Hybrid System Model of Air Traffic Controller Cognition

Increased automation in air traffic control has many benefits, but to incorporate advanced automation tools safely and effectively requires careful analysis of their impact on human controllers. The literature on cognitive psychology and human factors has produced many qualitative models that describe the cognitive processes of controllers as well as a variety of computational models that attempt to reproduce the way controllers make decisions. The work presented here uses these results to form a novel hybrid system framework for modeling human cognition and describes a model of air traffic controller cognition based on this framework. The thought process is modeled as a set of critical variables that represent the human controller's picture of a given air traffic situation, with the evolution of these variables described by a set of hybrid dynamics where the discrete variables correspond to different thought processes and cognitive tasks. The primary contribution of this paper is to place the cognitive model within the formal mathematical framework of hybrid systems theory, allowing verification and online estimation and control with the tools of hybrid systems.