Drinking and driving: A systematic review of the impacts of alcohol consumption on manual and automated driving performance

Publication Date

6-1-2024

Document Type

Article

Publication Title

Journal of Safety Research

Volume

89

DOI

10.1016/j.jsr.2024.01.006

First Page

1

Last Page

12

Abstract

Introduction: Almost a third of car accidents involve driving after alcohol consumption. Autonomous vehicles (AVs) may offer accident-prevention benefits, but at current automation levels, drivers must still perform manual driving tasks when automated systems fail. Therefore, understanding how alcohol affects driving in both manual and automated contexts offers insight into the role of future vehicle design in mediating crash risks for alcohol-impaired driving. Method: This study conducted a systematic review on alcohol effects on manual and automated (takeover) driving performance. Fifty-three articles from eight databases were analyzed, with findings structured based on the information processing model, which can be extended to the AV takeover model. Results: The literature indicates that different Blood Alcohol Concentration (BAC) levels affect driving skills essential for traffic safety at various information processing stages, such as delayed reacting time, impaired cognitive abilities, and hindered execution of driving tasks. Additionally, the driver's driving experience, drinking habits, and external driving environment play important roles in influencing driving performance. Conclusions: Future work is needed to examine the effects of alcohol on driving performance, particularly in AVs and takeover situations, and to develop driver monitoring systems. Practical applications: Findings from this review can inform future experiments, AV technology design, and the development of driver state monitoring systems.

Funding Number

69A3551747127

Funding Sponsor

U.S. Department of Transportation

Keywords

Alcohol-impaired driving, Automated Driving, Blood Alcohol Concentration, Information Process Model, Systematic Review

Department

Industrial and Systems Engineering

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