Driver Drowsiness Warning System Using Visual Information for Both Diurnal and Nocturnal Illumination Conditions

Every year, traffic accidents due to human errors cause increasing amounts of deaths and injuries globally. This article presents a new module for an Advanced Driver Assistance System (ADAS) which deals with automatic driver drowsiness detection based on visual information and artificial intelligence. This system locates, tracks, and analyzes the driver’s face and eyes to compute a drowsiness index. The real-time system works under varying light conditions (diurnal and nocturnal driving). Examples of different images of drivers taken in a real vehicle are shown to validate the algorithms used. The authors conclude that the algorithm proposed for eye detection, face tracking, and eye tracking is shown to be robust and accurate for varying light, external illumination interference, vibrations, changing backgrounds, and facial orientations. The goal of the system is to automatically estimate the driver’s drowsiness and to prevent drivers falling asleep at the wheel.

• Authors:
  • Flores, Marco Javier
  • Armingol, Jose Maria
  • De la Escalera, A
• Publication Date: 2010

Language

• English

Media Info

• Media Type: Print
• Features: Figures; Photos; References; Tables;
• Pagination: 19p
• Serial:
  • Journal of Advances in Signal Processing
  • Volume: 2010
  • Issue Number: 438205
  • Publisher: Hindawi Publishing Corporation

Subject/Index Terms

• TRT Terms: Daytime crashes; Detection and identification systems; Driver monitoring; Driver support systems; Drowsiness; Eye movements; Face; Fatigue (Physiological condition); Nighttime crashes; Periods of the day; Real time information; Sensors; Sleep disorders
• Subject Areas: Highways; Safety and Human Factors; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 01351536
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 6 2011 3:00PM