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dc.contributor.authorWeinert, Andrew Josephen_US
dc.date.accessioned2016-03-16T18:51:27Z
dc.date.available2016-03-16T18:51:27Z
dc.date.issued2015
dc.identifier.urihttps://hdl.handle.net/2144/15208
dc.description.abstractDeveloping a collision avoidance system that can meet safety standards required of commercial aviation is challenging. A dynamic programming approach to collision avoidance has been developed to optimize and generate logics that are robust to the complex dynamics of the national airspace. The current approach represents the aircraft avoidance problem as Markov Decision Processes and independently optimizes a horizontal and vertical maneuver avoidance logics. This is a result of the current memory requirements for each logic, simply combining the logics will result in a significantly larger representation. The "curse of dimensionality" makes it computationally inefficient and unfeasible to optimize this larger representation. However, existing and future collision avoidance systems have mostly defined the decision process by hand. In response, a simulation-based framework was built to better understand how each potential state quantifies the aircraft avoidance problem with regards to safety and operational components. The framework leverages recent advances in signals processing and database, while enabling the highest fidelity analysis of Monte Carlo aircraft encounter simulations to date. This framework enabled the calculation of how well each state of the decision process quantifies the collision risk and the associated memory requirements. Using this analysis, a collision avoidance logic that leverages both horizontal and vertical actions was built and optimized using this simulation based approach.en_US
dc.language.isoen_US
dc.rightsAttribution 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAerospace engineeringen_US
dc.subjectAviationen_US
dc.subjectControlen_US
dc.subjectEntropyen_US
dc.subjectOptimizationen_US
dc.subjectSafetyen_US
dc.subjectSimulationen_US
dc.titleAn information theoretic approach for generating an aircraft avoidance Markov decision processen_US
dc.typeThesis/Dissertationen_US
dc.date.updated2016-03-12T07:15:21Z
etd.degree.nameMaster of Scienceen_US
etd.degree.levelmastersen_US
etd.degree.disciplineElectrical & Computer Engineeringen_US
etd.degree.grantorBoston Universityen_US


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International