Non-intrusive Driver Fatigue and Stress Monitoring Using Ambient Vibration Sensing

An autonomous car would have to give back control to a capable driver when it is confronted by unusual road or weather conditions (e.g., snow covered roads with invisible road lane markings, other aggressive road users, unexpected events such as road lane closures, etc.). Such conditions may interfere with, or even blind, the embedded on-board sensors. Whereas human drivers have the ability to compensate and adapt to such conditions, the autonomous vehicle would be limited to only what its sensors can perceive. Before giving control back to the driver, it is essential for the car to know/estimate the state of the driver and determine whether the driver is capable of taking control or the car needs to take other cautious actions. To this end, the authors develop data analysis methods to 1) extract detailed driver’s physiological states (including movement, cardiovascular functions) and 2) infer higher level states (including stress, physical fatigue, and their physiological indicators such as heart rate and breathing rate), under various driving scenarios. The main challenge resides in high noise level due to the moving vehicle and sensing constraints relying only on contacts. To address these challenges, the authors utilize signal processing for multi-sourced, high-resolution and high frequency data with hybrid modeling approach to minimize uncertainties and obtain reliable information.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Research Report
  • Features: Figures; References;
  • Pagination: 8p

Subject/Index Terms

Filing Info

  • Accession Number: 01677422
  • Record Type: Publication
  • Contract Numbers: DTRT12GUTG11
  • Files: UTC, NTL, TRIS, ATRI, USDOT
  • Created Date: Jul 27 2018 9:06AM