A novel human-machine interface framework for conflict resolution
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This thesis introduces a novel architecture for human-machine interface focusing primarily on the human aspects as applied to aircraft and unmanned systems. There is a need to explore new human-machine interface strategies stemming from the proliferation over the past years of accidents due to system complexity, failure modes and human errors. Concepts of autonomy establish the foundational elements of the work. We pursue a rigorous systems engineering process to analyze and design the tools and techniques for automated vehicle health monitoring, human-automation interface and conflict resolution enabled by innovative methods from game theory and reasoning algorithms. The general structure is illustrated in the paper. This paper addresses the general interface framework while emphasizing the human’s (pilots) intended actions following an adverse event on-board the vehicle, i.e. critical component fault/failure modes. When combined with automated health state assessment means on-board the aircraft, the proposed strategy assists to improve the reliability of estimated actions the pilot must execute to mitigate possible catastrophic consequences. A “smart” knowledge base is exploited as the reasoning paradigm where cases are stored and new ones are compared with similar ones available in the case library. Learning and adaptation tools are used to improve the decision making process. The emphasis of this contribution is on methods and tools for conflict resolution when the automated system’s advisories are coincident with the human’s intended actions. Appropriate similarity metrics are defined and used for this purpose. The efficacy of the approach is demonstrated via an interface built in MATLAB highlighting the performance of the algorithmic modules for assessment and conflict resolution.