Simulation evaluation of controller-managed spacing tools under realistic operational conditions

Callantine, Todd J.; Hunt, Sarah; Prevôt, Thomas

doi:10.1145/2669592.2669658

Cited by 5 publications

(6 citation statements)

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“…CMS tool ratings again were highly consistent with those observed in prior research, with controllers finding the slot markers most usable and useful. 18 CA-5.3 afforded examination of all aspects of ATD-1 operations in a realistically complex traffic environment. The TMA-TM used runway allocation and an adaptation updated to include all aircraft types which, particularly for PHX west-flow operations, typically led to several aircraft scheduled on cross-over routes.…”

Section: System-level Evaluation Of Atd-1 Operationsmentioning

confidence: 99%

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

Prevôt

Smith

Palmer

et al. 2014

14th AIAA Aviation Technology, Integration, and Operations Conference

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The 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.

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Section: System-level Evaluation Of Atd-1 Operationsmentioning

confidence: 99%

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

Prevôt

Smith

Palmer

et al. 2014

14th AIAA Aviation Technology, Integration, and Operations Conference

Self Cite

View full text Add to dashboard Cite

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“…Additionally, TSS is coupled with the Controller-Managed Spacing (CMS) tool set. 2,3 The CMS tools support terminal controllers in achieving the scheduled plan by portraying three sets of information on the controllers' Standard Terminal Automation Replacement System (STARS) screen, as shown in Fig. 1: 1) A timeline displays the Expected Times of Arrival (ETAs) and the Scheduled Times of Arrival (STAs) of each aircraft at a fix point, usually a merge point.…”

Section: A Tbfm Solutions For Arrival Scheduling Problemsmentioning

confidence: 99%

“…Lastly, delay absorption is distributed across controllers and sectors, and as a result, reduces controller workload. [2][3][4]…”

Section: A Tbfm Solutions For Arrival Scheduling Problemsmentioning

confidence: 99%

Scheduling and Delivering Aircraft to Departure Fixes in the NY Metroplex with Controller-Managed Spacing Tools

Chevalley

Parke

Kraut

et al. 2015

15th AIAA Aviation Technology, Integration, and Operations Conference

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“…Also available was an aircraft's delay countdown information, displayed in the aircraft data block as well as in the meter list. TRACON tools included slot markers, speed advisories, and early / late indicators (Callantine, Hunt, & Prevot, 2014). All tools were designed to support the controllers in their task to deliver aircraft according to a scheduled arrival time.…”

Section: Management Toolsmentioning

confidence: 99%

“…The adaptations and subsequent performance of the HAT scale in both experimental environments is the focus of this paper. METHODS A full report on the simulations cited in this paper can be found in Mercer et al (2013) and Callantine, Hunt, & Prevot (2014) for Study 1 and Study 2, respectively. As Study 1 was conducted first, adaptations made to the HAT scale were further modified before use in Study 2.…”

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confidence: 99%

Adapting a Human – Automation Trust Scale to an Air Traffic Management Environment

Hunt

Martin

Mercer

2014

Proceedings of the Human Factors and Ergonomics Society Annual

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In response to the demand of future air traffic environments potentially exceeding human operator capabilities, the process of integrating automated decision-making tools into the air traffic management system is underway. However, the current system is lacking a validated standard for measuring a critical element of the human-automation partnership-trust. Specifically needed is a valid scale appropriate for and tested on air traffic controllers. To remedy this issue, a two-phase modification of the Human Automation Trust Scale by Jian, Bisantz and Drury (2000) was deployed at the Airspace Operations Laboratory at NASA Ames during 2013. Applied to two different human-in-the-loop experiments, the following results include a scale that supports understanding underlying trust attitude in air traffic controllers while maintaining a high inter-item reliability score. The use of this assessment method when testing new air traffic management tools can assist in understanding potential pitfalls for tool use and implementation. INTRODUCTION The next generation of air traffic control in the United States (NextGen) is evolving into an integrated humanautomation environment, with automation generated information becoming a critical contributor to decisionmaking (Joint Planning and Development Office, 2012). As this integration continues, it becomes increasingly necessary to appropriately assess the human-automation relationship as it pertains to decision-making and safety critical tasks. Underlying trust is one component that has been identified as a key (though not sole) contributor to intent to use and actual usage of an automated system (Lee & Moray, 1994). As such, developing a reliable method for measuring underlying trust is necessary in the assessment of human-automation integration. In the current air traffic control domain where most systems are very safe and the goal is near-perfect performance i.e., delivering aircraft safely and on time, the general underlying trust attitude (Lee & See, 2004) of a controller in regards to an automated system is of as much concern as their ability to detect envrionmentally (such as an incorrect weather forecast) induced inaccuracies / unreliabilities requiring a change in automated tool use by a controller (Kirlik,1993). As such, measuring actual general underlying trust of controllers in an automated system necessitates a method which is not highly sensitive to direct experimental manipulation of envrionmental factors impacting the current accuracy of the automation, but instead responds to their underlying attitude, knowledge in and trust of the system. To this end, in 2013, researchers in the Airspace Operations Laboratory (AOL) at NASA Ames employed modified versions of the Human-Automation Trust Scale (HAT) (Jian, Bisantz, & Drury, 2000) during two human-inthe-loop simulations to assess its efficacy in an air traffic management (ATM) environment. HAT was selected specifically for its empirically based assessment method, and its track record of use in different automated domai...

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Simulation evaluation of controller-managed spacing tools under realistic operational conditions

Cited by 5 publications

References 1 publication

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

Scheduling and Delivering Aircraft to Departure Fixes in the NY Metroplex with Controller-Managed Spacing Tools

Adapting a Human – Automation Trust Scale to an Air Traffic Management Environment

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