Modeling Air Traffic Controller Performance in Highly Automated Environments

As increasing levels of automation are planned for the United States' air traffic control system, there is a need to assess planned system design changes for their potential effects on human performance. The model of controller performance developed by this work permits the comparison of prior and planned system transition states on several performance dimensions: perceptual, analytic, response, and resource management. Systematic predictions of performance provide a basis for identifying potential trouble spots in a planned system. The model can be employed to determine whether system design changes will improve controller performance without placing unreasonable demands on the controller's resources. It can be tailored to represent human performance variables and sources of resource demand in any complex automated system.