As a part of NASA's NextGen research effort, the focus area of Airspace Super-Density Operations (ASDO) performs research pertaining to highly efficient operations at the busiest airports and terminal airspaces. It is expected that multiple ASDO concepts will be interacting with one another in a complex stochastic manner. This research effort developed a high-fidelity queuing model of the terminal area suitable for the design and analysis of NextGen ASDO concepts, as well as to perform time-varying stochastic analysis of terminal area operations with regards to schedule and wind uncertainties. A unique aspect of the current approach is the discretization of terminal airspace routes into 3-nmi servers for enforcing separation requirements. The current research effort developed high-fidelity queuing models of the San Francisco International Airport (SFO) terminal airspace, based on published airspace geometry. A discrete-event simulation framework was developed to simulate the temporal evolution of flights in the terminal area. The queuing simulation framework was used in different case studies involving various phenomena in the terminal area such as compression, conflict and delay analysis, runway reconfiguration and variable inter-aircraft separation. In addition to being a useful analysis tool, the proposed simulation framework shows potential as a real time stochastic decision support tool due to its low computational cost.

This paper develops guidance algorithms suitable for 4D-trajectory-based airspace operations. A previous paper by the same authors proposed a 4D-trajectory-based operational concept for terminal area operations. The concept consists of ground-side automation for synthesis of 4D trajectories and flight-deck-side automation for tracking the 4D-trajectory clearances. Whereas the previous paper dealt with the ground-side automation, the current paper deals with the flight-deck-side automation. The guidance algorithms are part of the flight automation necessary to realize the 4D-trajectory-based operations. The guidance algorithm design is based on the principles of feedback linearization and pole-placement techniques from feedback control theory. 4D trajectories are assumed to be designed using lower-fidelity models such as Base of Aircraft DAtabase (BADA) by ground-side automation. The guidance algorithms in the flight-deck automation on the other hand use higher-fidelity models to track the 4D trajectories. The guidance algorithm computes pitch attitude and throttle commands necessary to continually track a 4D trajectory. Closed-loop simulations using the high-fidelity TSRV aircraft model obtained from NASA Langley indicate very good tracking performance with time-tracking errors less than 1 second. Simulations demonstrate robustness to wind and temperature uncertainties. The guidance implemented on a pair of aircraft also demonstrate the capability to maintain along-trail separation.

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This paper evaluates the effect of Lateral NAVigation (LNAV) and Vertical NAVigation (NAV) equipage on the performance on time-based scheduling. The paper relies on two companion papers: (i) the first paper develops a high-fidelity simulations model of LNAV + VNAV, and (ii) the second paper develops a realistic spatio-temporally correlated model of wind uncertainty. Two different Monte Carlo simulation frameworks are used to evaluate the effect of LNAV + VNAV equipage on time-based-scheduling. The first Monte Carlo simulation framework is used to evaluate the time-of-arrival uncertainty for flights equipped with LNAV + VNAV capability. This Monte Carlo simulation uses a point-mass simulation model of the aircraft equipped with LNAV + VNAV and flying through spatio-temporally correlated wind uncertainty fields. The second Monte Carlo simulation evaluates the effect of LNAV + VNAV equipage on the performance of time-based scheduling. NASA's Stochastic Terminal Area Scheduling and Simulation (STASS) software is used for timebased scheduling and terminal area traffic simulations. Terminal-area traffic Monte Carlo simulations are conducted for 1.0x, 1.5x, and 2.0x demand ratio at San-Francisco International Airport (SFO), Los Angeles International Airport (LAX), and Dallas Fort Worth International Airport (DFW). Results illustrating the effect of LNAV + VNAV equipage level (0%, 25%, 50%, and 75%) on delay, throughput, and the number of separation violations are presented in the paper.

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