Assuring safety in air traffic control systems with argumentation and model checking

Abstract

Although the continuous safety technology advances in fields like air traffic control (ATC) systems or medical devices, the crux of safety assurance still comes down to human decision makers, which, within the context of having to define priorities while simultaneously considering different contextual criteria, present a constant high risk of erroneous decisions. We illustrate in this article a recommender framework for assisting flight controllers, which combines argumentation theory and model checking in the evaluation of trade-offs and compromises to be made in the presence of incomplete and potentially inconsistent information. We view a Hybrid Kripke model as a description of an ATC domain and we apply a rational decision strategy based on Hybrid Logics and Defeasible Reasoning to assist the process of model update when the system has to accommodate new properties or norm constraints. When the model fails to verify a property, a defeasible logic program is used to analyze the current state and perform updating operations on the model. The introduced decision making framework is tested on a recommender system in ATC and model update is demonstrated with respect to the verification and adaption of unmanned aerial vehicles routes in the air traffic space. The results show an important potential for the presented framework to be integrated directly into existing decision-making routines for achieving higher accuracy in recommender system methods.