A 3D game theoretical framework for the evaluation of unmanned aircraft systems airspace integration concepts

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buir.contributor.authorAlbaba, Berat Mert
buir.contributor.authorYıldız, Yıldıray
buir.contributor.orcidAlbaba, Mert Berat|0000-0002-3406-8412
dc.citation.epage103417-22en_US
dc.citation.issueNumber2021en_US
dc.citation.spage103417-1en_US
dc.citation.volumeNumber133en_US
dc.contributor.authorAlbaba, Berat Mert
dc.contributor.authorMusavi, Negin
dc.contributor.authorYıldız, Yıldıray
dc.date.accessioned2021-12-10T11:53:59Z
dc.date.available2021-12-10T11:53:59Z
dc.date.issued2021-10-23
dc.departmentDepartment of Mechanical Engineeringen_US
dc.description.abstractPredicting the outcomes of integrating Unmanned Aerial System (UAS) into the National Airspace System (NAS) is a complex problem, which is required to be addressed by simulation studies before allowing the routine access of UAS into the NAS. This paper focuses on providing a 3-dimensional (3D) simulation framework using a game-theoretical methodology to evaluate integration concepts using scenarios where manned and unmanned air vehicles co-exist. In the proposed method, the human pilot interactive decision-making process is incorporated into airspace models which can fill the gap in the literature where the pilot behavior is generally assumed to be known a priori. The proposed human pilot behavior is modeled using a dynamic level-k reasoning concept and approximate reinforcement learning. The level-k reasoning concept is a notion in game theory and is based on the assumption that humans have various levels of decision making. In the conventional “static” approach, each agent makes assumptions about his or her opponents and chooses his or her actions accordingly. On the other hand, in the dynamic level-k reasoning, agents can update their beliefs about their opponents and revise their level-k rule. In this study, Neural Fitted Q Iteration, which is an approximate reinforcement learning method, is used to model time-extended decisions of pilots with 3D maneuvers. An analysis of UAS integration is conducted using an Example 3D scenario in the presence of manned aircraft and fully autonomous UAS equipped with sense and avoid algorithms.en_US
dc.embargo.release2023-10-23
dc.identifier.doi10.1016/j.trc.2021.103417en_US
dc.identifier.eissn1879-2359
dc.identifier.issn0968-090X
dc.identifier.urihttp://hdl.handle.net/11693/76718
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttps://doi.org/10.1016/j.trc.2021.103417en_US
dc.source.titleTransportation Research Part C: Emerging Technologiesen_US
dc.subjectUAS integration into NASen_US
dc.subjectReinforcement learningen_US
dc.subjectBehavioral game theoryen_US
dc.subjectHuman modelingen_US
dc.titleA 3D game theoretical framework for the evaluation of unmanned aircraft systems airspace integration conceptsen_US
dc.typeArticleen_US

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