Andrew Cone

Robust Conict Detection and Resolution around Top of Descent

x at the edge of the terminal area. This paper explores a pair of enhanced vertical conict detection ranges (buers) for aircraft descending to their meter x that could provide enough coverage to catch potential losses for multiple types of uncertainty while limiting the increase in false alerts. The specic uncertainties examined include the predicted wind speed, cruise speed, descent speed, top-of-descent location, and the combination of all of those uncertainties plus uncertainty in aircraft fuel weight prediction. Performance metrics include false alerts, missed alerts, losses of separation, number of resolutions issued, and the total system delay caused by aircraft ying conict avoidance maneuvers. Results show that these vertical buers reduce the number of losses of separation for arriving aircraft from 207 to 12. However, using the vertical buers increases the number of resolutions issued by 50% and doubles the delay accrued by aircraft ying conict resolution maneuvers. Results also suggest that a smaller buer (80% size) could be used to gain most of the same benet as the full buer with less additional delay, while alternative methods might be best suited to remove the last few loss of separation cases during descent. Further, improving the trajectory prediction accuracy combined with a vertical buer signicantly reduced the number of losses of separation, resolutions issued, and delay accrued.

Well Clear Trade Study for Unmanned Aircraft System Detect And Avoid with Non-Cooperative Aircraft

This paper presents a process for selecting candidate Detect-and-Avoid Well Clear definitions for Unmanned Aircraft Systems and non-cooperative aircraft. The selection is based on considerations of the unmitigated collision risk, maneuver initiation range, and others. Operational assumptions related to low cost, size, weight, and power sensors equipped by the Unmanned Aircraft Systems are applied to set the scope of aircraft performance and drive metrics computation. Four candidate Well Clear definitions, two primary and two secondary, varying from 1500 to 2500 ft in their horizontal miss distance and from 0 to 25 sec in modified tau, are selected for future analyses.

UAS Well Clear Recovery Against Non-Cooperative Intruders Using Vertical Maneuvers

This paper documents a study that drove the development of a mathematical expression in the detect-and-avoid (DAA) minimum operational performance standards (MOPS) for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance should be provided during recovery of DAA well clear separation with a non-cooperative VFR aircraft. Although the original hypothesis was that vertical maneuvers for DAA well clear recovery should only be offered when sensor vertical rate errors are small, this paper suggests that UAS climb and descent performance should be considered—in addition to sensor errors for vertical position and vertical rate—when determining whether to offer vertical guidance. A fast-time simulation study involving 108,000 encounters between a UAS and a non-cooperative visual-flight-rules aircraft was conducted. Results are presented showing that, when vertical maneuver guidance for DAA well clear recovery was suppressed, the minimum vertical separation increased by roughly 50 feet (or horizontal separation by 500 to 800 feet). However, the percentage of encounters that had a risk of collision when performing vertical well clear recovery maneuvers was reduced as UAS vertical rate performance increased and sensor vertical rate errors decreased. A class of encounter is identified for which vertical-rate error had a large effect on the efficacy of horizontal maneuvers due to the difficulty of making the correct left/right turn decision: crossing conflict with intruder changing altitude. Overall, these results support logic that would allow vertical maneuvers when UAS vertical performance is sufficient to avoid the intruder, based on the intruder’s estimated vertical position and vertical rate, as well as the vertical rate error of the UAS’ sensor.

Separation Assurance and Scheduling Coordination in the Arrival Environment

Separation assurance (SA) automation has been proposed as either a ground-based or airborne paradigm. The arrival environment is complex because aircraft are being sequenced and spaced to the arrival fix. This paper examines the effect of the allocation of the SA and scheduling functions on the performance of the system. Two coordination configurations between an SA and an arrival management system are tested using both ground and airborne implementations. All configurations have a conflict detection and resolution (CD&R) system and either an integrated or separated scheduler. Performance metrics are presented for the ground and airborne systems based on arrival traffic headed to Dallas/ Fort Worth International airport. The total delay, time-spacing conformance, and schedule conformance are used to measure efficiency. The goal of the analysis is to use the metrics to identify performance differences between the configurations that are based on different function allocations. A surveillance range limitation of 100 nmi and a time delay for sharing updated trajectory intent of 30 seconds were implemented for the airborne system. Overall, these results indicate that the surveillance range and the sharing of trajectories and aircraft schedules are important factors in determining the efficiency of an airborne arrival management system. These parameters are not relevant to the ground-based system as modeled for this study because it has instantaneous access to all aircraft trajectories and intent. Creating a schedule external to the CD&R and the scheduling conformance system was seen to reduce total delays for the airborne system, and had a minor effect on the ground-based system. The effect of an external scheduler on other metrics was mixed.

Automated arrival management: Effects of descent trajectory prediction errors on metering conformance

The effects of descent trajectory prediction errors on the performance of an “Arrival Manager” algorithm are explored. Errors in descent calibrated airspeed and wind speed are modeled in order to assess their impact on the baseline performance of the Arrival Manager algorithm in terms of arrival time performance, airborne delay and the number of losses of separation. These data were obtained by simulating in fast-time two streams of arrival traffic merging at the northeast metering fix at Dallas/Fort Worth International Airport. A simple arrival schedule is imposed with uniform spacing between aircraft. Given the modeled error in descent speed or wind, the Arrival Managers ability to deliver each aircraft to meet its crossing-time constraint with no loss of separation from other aircraft is assessed. Results indicate that both metrics - airborne scheduled delay and the number of separation losses - are more sensitive to the modeled descent speed errors than the modeled wind speed error. Wind speed error resulted in no losses of separation.