Prendez, D. M., Brown, J. L., Venkatraman, V., Textor, C., Parong, J., & Robinson, E. (2024). Assessment of Driver Monitoring Systems for Alcohol Impairment Detection and Level 2 Automation (Report No. DOT HS 813 577). United States. Department of Transportation. National Highway Traffic Safety Administration. https://rosap.ntl.bts.gov/view/dot/77647
Prendez, David M, James L. Brown, Vindhya Venkatraman, Claire Textor, Jocelyn Parong, and Emanuel Robinson. Assessment of Driver Monitoring Systems for Alcohol Impairment Detection and Level 2 Automation. Report no. DOT HS 813 577. United States. Department of Transportation. National Highway Traffic Safety Administration, 2024. https://rosap.ntl.bts.gov/view/dot/77647.
Prendez, David M, et al. Assessment of Driver Monitoring Systems for Alcohol Impairment Detection and Level 2 Automation. United States. Department of Transportation. National Highway Traffic Safety Administration, 2024, Report no. DOT HS 813 577, ROSA P. https://rosap.ntl.bts.gov/view/dot/77647.
This report reviews and assesses driver monitoring systems (DMS) and related technologies for alcohol impairment detection and Level 2 partial driving automation systems. A key focus reviewed systems being developed to detect alcohol-caused driving impairment as well as systems that can precisely estimate blood alcohol concentrations. These were classified as physiology-based, tissue spectroscopy-based, camera-based, vehicle kinematics-based, hybrid (i.e., two or more technologies), and patent-stage systems. The review of DMS for Level 2 systems involved a literature review, technology review, and interviews with subject matter experts. The report describes the current state of the technology and practice, advantages and limitations of different approaches, and the readiness of these technologies to address targeted driver states.
Prendez, D. M., Brown, J. L., Venkatraman, V., Textor, C., Parong, J., & Robinson, E. (2024). Assessment of Driver Monitoring Systems for Alcohol Impairment Detection and Level 2 Automation (Report No. DOT HS 813 577). United States. Department of Transportation. National Highway Traffic Safety Administration. https://rosap.ntl.bts.gov/view/dot/77647
Prendez, David M, James L. Brown, Vindhya Venkatraman, Claire Textor, Jocelyn Parong, and Emanuel Robinson. Assessment of Driver Monitoring Systems for Alcohol Impairment Detection and Level 2 Automation. Report no. DOT HS 813 577. United States. Department of Transportation. National Highway Traffic Safety Administration, 2024. https://rosap.ntl.bts.gov/view/dot/77647.
Prendez, David M, et al. Assessment of Driver Monitoring Systems for Alcohol Impairment Detection and Level 2 Automation. United States. Department of Transportation. National Highway Traffic Safety Administration, 2024, Report no. DOT HS 813 577, ROSA P. https://rosap.ntl.bts.gov/view/dot/77647.
ROSA P serves as an archival repository of USDOT-published products including scientific
findings, journal articles, guidelines, recommendations, or other information authored or co-authored by
USDOT or funded partners. As a repository, ROSA P retains documents in their original published format to
ensure public access to scientific information.
Links with this icon indicate that you are leaving a Bureau of Transportation
Statistics (BTS)/National Transportation Library (NTL)
Web-based service.
Thank you for visiting.
You are about to access a non-government link outside of
the U.S. Department of Transportation's National
Transportation Library.
Please note: While links to Web sites outside of DOT are
offered for your convenience, when you exit DOT Web sites,
Federal privacy policy and Section 508 of the Rehabilitation
Act (accessibility requirements) no longer apply. In
addition, DOT does not attest to the accuracy, relevance,
timeliness or completeness of information provided by linked
sites. Linking to a Web site does not constitute an
endorsement by DOT of the sponsors of the site or the
products presented on the site. For more information, please
view DOT's Web site linking policy.
To get back to the page you were previously viewing, click
your Cancel button.