, in the algorithm's performance data. This relationships
are formed as a predictive model for algorithm's vulnerability
which can then be included in an ensemble that can minimize the
overall vulnerability of the system.
General
| Imprint: |
VDM Verlag
|
| Country of origin: |
Germany |
| Release date: |
March 2009 |
| First published: |
March 2009 |
| Authors: |
Sameer Alam
|
| Dimensions: |
229 x 152 x 17mm (L x W x T) |
| Format: |
Paperback - Trade
|
| Pages: |
288 |
| ISBN-13: |
978-3-639-02255-1 |
| Categories: |
Books
Promotions
|
| LSN: |
3-639-02255-6 |
| Barcode: |
9783639022551 |
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