Effect of drowsiness on driving performance variables of commercial vehicle drivers

• Published in: International journal of automotive technology Vol. 10; no. 3; pp. 391 - 404
• Main Authors: Mortazavi, A., Eskandarian, A., Sayed, R. A.
• Format: Journal Article
• Language: English
• Published: Heidelberg The Korean Society of Automotive Engineers 01.06.2009; Springer Nature B.V; 한국자동차공학회
• Subjects: Age; Automobile drivers; Automobile safety; Automotive Engineering; Engineering; Experiments; Fatalities; Fatigue; Intelligent systems; Sensors; Sleep; Studies; Traffic accidents & safety; Truck drivers; Trucks; Vehicles; 자동차공학; Commercial drivers; Drowsiness; Steering control; Lane keeping; Vehicle safety; Drowsiness detection
• ISSN: 1229-9138; 1976-3832
• DOI: 10.1007/s12239-009-0045-x

Driver drowsiness is a major safety concern, especially among commercial vehicle drivers, and is responsible for thousands of accidents and numerous fatalities every year. The design of a drowsiness detection system is based on identifying suitable driver-related and/or vehicle-related variables that are correlated to the driver’s level of drowsiness. Among different candidates, vehicle control variables seem to be more promising since they are unobtrusive, easy to implement, and cost effective. This paper focuses on in-depth analysis of different driver-vehicle control variables, e.g., steering angle, lane keeping, etc. that are correlated with the level of drowsiness. The goal is to find relationships and to characterize the effect of a driver’s drowsiness on measurable vehicle or driving variables and set up a framework for developing a drowsiness detection system. Several commercial drivers were tested in a simulated environment and different variables were recorded. This study shows that drowsiness has a major impact on lane keeping and steering control behavior. The correlation of the number and type of accidents with the level of drowsiness was also examined. Significant patterns in lateral position variations and steering corrections were observed, and two phases of drowsiness-related degradation in steering control were identified. The two steering degradation phases examined are suitable features for use in drowsiness detection systems.