Systems approach to the design of locomotive fatigue management technologies

摘要

Falling asleep while operating a vehicle leads to serious accidents and loss of lives. The challenge of detecting drowsiness nonintrusively stems from the absence of a single marker, and the existence of diverse signs and symptoms that collectively but not uniquely characterize it. Current alerters for locomotive cabs are inadequate partly because they a) often monitor one modality b) fail to consider the inherent characteristics of the locomotive operator tasks and physical environment, and c) are typically developed without quantitative techniques to assess performance and optimize components as part of an overall system, rather than at the individual level. Based on an estimation theory framework, a new systems approach is here proposed to design locomotive cab alerting technologies. The main idea is to combine information from an infrared eyelid monitor and a generic Train Sentry class activity monitor, to isolate the common drowsiness component and obtain an improved estimate of the operator's state. A study first quantified the important physical aspects of the locomotive cab and engineer behavior pertinent to the performance of image-based eye closure monitors.