A Predictive Model of Flight Crew Performance in Automated Air Traffic Control and Flight Management Operations*

This paper describes Air-MIDAS, a model of pilot performance in interaction with varied levels of automation in flight management operations. The model was used to predict the performance of a two person flight crew responding to clearance information generated by the Center TRACON Automation System (CTAS). The model represents the information requirements, decision processes, communication processes, and motor performance required by the flight crew to integrate flight management automation and ground-side automation in clearance aiding. Stochastic variations in environment and flight crew interruption were entered into the model, which then generated predictions of flight crew decision-making and clearance enactment strategies. The model’s predictions were then compared to full-mission LOFT-type simulation data in which CTAS clearances were systematically varied in performance requirements and timing at top-of-descent. The paper describes the model, its development and implementation, the simulation test of the model predictions, and the empirical validation process. The complex human performance model allows variations in CTAS design to be explored through predictive simulation. Procedures and performance criteria as well as situational variations can be controlled and tested. The model and its supporting data provide a generalizable tool that is being expanded to include air/ground compatibility and ATC crew interactions in air traffic management.