Fatigue prediction |
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Prediction of fatigue by mathematical fatigue models
Determinants of fatigue
The main determinants of fatigue are the time of the day (i.e. the circadian rhythm), time since last sleep and time on task.
Fatigue resulting from performing a task (i.e. the time on task component) superimposes
circadian and sleep-related fatigue. Breaks between tasks are supposed to "set back"
fatigue to the value which is caused by the combined influence of the time of the day and sleep related factors.
Purpose of fatigue models
Computer programmes (e.g. the DLR-programme "ALERT") have been constructed on the basis of mathematical models
of the main determinants of fatigue. These programmes can be used to predict phases of critically increased fatigue
during a traffic operation. The programmes enable drivers and schedulers to plan operations and rosters
carefully to keep alertness at an acceptable level.
Validation
For mathematical fatigue models to be accurate, the impact of the different determinants have to be
quantified. To this end, fatigue data have to be obtained from drivers of different transport modes (e.g. truck,
aeroplane, rail transport) at different times of the day, considering the time since last sleep and time on duty.
Activities
ALERT is used in the training of drivers and schedulers to demonstrate the effects of inappropriate schedules on fatigue and performance. At the same time it can be shown how (small) changes in schedules can have large impacts on fatigue, i.e. reduce phases of decreased alertness. Second, experiments are being conducted investigating the effect of the time on task component on fatigue
Members of the working group
Speaker: Alexander Dr. Gundel, German Aerospace Centre (DLR)
Institute for Sociology of Traffic, Automobile-Club of Germany (AvD; see there: "Presse")
Daimler-Chrysler AG Stuttgart, Research and Technology
German Insurance Association (GDV)
University of Applied Sciences Schmalkalden, Prof. Dr. Michael Golz
University of Cologne, Prof. Dr. Niels Galley
University of Regensburg, Prof. Dr. Jürgen Zulley
Volkswagen AG
For more information on the institutions see Members
