Future air traffic systems aim at increasing both the capacity and safety of the system, necessitating the development of new metrics and advisory tools for controllers' workload in real-time. Psychophysiological data such as Electroencephalography (EEG) are used to contrast and validate subjective assessments and workload indices. EEG used within augmented cognition systems form situation awareness advisory tools that are able to provide real-time feedback to air-traffic control supervisors and planners. This augmented cognition system and experiments using the system with air traffic controllers are presented. Traffic indicators are used in conjunction with EEG-driven cognitive indicators to adapt the traffic in real-time through Computational Red Teaming (CRT) based adaptive control mechanisms. The metrics, measures, and adaptive control mechanisms are described and evaluated. The best mechanism to improve system efficacy was found when the system allowed for real-time adaptation of traffic based on engagement metrics driven from the EEG data.

Continuous Descent Approaches (CDAs) can significantly reduce fuel burn and noise impact by keeping arriving aircraft at their cruise altitude for longer than during conventional approaches(to descend as late as possible)and then having them make a continuous descent to the runway at near idle thrust with no level flight segments. The CDA procedures are fixed routes that are vertically optimized. With the changing traffic conditions and variable noise abatement rules the benefits of CDA operations are not yet fully realized.In this paper we propose a methodology to generate aircraft-specific dynamic CDA routes that are both laterally and vertically optimized on given objectives (noise, emission and fuel) from an Initial Approach Fix (IAF) to Final Approach Fix (FAF). The methodology utilizes real-time aircraft position and defined objectives to generate CDA routes which can then be converted into a set of artificial waypoints for continuous descent in transition airspace. The methodology involves discretizing the terminal airspace into concentric cylinders with artificial waypoints and uses enumeration and elimination (based on aircraft performance envelope) from one waypoint to other to identify all the possible routes. For each transition a variety of metrics including noise, emission and fuel burn are computed. From the resulting set of possible CDA routes, those routes are identified that represent the best trade-off on the given objectives. One of these routes is then used to dynamically update the flight route for executing the CDA procedure.For noise we used The Overall Sound Pressure Level (OPSL) and for emissions we used four pollutants , , 2 and . The dynamic CDA algorithm is implemented in a high-fidelity simulator ATOMS for Sydney Terminal Area with 34L as arrival runway for a Melbourne-Sydney flight (B737-400 aircraft, CFM56-3C-1 engines with a nominal weight of 58000 kg). The dynamic CDA routes are then compared on noise, emission and fuel burn with same flight conducting a typical CDA procedure (MANFA ONE Arrival) at the Sydney airport. The results shows that the methodology generates 64 possible solutions (dynamic CDA routes) from IAF to FAF in the transition airspace, of which 5 solutions were non-dominated. Dynamic CDA approach shows a reduction of 14.96% in noise, 11.6% reduction in emission and 1.5% reduction in fuel burn when compared to a standard CDA trajectory.The paper also investigates the throughput capacity of transition airspace for multiple flights performing CDA operation. The methodology incorporates a delay algorithm which uses the flights' estimated time of arrival (ETA) at the IAF and then allocates them a conflict free CDA route by searching through available routes. The approach takes into account the aircraft category and corresponding time occupancy at each artificial waypoint of the proposed CDA routes and propagate delays back when conflict exists.

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