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HIGHLIGHTS ARCHIVE
Division Highlights


Fully-Integrated ATD-1 Test (FIAT) 2 Completes Shakedown Simulations
February 14, 2013

Screenshot of Controller Managed Spacing Tools
Screenshot of ATD-1 Controller Managed Spacing tools

NASA has developed a suite of advanced arrival management technologies combining time-based scheduling with controller- and flight deck-based precision spacing capabilities that allow fuel-efficient arrival operations during periods of high throughput. An operational demonstration of these integrated technologies, i.e., the ATM Technology Demonstration #1 (ATD-1), is slated for 2016. Human-in-the-loop simulations were conducted to evaluate the performance of the ATD-1 system and validate operational feasibility. The Fully-Integrated ATD-1 Test (FIAT)-2 focuses on developing the ground-based controller tools used in ATD-1. The Controller Managed Spacing (CMS) tools were ported and tested in the NASA Traffic Management Advisor (TMA) software baseline. On February 4-6, 2013, the FIAT research team completed a set of system checkout simulation runs of the CMS algorithms. Participants included 5 controllers and 8 pseudo pilots, who also assisted in refining the phraseology and procedures proposed for ATD-1. MITRE researchers also observed the shakedown and discussed plans for the upcoming Terminal Spacing and Sequencing (TSS) simulations. (POC - Jane Thipphavong)


HITL Simulation Explores Trajectory Prediction Requirements for TBO: "How Good Is Good Enough?"
February 14, 2013

In January 2013, Aviation Systems and Human Systems Integration Division researchers completed what is believed to be the first human-in-the-loop simulation to address the age-old question regarding Trajectory Prediction (TP) performance: "How good is good enough?" That is, how much trajectory-prediction error can be accommodated by air traffic controllers before a NextGen Trajectory-Based Operations (TBO) concept becomes untenable? Two controller teams used an advanced set of tools over 22 typical Atlanta arrival-metering trials in which uncertainties in the form of wind forecast errors and errors in aircraft performance (e.g., descent rate) assumptions were varied from nominal levels to four- to five-times these real-world uncertainties. Real-time controller performance metrics on the number of clearance instructions, workload, and quality of service in terms of arrival metering accuracy and traffic separation were recorded. Preliminary observations suggest that there was no clear controller "breakpoint" (whereupon the operational concept became untenable). Even with the largest errors, controllers were able to compensate and adapt the advisories suggested by the automated tools to maintain safe separation and deliver arrival aircraft on time. Reported workload ratings did increase with increasing errors, but on average remained within acceptable levels. Increased TP errors did not appear to be correlated with an increase in the number of corrective clearances, nor a reduction in the efficiency benefits of the NextGen tools. These findings suggest future research should further investigate the exact nature and impact of how the controllers adapted to the TP errors, and, if the same TP errors that were so effectively managed by the controllers are found to overwhelm a fully automated system that relies solely on corrective advisories, there may be a need to incorporate corrective learning in TBO automation as the controllers did naturally in the simulation. There may also be a need for additional development of the human-system concept for transition to more automated paradigms. (POC: Steve Green)


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