DOI

10.17077/drivingassessment.1287

Location

Stevenson, Washington

Date

12-7-2007

Session

Session 9 – Hybrid

Abstract

Fatigue is one of the most pervasive yet under-investigated causes of human-error-related driving accidents, incidents, and injuries. Several studies suggest that 25-30% of driving accidents are fatigue related (Horne et al., 1995). However, government reports estimate that only 1-4% of crashes may be attributable to the driver falling asleep or being drowsy, based largely on data derived from police reports recorded at these accidents (Cummings et al., 2001). The reason for this wide disparity is that there is no simple tool or objective way for investigators to collect the (right) data needed to correlate accidents with fatigue. To bridge this gap, a diagnostic survey instrument was developed, along with a weighted risk model based on Fuzzy Scalable Monotonic Chaining (FSMC), to help investigators readily determine (by standardized criteria and with high probability) the role of fatigue as a causal factor in driving accidents.

Rights

Copyright © 2007 the author(s)

DC Citation

Proceedings of the Fourth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design, July 9-12, 2007, Stevenson, Washington. Iowa City, IA: Public Policy Center, University of Iowa, 2007: 527-533.

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Jul 12th, 12:00 AM

Assessing Driver Fatigue as a Factor in Road Accidents

Stevenson, Washington

Fatigue is one of the most pervasive yet under-investigated causes of human-error-related driving accidents, incidents, and injuries. Several studies suggest that 25-30% of driving accidents are fatigue related (Horne et al., 1995). However, government reports estimate that only 1-4% of crashes may be attributable to the driver falling asleep or being drowsy, based largely on data derived from police reports recorded at these accidents (Cummings et al., 2001). The reason for this wide disparity is that there is no simple tool or objective way for investigators to collect the (right) data needed to correlate accidents with fatigue. To bridge this gap, a diagnostic survey instrument was developed, along with a weighted risk model based on Fuzzy Scalable Monotonic Chaining (FSMC), to help investigators readily determine (by standardized criteria and with high probability) the role of fatigue as a causal factor in driving accidents.