Procedures for Validation and Calibration of Human Fatigue Models: The Fatigue Audit InterDyne Tool
This report presents the results of a study that illustrates a procedure for validating and calibrating a biomathematical fatigue prediction model for evaluating work schedules. The validation has two components: (1) establishing that the model is consistent with science in the area of human performance, sleep, and fatigue, and (2) determining that the model has a statistically reliable relationship with the risk of a human factors (HF) accident and lacks a relationship with the risk of other accidents. Calibration is achieved by showing a statistically increasing relationship between cumulative risk of an HF accident and fatigue level. A railroad accident database containing work intervals for individuals involved in 732 HF accidents and 1944 nonhuman factors accidents was used to apply this process to the Fatigue Audit InterDyne (FAID) tool. Validation of FAID was achieved, but an alternative method, comparing a previously validated and calibrated model, was necessary to calibrate FAID.
- Record URL:
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Corporate Authors:
QinetiQ North America, Technology Solutions Group
350 Second Avenue
Waltham, MA United States 02451-1196Federal Railroad Administration
Office of Railroad Policy and Development, 1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Authors:
- Tabak, Barbara
- Raslear, Thomas G
- Publication Date: 2010-11
Language
- English
Media Info
- Media Type: Digital/other
- Edition: Final Report
- Features: Figures; References; Tables;
- Pagination: 36p
Subject/Index Terms
- TRT Terms: Calibration; Fatigue (Physiological condition); Forecasting; Hours of labor; Human factors in crashes; Mathematical models; Railroad crashes; Railroad safety
- Subject Areas: Railroads; Safety and Human Factors; I83: Accidents and the Human Factor;
Filing Info
- Accession Number: 01354570
- Record Type: Publication
- Report/Paper Numbers: DOT/FRA/ORD-10/14, DFRA.101152
- Files: TRIS, USDOT
- Created Date: Oct 21 2011 7:38AM