Assessment of Driver Monitoring Systems for Alcohol Impairment Detection and Level 2 Automation

This report reviews and assesses driver monitoring systems (DMS) and related technologies for alcohol impairment detection and SAE International Level 2 partial driving automation systems. For the review of technologies to identify driver alcohol impairment, 331 technologies were reviewed. The systems were classified as physiology-based, tissue spectroscopy-based, camera-based, vehicle kinematics-based, hybrid, and patent-stage systems. A key focus was to review systems that are being developed to detect alcohol-related driving impairment, as well as systems that can estimate blood alcohol concentrations. Of the systems reviewed, no commercially available product was found to estimate the presence or amount of alcohol or identify alcohol impairment in the driver during the driving task. Behavioral indicators investigated included eye glances, facial features, posture, and vehicle kinematic metrics. Camera-based and most physiology-based DMS are still in stages of preliminary research and design for alcohol impairment detection. The efficacy of vehicle kinematic measures in identifying alcohol impairment is currently undetermined. Finally, hybrid systems that use two or more types of detection technologies are promising in being able to discern between driver states, due to the number of different measures used in making state determinations. The review of DMS for Level 2 partial driving automation systems involved a literature review, technology review, and interviews with subject matter experts. The literature review discusses driver attention, distraction, and drowsiness, and identifies measures that can be used to estimate driver state. The technology review identified two primary approaches to DMS for Level 2 partial driving automation: hands-on-wheel and eyes-on-road systems. The interviews included nine subject matter experts representing automotive manufacturers and suppliers as well as safety research organizations. Interviews addressed implementation approaches, alerting strategies, and capabilities and limitations of these approaches.

• Record URL:
  • https://rosap.ntl.bts.gov/view/dot/77647
• Corporate Authors:

  Battelle Memorial Institute

  Columbus, OH  United States 

  National Highway Traffic Safety Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Prendez, David M
  • Brown, James L
  • Venkatraman, Vindhya
  • Textor, Claire
  • Parong, Jocelyn
  • Robinson, Emanuel
• Publication Date: 2024-9

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: References; Tables;
• Pagination: 118p

Subject/Index Terms

• TRT Terms: Driver monitoring; Drunk driving; Highway safety; Level 2 driving automation
• Subject Areas: Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01935065
• Record Type: Publication
• Report/Paper Numbers: DOT HS 813 577, DOT-VNTSC-NHTSA-xx- xx
• Files: HSL, NTL, TRIS, USDOT
• Created Date: Oct 24 2024 9:41AM