Driving Fatigue Detection based on Blink Frequency and Eyes Movement

The development of the vehicle quantity and the transportation system accompanies the rise of traffic accidents. Statistics shows that nearly 35-45% traffic accidents are due to drivers’ fatigue. If the driver’s fatigue status could be judged in advance and reminded accurately, the driving safety could be further improved. In this research, the blink frequency and eyes movement information are monitored and the statistical method was used to assess the status of the driving fatigue. The main tasks include locating the edge of the human eyes, obtaining the distance between the upper and lower eyelids for calculating the frequency of the driver's blink. The velocity and position of eyes movement are calculated by detecting the pupils’ movement. The normal eyes movement model is established and the corresponding database is updated constantly by monitoring the driver blink frequency and eyes movement during a certain period of time. The real-time data and the model calculation data are compared, and the warning is given when the eyes movement flat rate is consistent with the sleep characteristics. The study found that when the driver is in the stage of fatigue driving, the blink frequency and the saccade velocity standard deviation will be reduced. On this basis, the judgment accuracy of the driver's driving condition can be accepted. This research would play a positive role in promoting the development of real-time detection technology of driving fatigue.

• Record URL:
  https://doi.org/10.4271/2017-01-1443
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
• Supplemental Notes:
  • Abstract reprinted with permission of SAE International.
• Authors:
  • ZiLin, Lu
  • Tan, Gangfeng
  • Pang, Yuxin
  • Tang, Yu
  • Qian, Keyu
• Conference:
  • WCX™ 17: SAE World Congress Experience
  • Location: Detroit Michigan, United States
  • Date: 2017-4-4 to 2017-4-6
• Publication Date: 2017-3-28

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Serial:
  • SAE Technical Paper
  • Publisher: Society of Automotive Engineers (SAE)
  • ISSN: 0148-7191
  • EISSN: 2688-3627
  • Serial URL: http://papers.sae.org/

Subject/Index Terms

• TRT Terms: Detection and identification; Drivers; Eye movements; Fatigue (Physiological condition); Highway safety; Human factors; Real time data processing; Statistical analysis
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01731648
• Record Type: Publication
• Source Agency: SAE International
• Report/Paper Numbers: 2017-01-1443
• Files: TRIS, SAE
• Created Date: Feb 21 2020 10:24AM