Air Traffic Simulation and Modelling : Evolving Complex Scenario for Evaluating Advanced Air Traffic Management Concepts

Sameer Alam

ISBN 10: 3639022556 / ISBN 13: 9783639022551

Verlag: VDM Verlag Dr. Müller, 2009

Beschreibung

nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9783639022551

Bibliografische Details

Titel: Air Traffic Simulation and Modelling : ...

Verlag: VDM Verlag Dr. Müller

Erscheinungsdatum: 2009

Einband: Taschenbuch

Zustand: Neu

Über diesen Titel

Inhaltsangabe:

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.