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Benefits Assessment of Algorithmically Combining Generic High Altitude Airspace SectorsIn today's air traffic control operations, sectors that have traffic demand below capacity are combined so that fewer controller teams are required to manage air traffic. Controllers in current operations are certified to control a group of six to eight sectors, known as an area of specialization. Sector combinations are restricted to occur within areas of specialization. Since there are few sector combination possibilities in each area of specialization, human supervisors can effectively make sector combination decisions. In the future, automation and procedures will allow any appropriately trained controller to control any of a large set of generic sectors. The primary benefit of this will be increased controller staffing flexibility. Generic sectors will also allow more options for combining sectors, making sector combination decisions difficult for human supervisors. A sector-combining algorithm can assist supervisors as they make generic sector combination decisions. A heuristic algorithm for combining under-utilized air space sectors to conserve air traffic control resources has been described and analyzed. Analysis of the algorithm and comparisons with operational sector combinations indicate that this algorithm could more efficiently utilize air traffic control resources than current sector combinations. This paper investigates the benefits of using the sector-combining algorithm proposed in previous research to combine high altitude generic airspace sectors. Simulations are conducted in which all the high altitude sectors in a center are allowed to combine, as will be possible in generic high altitude airspace. Furthermore, the algorithm is adjusted to use a version of the simplified dynamic density (SDD) workload metric that has been modified to account for workload reductions due to automatic handoffs and Automatic Dependent Surveillance Broadcast (ADS-B). This modified metric is referred to here as future simplified dynamic density (FSDD). Finally, traffic demand sets with increased air traffic demand are used in the simulations to capture the expected growth in air traffic demand by the mid-term.
Document ID
20100023357
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Bloem, Michael (NASA Ames Research Center Moffett Field, CA, United States)
Gupta, Pramod (California Univ. Santa Cruz, CA, United States)
Lai, Chok Fung (California Univ. Santa Cruz, CA, United States)
Kopardekar, Parimal (NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 24, 2013
Publication Date
July 31, 2009
Subject Category
Air Transportation And Safety
Report/Patent Number
ARC-E-DAA-TN735
Meeting Information
Meeting: 27th Congress of the International Council of the Aeronautical Sciences
Location: Nice, France
Country: France
Start Date: September 19, 2010
End Date: September 24, 2010
Sponsors: International Council of the Aeronautical Sciences
Funding Number(s)
WBS: WBS 411931.02.31.01.02
CONTRACT_GRANT: NAS2-03144
Distribution Limits
Public
Copyright
Public Use Permitted.

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