Modeling and predicting mental workload in en route air traffic control: critical review and broader implications.
OBJECTIVE
We perform a critical review of research on mental workload in en route air traffic control (ATC). We present a model of operator strategic behavior and workload management through which workload can be predicted within ATC and other complex work systems.


BACKGROUND
Air traffic volume is increasing worldwide. If air traffic management organizations are to meet future demand safely, better models of controller workload are needed.


METHODS
We present the theoretical model and then review investigations of how effectively traffic factors, airspace factors, and operational constraints predict controller workload.


RESULTS
Although task demand has a strong relationship with workload, evidence suggests that the relationship depends on the capacity of the controllers to select priorities, manage their cognitive resources, and regulate their own performance. We review research on strategies employed by controllers to minimize the control activity and information-processing requirements of control tasks.


CONCLUSIONS
Controller workload will not be effectively modeled until controllers' strategies for regulating the cognitive impact of task demand have been modeled.


CONCLUSIONS
Actual and potential applications of our conclusions include a reorientation of workload modeling in complex work systems to capture the dynamic and adaptive nature of the operator's work. Models based around workload regulation may be more useful in helping management organizations adapt to future control regimens in complex work systems.
Loft
Shayne
S
ARC Key Centre for Human Factors and Applied Cognitive Psychology, University of Queensland, Brisbane 4072, Australia. lofts@psy.uq.edu.au
Sanderson
Penelope
P
Neal
Andrew
A
Mooij
Martijn
M
D000060:Accidents, Aviation / Q000517:prevention & control*; D001364:Awareness; D005544:Forecasting; D006801:Humans; D008606:Mental Processes; D008960:Models, Psychological; D011340:Problem Solving; D011597:Psychomotor Performance; D012449:Safety; D013647:Task Performance and Analysis; D013997:Time Factors; D016526:Workload