Crewcut - a Tool for Modeling the Effects of High Workload on Human Performance

Hahler, Beth; Dahl, Susan; Laughery, Ron; Lockett, John; Thein, Brenda

doi:10.1177/154193129103501708

Cited by 3 publications

(2 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Performance, in this case, is computed as (1 -NormalizedExecutionTime), which associates faster implementation times with better performance. As we see from Figure 3, the directive leadership style correlates to faster execution times than the transactional leadership style, but results in higher workload on the human operator, which is perhaps the greatest contributor to human error in many systems [21]. In directive leadership scenarios, a faster execution time is more desired than reducing the workload on the human operator, so directive behavior is more applicable to improving team efficiency.…”

Section: Test Resultsmentioning

confidence: 88%

Adapting Human Leadership Approaches for Role Allocation in Human-Robot Navigation Scenarios

Howard

Cruz

2006

2006 World Automation Congress

View full text Add to dashboard Cite

In this paper, we propose to examine the practices of leadership defined in human relationships and model their use in maximizing performance for human-robot interaction scenarios. This process involves first defining the human-robot space of interaction and mapping the situational context in which human leadership styles are most fitting. We then determine which behavior, for both the human and robot, is most appropriate in order to understand the proper roles for human-robot integration. From there, we model the necessary robot behavior for increasing efficiency in human-robot interaction schemes. We conclude by discussing experimental results derived from allocating roles in representative human-robot navigation scenarios.

show abstract

Section: Test Resultsmentioning

confidence: 88%

Adapting Human Leadership Approaches for Role Allocation in Human-Robot Navigation Scenarios

Howard

Cruz

2006

2006 World Automation Congress

View full text Add to dashboard Cite

show abstract

“…Perhaps the greatest contributor to human error in many systems is the extensive workload placed upon the human operator [8]. Workload studies are used to characterize human performance in terms of total mental demand placed on a person implementing a task.…”

Section: A Scenario Decompositionmentioning

confidence: 99%

A Systematic Approach to Predict Performance of Human–Automation Systems

Howard¹

2007

IEEE Trans. Syst., Man, Cybern. C

View full text Add to dashboard Cite

This paper discusses an approach for predicting system performance resulting from humans and robots performing repetitive tasks in a collaborative manner. The methodology uses a systematic approach that incorporates the various effects of workload on human performance, and estimates resulting performance attributes derived between teleoperated and autonomous control of robotic systems. Performance is determined by incorporating capabilities of the human and robotic agent based on accomplishment of functional operations and effect of cognitive stress due to continuous operation by the human agent. This paper provides an overview of the prediction system and discusses its implementation on a simulated rendezvous/docking task.

show abstract

Computer Modeling of a Nuclear Power Plant Operating Crew to Aid in Analysis of Crew Size Issues

Plott¹,

Scott-Nash²,

Hallbert

et al. 1995

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

An analytical approach to addressing the implications of nuclear power plant shift sizing is needed as an augmentation to the classical empirical approach. The research reported in this paper was to evaluate the feasibility and validity of one potential analytical approach as a means of evaluating the consequences of crew reduction on crew performance in a nuclear power plant setting. The approach selected for analysis was task network modeling and simulation using a tool named Micro Saint. Task network modeling allows the human factors engineer to extend the information from a task analysis and generate a computer simulation of crew performance that can predict critical task times and error rates. Through modeling, the current and proposed processes can be evaluated and analyzed in order to understand, identify, and test opportunities for process improvement or reengineering. For this effort, models of a conventional nuclear power plant during four extremely demanding scenarios were developed. Task analysis and timing data were collected at the Imatran Voima Nuclear Power Plant at Loviisa, Finland. The task analyses were collected over a two week period by interviewing reactor operators, reviewing procedures, and conducting walk-throughs. We then refined the models and incorporated workload modeling constructs. At the completion of the modeling effort, the models were executed and the data collected were used to predict crew performance in varying staffing conditions.

show abstract

Crewcut - a Tool for Modeling the Effects of High Workload on Human Performance

Cited by 3 publications

References 2 publications

Adapting Human Leadership Approaches for Role Allocation in Human-Robot Navigation Scenarios

Adapting Human Leadership Approaches for Role Allocation in Human-Robot Navigation Scenarios

A Systematic Approach to Predict Performance of Human–Automation Systems

Computer Modeling of a Nuclear Power Plant Operating Crew to Aid in Analysis of Crew Size Issues

Contact Info

Product

Resources

About