Association Between Driver-Reported Sleep and Predicted Levels of Effectiveness Based on the Fatigue Avoidance Scheduling Tool

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Association Between Driver-Reported Sleep and Predicted Levels of Effectiveness Based on the Fatigue Avoidance Scheduling Tool
Christopher D. Bertram

Current military operations require a high state of operational readiness. Service members and civilian workers are tasked with performing in a near non-stop environment without proper rest and recuperation. Unit and individual effectiveness depend upon initiative, judgment, courage, and motivation, which are all enhanced by the ability to think clearly and logically – attributes that are degraded by fatigue. This thesis seeks to determine the extent to which fatigue plays a part in human factors related to large truck mishaps. This study is conducted using the Large Truck Crash Causation Study data base and assesses drivers’ predicted level of effectiveness employing the Sleep, Activity, Fatigue, and Task Effectiveness Model as instantiated in the Fatigue Avoidance Scheduling Tool (FAST). The entire population of truck crashes is categorized into two groups, those with human factors causes and those with non-human factors causes. A comparison of the two groups shows a statistically significant difference between the two groups in reported sleep and predicted levels of effectiveness. This result shows that fatigue is more prevalent and is potentially an important contributing factor to human factors related mishaps. Heightened levels of fatigue diminish situational awareness, judgment, and decision-making capabilities and can result in serious, sometimes even deadly consequences. It is recommended that fatigue avoidance strategies such as FAST be implemented in training and operational planning. Such strategies can assist in the development of more efficient and potentially safer sleep-work schedules