Driver Assistance System With a Dual Control Scheme: Effectiveness of Identifying Driver Drowsiness and Preventing Lane Departure Accidents

• Published in: IEEE transactions on human-machine systems Vol. 46; no. 5; pp. 660 - 671
• Main Authors: Saito, Yuichi, Itoh, Makoto, Inagaki, Toshiyuki
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-10-2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accidents; Adaptive automation; advanced driver assistance systems (ADAS); Biomedical monitoring; driver behavior monitoring; dual control; Eyelids; Monitoring; Pressure measurement; Safety; Traffic accidents & safety; Vehicles
• ISSN: 2168-2291; 2168-2305
• DOI: 10.1109/THMS.2016.2549032

Driver drowsiness is a common cause of fatal traffic accidents. In this study, a driver assistance system with a dual control scheme is developed; it attempts to perform simultaneously the safety control of the vehicle and identification of the driver's state. The assistance system implements partial control in the event of lane departure and gives the driver the chance to voluntarily take the action needed. If the driver fails to implement the steering action needed within a limited time, the assistance system judges that "the driver's understanding of the given situation is incorrect" and executes the remaining control. We used a driving simulator equipped with the assistance system to investigate the effectiveness of identifying driver drowsiness and preventing lane departure accidents. Twenty students participated in three trials on a straight expressway, and they were required to implement only lateral control. We hypothesized that a participant cannot implement the action needed to maintain safety when he/she falls asleep, and that in such a case, the assistance system will implement the safety control repeatedly. The assistance system assisted the participants only when almost really needed, such as when their eyelids were closed. The results validated the hypothesis, showing that the assistance system implemented the safety control repeatedly when a participant fell asleep. In addition, the algorithms used by the assistance system to determine whether the driver can continue driving were evaluated through a leave-one-out cross-validation, and they were proven to be effective for identifying driver drowsiness.