Fatigue and performance models: general background and commentary on the circadian alertness simulator for fatigue risk assessment in transportation.

Mathematical models of fatigue and performance are potentially powerful tools to predict the effects of duty-rest schedules in many situations. Most current models, including the Circadian Alertness Simulator (CAS), derive from the two-process theory of sleep regulation. In these models, performance and fatigue are determined by a homeostatic process that depends solely on sleep/wake history, and a circadian process, driven by the biological clock. These models assume: 1) performance capability recovers in an exponential manner during sleep; 2) the homeostatic and circadian processes are additive. Current evidence suggests that both assumptions require modification. An attractive feature of the CAS is that it computes alertness curves for individuals, based on individual sleep/wake histories and other data. However, statistical evaluation is usually based on group data, with few performance metrics. As in other models, there is no substantive theory to connect the alertness computation with specific cognitive or psychomotor functions.

Research requirements for operational decision-making using models of fatigue and performance.

Sustained human performance is critical to job and mission success in many federal agencies including national defense, aerospace exploration, and transportation. For the responsible agencies, applications of the basic biomedical and applied human factors science provide the best available solutions to help individuals perform more effectively and with increased safety. Key products of this research are biomathematical models that predict periods of impaired performance, with applications in planning tools, real time monitoring, and intervention decision aids. Since it is difficult to quantify the number of judgment errors or accidents averted, metrics of success for fatigue management systems must be largely based on the accuracy of performance predictions derived from laboratory-based research studies and the extent to which such results can be generalized to the field environment. Performance metrics must, at a minimum, be correlated with occupational task performance to demonstrate relevance to real-world applications. This paper outlines broad goals for human effectiveness research related to fatigue, alertness, and performance. To advance from the present state of knowledge to useful predictive models requires a well-coordinated commitment from federal agencies. Users should be made aware that current models and tests are not likely to encompass all of the aspects of human performance that are relevant to field environments and occupations.