Predicting Subjective Workload Ratings: A Comparison and Synthesis of Operational and Theoretical Models

Jerry, Crutchfield; Rosenberg, Craig

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Predicting Subjective Workload Ratings: A Comparison and Synthesis of Operational and Theoretical Models

2007-03-01
By Jerry, Crutchfield ; Rosenberg, Craig

File Language:

English

Details

Creators:

Jerry, Crutchfield ; Rosenberg, Craig
Corporate Creators:

United States. Department of Transportation. Federal Aviation Administration. Office of Aviation. Civil Aerospace Medical Institute ; Boeing Company
Corporate Contributors:

United States. Department of Transportation. Federal Aviation Administration. Office of Aviation. Office of Aerospace Medicine
Subject/TRT Terms:
Publication/ Report Number:

DOT/FAA/AM-07/6
Resource Type:

Tech Report
Right Statement:

Public Domain
Geographical Coverage:

United States
Corporate Publisher:

United States. Department of Transportation. Federal Aviation Administration. Office of Aviation. Civil Aerospace Medical Institute
Abstract:

Output from a computer simulation of two air traffic control (ATC) scenarios was fit to workload ratings that ATC subject-matter experts provided while observing each scenario in real time. Simulation output enabled regression analyses that tested the assumptions of a variety of workload prediction models. These included both operational models that use observable situational and behavioral variables (e.g., number of aircraft and communications by type) and theoretical models that use queuing and cognitive architecture variables (e.g., activities performed, amount of busy time, and sensory and cognitive resource usage). Results suggested the models that included number of activities performed weighted by priority accounted for the highest amount of variance in subjective workload ratings.
Format:

PDF
Download URL:

https://rosap.ntl.bts.gov/view/dot/58395/dot_58395_DS1.pdf
File Type:

[PDF - 670.71 KB]
Collection(s):

FAA Civil Aerospace Medical Institute
Main Document Checksum:

urn:sha256:68d04d5cbb8ece64d9351d6f4a7c2fa6811e65c3901f63ea38e2a39c6c8b28cc

File Language:

English

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