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RNAV STAR Procedural Adherence
NTRS Full-Text: Click to View  [PDF Size: 6.5 MB]
Author and Affiliation:
Matthews, Bryan L.(SGT, Inc., Moffett Field, CA, United States)
Stewart, Michael J.(San Jose State Univ., Moffett Field, CA, United States)
Abstract: Flight crews and air traffic controllers have reported many safety concerns regarding area navigation standard terminal arrival routes (RNAV STARs). However, our information sources to quantify these issues are limited to subjective reporting and time consuming case-by-case investigations. This work is a preliminary study into the objective performance of instrument procedures and provides a framework to track procedural concepts and assess design functionality. We created a tool and analysis methods for gauging aircraft adherence as it relates to RNAV STARs. This information is vital for comprehensive understanding of how our air traffic behaves. In this exploratory archival study, we mined the performance of 24 major US airports over the preceding three years. Overlaying radar track data on top of RNAV STAR routes provided a comparison between aircraft flight paths and the waypoint positions and altitude restrictions. NASA Ames Supercomputing resources were utilized to perform the data mining and processing. We assessed STARs by lateral transition path (full-lateral), vertical restrictions (full-lateralfull-vertical), and skipped waypoints (skips). In addition, we graphed aircraft altitudes relative to the altitude restrictions and their occurrence rates. Full-lateral adherence was generally greater than Full-lateralfull-vertical, but the difference between the rates was not always consistent. Full-lateralfull-vertical adherence medians of the 2016 procedures ranged from 0 in KDEN (Denver) to 21 in KMEM (Memphis). Waypoint skips ranged from 0 to nearly 100 for specific waypoints. Altitudes restrictions were sometimes missed by systematic amounts in 1000 ft. increments from the restriction, creating multi-modal distributions. Other times, altitude misses looked to be more normally distributed around the restriction. This tool may aid in providing acceptability metrics as well as risk assessment information.
Publication Date: Aug 29, 2017
Document ID:
20170012335
(Acquired Jan 03, 2018)
Subject Category: ASTRONAUTICS (GENERAL)
Report/Patent Number: ARC-E-DAA-TN46326
Document Type: Oral/Visual Presentation
Publication Information: SEE 2017001115
Meeting Information: Machine Learning Workshop 2017; 29-31 Aug. 2017; Moffett Field, CA; United States
Meeting Sponsor: NASA Ames Research Center; Moffett Field, CA, United States
Contract/Grant/Task Num: NNA14AA60C; NNA08CG83C; NNX17AE07A
Financial Sponsor: NASA Ames Research Center; Moffett Field, CA, United States
Organization Source: NASA Ames Research Center; Moffett Field, CA, United States
Description: 36p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Public use permitted
NASA Terms: AREA NAVIGATION; RADIO NAVIGATION; AIR TRAFFIC; ROUTES; AIRPORTS; ARRIVALS; DATA MINING; INSTRUMENT APPROACH; TERRAIN; FLIGHT PATHS; PROCEDURES; AIR TRAFFIC CONTROLLERS (PERSONNEL); AIRCRAFT SAFETY; RISK ASSESSMENT; NOISE REDUCTION; FLIGHT TIME; MACHINE LEARNING; AUTOMATIC CONTROL; SCIENTIFIC VISUALIZATION
Other Descriptors: DATA MINING; ADHERENCE; RNAV; STAR
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