Human Performance Modeling of Reduced Manning Concepts for Navy Ships

WinCrew is a human performance assessment tool developed by the Army Research Laboratory, Human Research and Engineering Directorate that implements the Wickens' Theory of Multiple Resources. WinCrew supports the hierarchical decomposition of missions into functions and tasks. As a demonstration of the capability of WinCrew, simulation models of the activities performed by bridge personnel on a Navy Guided Missile Destroyer DDG51 were developed. The scenarios were chosen to illustrate the potential of task network based human performance modeling to address reduced manning issues for naval ship operations. In order to fully exercise the functionality of WinCrew, four bridge models were developed. One scenario was modeled for four different manning, automation, and task allocation configurations. The scenario modeled was entry into San Diego Harbor. The major events for the bridge team were: bearing fixes, gyro error checks, turns, precision anchoring, and obstacle avoidance. Results of the effort demonstrated the utility of workload modeling for assessing human system integration alternatives for shipboard manning.

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Workload Warriors: Lessons Learned from a Decade of Mental Workload Prediction Using Human Performance Modeling

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193120905301212 ◽

2009 ◽

Vol 53 (12) ◽

pp. 819-823 ◽

Cited By ~ 1

Author(s):

Diane Kuhl Mitchell ◽

Charneta Samms

Keyword(s):

Human Behavior ◽

Human Performance ◽

Performance Modeling ◽

Mental Workload ◽

Lessons Learned ◽

Experimental Conditions ◽

Workload Prediction ◽

Army Research Laboratory ◽

Performance Predictions ◽

Concept Vehicle

For at least a decade, researchers at the Army Research Laboratory (ARL) have predicted mental workload using human performance modeling (HPM) tools, primarily IMPRINT. During this timeframe their projects have matured from simple models of human behavior to complex analyses of the interactions of system design and human behavior. As part of this maturation process, the researchers learned: 1) to develop a modeling question that incorporates all aspects of workload, 2) to determine when workload is most likely to affect performance, 3) to build multiple models to represent experimental conditions, 4) to connect performance predictions to an overall mission or system capability, and 5) to format results in a clear, concise format. By implementing the techniques they developed from these lessons learned, the researchers have had an impact on major Army programs with their workload predictions. Specifically, they have successfully changed design requirements for future concept Army vehicles, substantiated manpower requirements for fielded Army vehicles, and made Soldier workload the number one item during preliminary design review for a major Army future concept vehicle program. The effective techniques the ARL researchers developed for their IMPRINT projects are applicable to other HPM tools. In addition, they can be used by students and researchers who are doing human performance modeling projects and are confronted with similar problems to help them achieve project success.

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Human performance modeling using the signal detection paradigm

PsycEXTRA Dataset ◽

10.1037/e574122012-015 ◽

1983 ◽

Author(s):

John F. McGrew

Keyword(s):

Signal Detection ◽

Human Performance ◽

Performance Modeling

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Human performance modeling for operational Command, Control and Communication

PsycEXTRA Dataset ◽

10.1037/e577362012-018 ◽

2005 ◽

Author(s):

Jeffrey T. Hansberger ◽

Diane Barnette

Keyword(s):

Human Performance ◽

Performance Modeling

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Impacting system design with human performance modeling and experiment: Another success story

PsycEXTRA Dataset ◽

10.1037/e577772012-003 ◽

2006 ◽

Author(s):

Diane K. Mitchel ◽

Jessie Y. C. Chen

Keyword(s):

System Design ◽

Human Performance ◽

Performance Modeling ◽

Success Story

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The Effect of Processing Code, Response Modality and Task Difficulty on Dual Task Performance and Subjective Workload in a Manual System

Proceedings of the Human Factors Society Annual Meeting ◽

10.1177/154193128703100736 ◽

1987 ◽

Vol 31 (7) ◽

pp. 847-851 ◽

Cited By ~ 4

Author(s):

Yili Liu ◽

Christopher D. Wickens

Keyword(s):

Task Performance ◽

Dual Task ◽

Task Difficulty ◽

Task Structure ◽

Time Sharing ◽

Multiple Resources ◽

Response Modality ◽

Dual Task Performance ◽

Processing Resources ◽

And Task

We report here the first experiment of a series studying the effect of task structure and difficulty demand on time-sharing performance and workload in both automated and corresponding manual systems. The experimental task involves manual control time-shared with spatial and verbal decisions tasks of two levels of difficulty and two modes of response (voice or manual). The results provide strong evidence that tasks and processes competing for common processing resources are time shared less effectively and have higher workload than tasks competing for separate resources. Subjective measures and the structure of multiple resources are used in conjunction to predict dual task performance. The evidence comes from both single task and from dual task performance.

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