The Fatigue Avoidance Scheduling Tool: Modeling to Minimize the Effects of Fatigue on Cognitive Performance

计算机科学 调度(生产过程) 认知 工程类 心理学 运营管理 神经科学
作者
Steven R. Hursh,Thomas J. Balkin,James C. Miller,Douglas R. Eddy
出处
期刊:SAE technical paper series 被引量:48
标识
DOI:10.4271/2004-01-2151
摘要

Operator fatigue and time-of-day induced variations in cognitive effectiveness can lead to lapses in attention, slowed reactions, and impaired reasoning and decision-making that has been shown to contribute to accidents, incidents and errors in a host of industrial and military settings. During the past three years, the US Air Force has sponsored the development of a model of human fatigue and circadian variation and a scheduling tool based upon the model that will be used to minimize aircrew fatigue. The initial test version of the tool has passed review by the operational wings of the AF and a final operational product is in advanced development and validation. The software was developed by SAIC and NTI and is called the Fatigue Avoidance Scheduling Tool (FAST). This fatigue forecasting system is being developed and tested by NTI under a small business innovative research (SBIR) grant from the US Air Force, now in the third year of a three-year program. Fatigue predictions are derived from the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) model invented by Dr. Steven Hursh of SAIC. The patented SAFTE model has received a broad scientific review and the DoD considers it the most complete, accurate, and operationally practical model currently available to aid operator scheduling. The Department of Transportation is in the second phase of a three-phase project to validate and calibrate the model for avoiding excessive fatigue in transportation operations. The FAST scheduling tool uses the model to compare schedules in terms of predicted performance effectiveness. FAST allows easy entry of proposed schedules and generates graphical predictions of performance along with tables of estimated effectiveness scores for objective comparison. Optimal schedules may be selected based on average effectiveness for proposed work periods or mission critical events. The tool may also be used for retrospective analysis of fatigue related factors that may have contributed to an accident, error or safety related incident. In this mode, information on the work and sleep schedules of operators prior to the event may be entered into the tool and a projection of performance effectiveness at the time of the event is determined. In combination with other information, this analysis can project the combined effects of time of day and sleep history as a contributing factor to safety related events.
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