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Survey of Methods to Predict Controller Workload for Real-Time Monitoring of Airspace SafetyThe Real Time Safety Monitoring (RTSM) approach allows for assessment and prediction of the safety margin in the National Airspace System (NAS) to help preempt incidents and accidents, rather than having to reactively mitigate them. In RTSM, the NAS is modeled using state variables, and safety metrics are defined in terms of these state variables. The safety metrics have been classified as weather-related, airspace-related, and human-related. Many of the formulated human-related safety metrics need an estimate of the controller workload for their computation. However, this computation is not trivial. Hence, in this report, we perform a literature survey to identify the different factors that enable the computation of controller workload and categorize these factors. Next, we describe studies undertaken to determine a minimal set of factors that pro- vide a correct assessment of controller workload. Lastly, we survey approaches for evaluating how well the selected factors correlate with the controllers' subjective assessment of their workload. Based on this survey, we present factors beneficial to computing and predicting controller workload in real time, and discuss the status of data sources necessary for these computations.
Document ID
20180006676
Acquisition Source
Ames Research Center
Document Type
Technical Memorandum (TM)
Authors
Roychoudhury, Indranil
(SGT, Inc. Moffett Field, CA, United States)
Spirkovska, Liljana
(NASA Ames Research Center Moffett Field, CA, United States)
Oconnor, Molly
(NASA Ames Research Center Moffett Field, CA, United States)
Kulkarni, Chetan
(SGT, Inc. Moffett Field, CA, United States)
Date Acquired
October 24, 2018
Publication Date
August 1, 2018
Subject Category
Air Transportation And Safety
Report/Patent Number
NASA/TM-2018-219985
ARC-E-DAA-TN60548
Funding Number(s)
CONTRACT_GRANT: NNA14AA60C
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
National Airspace System
safety monitoring
controller workload
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