NASA's Unmanned Aircraft Systems Traffic Management research aims to develop policies, procedures, requirements, and other artifacts to inform the implementation of a future system that enables small drones to access the low altitude airspace. In this endeavor, NASA conducted a geographically diverse flight test in conjunction with the FAA's six unmanned aircraft systems Test Sites. A control center at NASA Ames Research Center autonomously managed the airspace for all participants in eight states as they flew operations (both real and simulated). The system allowed for common situational awareness across all stakeholders, kept traffic procedurally separated, offered messages to inform the participants of activity relevant to their operations. Over the 3hour test, 102 flight operations connected to the central research platform with 17 different vehicle types and 8 distinct software client implementations while seamlessly interacting with simulated traffic.
Design of a terminal area arrival scheduler depends on the interrelationship between throughput, delay and controller intervention. The main contribution of this paper is an analysis of the above interdependence for several stochastic behaviors of expected system performance distributions in the aircraft's time of arrival at the meter fix and runway. Results of this analysis serve to guide the scheduler design choices for key control variables. Two types of variables are analyzed, separation buffers and terminal delay margins. The choice for these decision variables was tested using sensitivity analysis. Analysis suggests that it is best to set the separation buffer at the meter fix to its minimum and adjust the runway buffer to attain the desired system performance. Delay margin was found to have the least effect. These results help characterize the variables most influential in the scheduling operations of terminal area arrivals.
Integrating departures and arrivals in terminal airspace with shared resources, such as waypoints, fixes and routes, has the potential to provide more efficient operations than segregated operations. However, the benefits of integrated operations may be vulnerable to flight time uncertainty. This paper presents an analysis of the impacts of flight time uncertainty on scheduled integrated operations. Monte Carlo simulations were implemented with perturbations incorporated into flight arrival/departure times. Impacts of the uncertainty on delays and controller interventions were investigated. Two cases in Los Angeles terminal airspace were examined. Results showed the general trend that when uncertainty buffer increased, delay normally increased whereas controller interventions decreased. In addition, results from the Los Angeles cases showed that, even with 60s uncertainty buffer, the schedules of integrated operations generated under deterministic scenarios still had over 90 percent chance of reducing delay over the segregated operations, although the controller interventions increased as a trade-off. On the other hand, in these two cases, the departure time precision showed mixed impact which depended on the intervals in departure sequence, however, the departure time precision showed a stronger relationship with controller interventions than the arrival time precision in both cases.
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