Survey of Air/Ground and Human/Automation Functional Allocation for Separation Assurance

*Separation assurance is a fundamental requirement for safe operations of air traffic. New paradigms of separation assurance will be required to accommodate the anticipated increase of air traffic in the future. This paper defines a taxonomy for the allocation of separation assurance functions along the air/ground and human/automation axes, and then builds a knowledge base from a comprehensive survey of separation assurance studies conduced over the past 12 years with an emphasis on high-fidelity human-in-the-loop simulations and operational evaluations. The goal of this effort is to identify trends and gaps in the current knowledge base of functional allocation for separation assurance, so that it may serve as a guide for planning future work. One finding is that limited delegation for arrival merging/spacing has been developed to a relatively high level of maturity. Another finding is that various aspects of automated concepts for ground-based and airborne separation assurance have been well studied; the key challenge going forward is system level integration and evaluation

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