Examining the relative costs and benefits of shifting the locus of control in a novel air traffic management environment via multi-agent dynamic analysis and simulation
Bigelow, Matthew Steven
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The current air traffic management system has primarily evolved via incremental changes around historic control, navigation, and surveillance technologies. As a result, the system as a whole is not capable of handling air traffic capacities well beyond current levels, despite recent developments, such as ADS-B, that could potentially enable new concepts of operation. Methods of analyzing air traffic for safety and performance have also evolved around current-day operating constructs. Thus, attempts to examine future systems tend to use different analysis methods developed for each. Most notably, questions of 'locus of control' - whether the control should be centralized or de-centralized and distributed - have no common framework by which to judge relative costs and benefits. For instance, a completely centralized control paradigm is commonly asserted to provide an airspace-wide optimal traffic management solution due to a more complete picture of the state of the airspace, whereas a completely decentralized control paradigm is commonly asserted to provide a more user-specific optimal traffic management solution, to distribute the traffic management workload, and potentially be more robust. Given the disparate nature of these assertions and the different types of evaluations commonly used with each, some shared framework must be established to allow comparisons between very different control paradigms. The objective of this thesis was to construct a formal framework to examine the relative costs and benefits of shifting the locus of control in a novel air traffic management environment. This framework provides useful definitions and quantitative measures of flexibility and robustness with respect to various control paradigms ranging between, and including, completely centralized and completely decentralized concepts of operation. Multi-agent dynamic analysis and simulation was used to analyze the range of dynamics found in the different control paradigms. In addition, futuristic air traffic management concepts were developed in sufficient detail to demonstrate the framework. In other words, the objectives were met because the framework was demonstrated to have the ability to identify (or dispel) hypotheses about the relative costs and benefits of locus of control.