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An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research CenterThe Airspace Operations Laboratory at NASA Ames conducts research to provide a better understanding of roles, responsibilities, and requirements for human operators and automation in future air traffic management (ATM) systems. The research encompasses developing, evaluating, and integrating operational concepts and technologies for near-, mid-, and far-term air traffic operations. Current research threads include efficient arrival operations, function allocation in separation assurance and efficient airspace and trajectory management. The AOL has developed powerful air traffic simulation capabilities, most notably the Multi Aircraft Control System (MACS) that is used for many air traffic control simulations at NASA and its partners in government, academia and industry. Several additional NASA technologies have been integrated with the AOL's primary simulation capabilities where appropriate. Using this environment, large and small-scale system-level evaluations can be conducted to help make near-term improvements and transition NASA technologies to the FAA, such as the technologies developed under NASA's Air Traffic Management Demonstration-1 (ATD-1). The AOL's rapid prototyping and flexible simulation capabilities have proven a highly effective environment to progress the initiation of trajectory-based operations and support the mid-term implementation of NextGen. Fundamental questions about accuracy requirements have been investigated as well as realworld problems on how to improve operations in some of the most complex airspaces in the US. This includes using advanced trajectory-based operations and prototype tools for coordinating arrivals to converging runways at Newark airport and coordinating departures and arrivals in the San Francisco and the New York metro areas. Looking beyond NextGen, the AOL has started exploring hybrid human/automation control strategies as well as highly autonomous operations in the air traffic control domain. Initial results indicate improved capacity, low operator workload, good situation awareness and acceptability for controllers teaming with autonomous air traffic systems. While much research and development needs to be conducted to make such concepts a reality, these approaches have the potential to truly transform the airspace system towards increased mobility, safe and efficient growth in global operations and enabling many of the new vehicles and operations that are expected over the next decades. This paper describes how the AOL currently contributes to the ongoing air transportation transformation.
Document ID
20140012038
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Prevot, Thomas
(NASA Ames Research Center Moffett Field, CA United States)
Smith, Nancy M.
(NASA Ames Research Center Moffett Field, CA United States)
Palmer, Everett
(NASA Ames Research Center Moffett Field, CA United States)
Callantine, Todd
(San Jose State Univ. Moffett Field, CA, United States)
Lee, Paul
(San Jose State Univ. Moffett Field, CA, United States)
Mercer, Joey
(San Jose State Univ. Moffett Field, CA, United States)
Homola, Jeff
(San Jose State Univ. Moffett Field, CA, United States)
Martin, Lynne
(San Jose State Univ. Moffett Field, CA, United States)
Brasil, Connie
(San Jose State Univ. Moffett Field, CA, United States)
Cabrall, Christopher
(San Jose State Univ. Moffett Field, CA, United States)
Date Acquired
September 18, 2014
Publication Date
June 16, 2014
Subject Category
Air Transportation And Safety
Report/Patent Number
ARC-E-DAA-TN15475
Meeting Information
Meeting: AIAA Aviation Technology, Integration, and Operations Conference
Location: Atlanta, GA
Country: United States
Start Date: June 16, 2014
End Date: June 20, 2014
Sponsors: American Inst. of Aeronautics and Astronautics
Funding Number(s)
CONTRACT_GRANT: NNX12AB08A
WBS: WBS 305295.02.31.01.01.07
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
simulation
autonomy
human/systems
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