ABSTRACT
This papcr is conccrncd with a human-machine-modcl for thc tower controller working position to investigatc human decision making in dynamical environments. The authors assumc that human decision making in thc highly dynamical task environment of tower controllers is guided by heuristics. Tower controllers don't have the time to look for all information in their work environment before making a decision. They have to use heuristics to interact successfully with their task environment. Colored petrinets are used (CPN-Tools) for modeling the human-machine-system. The three-step-principle of fast and frugal heuristics is implemented into the controller model. The strength of petrinets is their mathematical background that allows for calculating state spaces. Analyzing fast and fmgal heuristics in dynamical environments, using state space analysis, is introduced here as a methodological approach. This approach can not only be used to analyze heuristics implemented in formal models, but also to analyzc empirical data of human decision making. The application of this approach for the analysis of heuristics used by air traffic controllers in the field is evident.
