Kevin M. Corker

Analysis and Modeling of Flight Crew Performance in Automated Air Traffic Management Systems

Abstract NASA has recently initiated a research program to enhance commercial aviation throughput in crowded terminal areas. The Terminal Area Productivity (TAP) initiative seeks to focus technologies in automated air traffic management and to improve flight management systems. The interaction between air traffic control (ATC) automation, flight deck automation and the human operators who mediate them will be reported here. We’ve performed empirical studies in full-mission simulation to address procedural coordination between flight crews and air traffic controllers. In parallel, we have addressed the need for rapidly adaptable analytic techniques by developing a human performance model of flight crew.

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.

Future air traffic management: technology, operations, and human factors implications

Abstract The NASA, the FAA and Eurocontrol have initiated programs of research and development to provide flight crew, air line operators and air traffic managers with automation aids to increase capacity in enroute and terminal areas, to support the goals of safe, flexible, predictable and efficient operations, and to ensure, and to enhance the safety of operations in the response to demands for capacity enhancement. Achievement of these goals is enabled by increased precision of knowledge of aircraft and asset position in space and time, by increased density and bandwidth of transmitted information among the airspace assets and users, and by increased service and information to the flight deck, ATC and airline operations centers. These aiding technologies are intended to support exploitation of timely and dynamic information on atmospheric hazards, traffic fluctuations, and airspace utilization. These systems are intended to support the human operators who maintain the authority and responsibility for safe, efficient operations through cognitive aiding technologies, to serve as cognitive orthoses (Reason, 1988) [12].