@conference{driving 28302, author = {David J Edwards, Bill Sirois, Todd Dawson, Acacia Aguirre, Bill Davis, Udo Trutschel}, title = {Evaluation of Fatigue Management Technologies Using Weighted Feature Matrix Method}, volume = {4}, year = {2007}, url = {https://pubs.lib.uiowa.edu/driving/article/id/28302/}, issue = {2007}, doi = {10.17077/drivingassessment.1229}, abstract = {<p>Operator fatigue is one of the most prevalent root causes of accidents,both on the highway and in workplaces where heavy equipment is used and 12-hour shifts are employed, such as in the mining industry. In response to thisconcern, a growing number of Fatigue Management Technologies (FMT) arebecoming available to help maintain operator alertness and performance levels bydetecting operator fatigue and interfacing with the operator and/or supervisor toprevent accidents and incidents (Williamson et al., 2005, Barr et al., 2005). Inlight of the numerous competing technologies, the research community, as well asindustry, could benefit from the flexible evaluation tool proposed here. It willassist industries as a whole, and corporations more specifically, in identifying thebest FMT solutions for different work and/or driving situations. This project wasspecifically focused on the needs of operators of heavy equipment in the miningindustry, but could also be of value to other like industries where shift work isnecessary and maintaining high levels of alertness are crucial for ensuringworkplace safety and productivity.</p>}, month = {7}, pages = {146-152}, publisher={University of Iowa}, journal = {Driving Assessment Conference} }