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饮酒与驾车:酒精摄入对手动和自动驾驶性能影响的系统综述。

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

机构信息

Department of Industrial and Systems Engineering, San Jose State University One Washington Square, San Jose, CA 95192, USA.

Department of Industrial Engineering, Clemson University 268 Freeman Hall, Clemson, SC 29634, USA.

出版信息

J Safety Res. 2024 Jun;89:1-12. doi: 10.1016/j.jsr.2024.01.006. Epub 2024 Feb 9.

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.

摘要

简介

近三分之一的汽车事故涉及酒后驾驶。自动驾驶车辆(AV)可能提供预防事故的好处,但在当前的自动化水平下,当自动化系统出现故障时,驾驶员仍必须执行手动驾驶任务。因此,了解酒精如何影响手动和自动驾驶(接管)环境中的驾驶,可以深入了解未来车辆设计在调解因酒精而导致的驾驶事故风险方面的作用。

方法

本研究对酒精对手动和自动驾驶(接管)驾驶性能的影响进行了系统综述。从八个数据库中分析了 53 篇文章,研究结果基于信息处理模型进行了构建,该模型可以扩展到自动驾驶接管模型。

结果

文献表明,不同的血液酒精浓度(BAC)水平会影响到信息处理各个阶段对交通安全至关重要的驾驶技能,例如反应时间延迟、认知能力受损以及执行驾驶任务受阻。此外,驾驶员的驾驶经验、饮酒习惯和外部驾驶环境在影响驾驶性能方面起着重要作用。

结论

未来需要研究酒精对驾驶性能的影响,特别是在自动驾驶和接管情况下,并开发驾驶员监控系统。

实际应用

本综述的研究结果可为未来的实验、自动驾驶技术设计和驾驶员状态监控系统的开发提供信息。

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