Abstract：
BACKGROUND: 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.
METHODS: 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.
CONCLUSIONS: Findings from this review can inform future experiments, AV technology design, and the development of driver state monitoring systems.
METHODS: 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.
CONCLUSIONS: Findings from this review can inform future experiments, AV technology design, and the development of driver state monitoring systems.
摘要：
背景：几乎三分之一的车祸涉及饮酒后的驾驶。自动驾驶汽车(AV)可能会提供预防事故的好处，但是在目前的自动化水平上，当自动系统出现故障时，驾驶员仍必须执行手动驾驶任务。因此,了解酒精如何在手动和自动环境中影响驾驶，可以深入了解未来车辆设计在调节酒精受损驾驶的碰撞风险方面的作用。
方法：这项研究对酒精对手动和自动（接管）驾驶性能的影响进行了系统综述。对来自8个数据库的53篇文章进行了分析，基于信息处理模型构建的研究结果，可以扩展到AV接管模型。
结果：文献表明，不同的血液酒精浓度（BAC）水平会影响在各个信息处理阶段对交通安全至关重要的驾驶技能，例如延迟反应时间，认知能力受损，阻碍驾驶任务的执行。此外,司机的驾驶经验，饮酒习惯,外部驾驶环境在影响驾驶绩效方面起着重要作用。
结论：需要进一步研究酒精对驾驶表现的影响，特别是在AVs和接管情况下，并开发驾驶员监控系统。
结论：这篇综述的结果可以为未来的实验提供信息，AV技术设计，以及驾驶员状态监控系统的开发。
方法：这项研究对酒精对手动和自动（接管）驾驶性能的影响进行了系统综述。对来自8个数据库的53篇文章进行了分析，基于信息处理模型构建的研究结果，可以扩展到AV接管模型。
结果：文献表明，不同的血液酒精浓度（BAC）水平会影响在各个信息处理阶段对交通安全至关重要的驾驶技能，例如延迟反应时间，认知能力受损，阻碍驾驶任务的执行。此外,司机的驾驶经验，饮酒习惯,外部驾驶环境在影响驾驶绩效方面起着重要作用。
结论：需要进一步研究酒精对驾驶表现的影响，特别是在AVs和接管情况下，并开发驾驶员监控系统。
结论：这篇综述的结果可以为未来的实验提供信息，AV技术设计，以及驾驶员状态监控系统的开发。
