Flight Crew Survey Responses from the Interval Management (IM) Avionics Phase 2 Flight Test

Baxley, Brian T.; Swieringa, Kurt A.; Wilson, Stephanie J.; Roper, Roy D.; Hubbs, Clay E.; Goess, Paul A.; Shay, Richard F.

doi:10.2514/6.2017-4095

Cited by 9 publications

(12 citation statements)

References 7 publications

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“…Although the spacing performance was satisfactory, operational issues that are barely identifiable outside an HITL environment were found in terms of the number, frequency, and timing of speed commands, their magnitude (step size), and overall energy management. [7][8][9] The parameters measured in our simulation (described in Section 3.11) were selected to quantify these findings.…”

Section: Flight Test Resultsmentioning

confidence: 99%

“…Furthermore, a qualitative flight crew survey conducted during a flight test in February 2017 indicated that the system has not yet attained an operationally implementable level owing to issues related to workload and acceptance. [7][8][9] This was reflected by negative feedback comments such as "Too many speed changes," "Large decelerations" (speed steps well over 40 kt), and "inefficient IM speed reversals" (speed commands negating the effect of a previous command). Previous studies have primarily focused on the goal time observation or the string stability of multiple aircraft engaged in FIM, 10) while usability factors have rarely been considered.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating Applied Flight-deck Interval Management using Monte Carlo Simulations on the K-Supercomputer

Riedel

Takahashi

Tatsukawa

et al. 2019

Trans. Japan Soc. Aero. S Sci.

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Increasing air traffic and airport congestion calls for solutions to improve traffic throughput. In this paper, we evaluate one solution, Flight-deck Interval Management and its underlying logic, particularly in terms of its utility. An environment to simulate traffic engaged in interval management on the most common arrival routes toward Tokyo International Airport was set up and run as a large-scale Monte Carlo simulation on the K-Supercomputer. The results show that under low wind conditions in particular, spacing goal times with a standard deviation of less than 5 s can be achieved and a speed tolerance mode can reduce the number of speed commands without compromising performance.

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Section: Flight Test Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluating Applied Flight-deck Interval Management using Monte Carlo Simulations on the K-Supercomputer

Riedel

Takahashi

Tatsukawa

et al. 2019

Trans. Japan Soc. Aero. S Sci.

View full text Add to dashboard Cite

show abstract

“…In this study, two scoring attributes and three penalty attributes, influenced by the results of Refs. (23)(24)(25), were employed. The final score (S) is determined from the sum of all individual scores (s k ) multiplied by an optional corresponding weight factor (q k ).…”

Section: Cost Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…NASA's research on ASTAR was concluded in early 2017 with a final flight test (23)(24)(25) . While sophisticated spacing capability of FIM could be confirmed, pilots' comments highlighted the operational difficulties such as 'too many IM speed changes, or the rate of the speed changes is too high' (24) , and the crew had 'no fore-knowledge of when or what the next IM speed would be' and 'could only be reactive'. In its 'Recommended changes to Interval Management to Achieve Operational Implementation' (25) , NASA concludes that 'improvements to the IM commanded speed behaviour is needed before implementation' and further recommends to 'explore alternative control law techniques to allow for trade-offs between spacing error and IM speed change behaviour to reduce the rate of speed changes and speed reversals' (i.e.…”

Section: Introductionmentioning

confidence: 99%

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Reducing speed commands in interval management with speed planning

Riedel

Takahashi²,

Itoh

2019

Aeronaut. j.

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Flight-deck Interval Management (FIM) is a modern airborne self-spacing technology that improves arrival route throughput and runway utilisation and increases hourly arrival capacity by up to four aircraft per hour and per runway, compared to conventional air traffic controller guided arrivals. The National Aeronautics and Space Administration (NASA) has been the leader in FIM research and formulated a logic that was put to an actual flight test in 2017. Despite the overall success of the project, operational deficiencies concerning the number of speed commands, which led to several recommendations for future research before operational implementation, were discovered. In this study, a new logic that implements a two-stage rule-based selection algorithm was developed to overcome those deficiencies. The proposed logic was compared to NASA’s logic on an arrival in Tokyo International Airport with multiple induced error patterns. The results indicate that the new logic significantly decreases the number of speed commands with only minor aggravations in spacing performance. The results that highlight the strengths and weaknesses of both concepts are discussed, and an outlook on and ideas for future research on FIM and the proposed logic are presented.

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Participant Training for a Flight Test Evaluation of Interval Management

Roper

Baxley

Swieringa

et al. 2018

Advances in Intelligent Systems and Computing

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Interval Management is a concept designed to be used by air traffic controllers and flight crews to more efficiently and precisely manage inter-aircraft spacing. NASA, in cooperation with Boeing, Honeywell, and United Airlines, tested an avionics prototype onboard flight test aircraft. A critical need was identified to train the pilots participating in the flight test prior to the first flight. This paper documents the flight training regimen that successfully trained the pilots on the Interval Management concepts and flight crew procedures and suggests potential improvements to future training regimens for industry use.

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Flight Crew Survey Responses from the Interval Management (IM) Avionics Phase 2 Flight Test

Cited by 9 publications

References 7 publications

Evaluating Applied Flight-deck Interval Management using Monte Carlo Simulations on the K-Supercomputer

Evaluating Applied Flight-deck Interval Management using Monte Carlo Simulations on the K-Supercomputer

Reducing speed commands in interval management with speed planning

Participant Training for a Flight Test Evaluation of Interval Management

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