Drowsiness Mitigation Through Driver State Monitoring Systems: A Scoping Review.

IF 2.9 3区 心理学 Q1 BEHAVIORAL SCIENCES
Human Factors Pub Date : 2024-09-01 Epub Date: 2023-11-20 DOI:10.1177/00187208231208523
Suzan Ayas, Birsen Donmez, Xing Tang
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引用次数: 0

Abstract

Objective: To explore the scope of available research and to identify research gaps on in-vehicle interventions for drowsiness that utilize driver monitoring systems (DMS).

Background: DMS are gaining popularity as a countermeasure against drowsiness. However, how these systems can be best utilized to guide driver attention is unclear.

Methods: A scoping review was conducted in adherence to PRISMA guidelines. Five electronic databases (ACM Digital Library, Scopus, IEEE Xplore, TRID, and SAE Mobilus) were systematically searched in April 2022. Original studies examining in-vehicle drowsiness interventions that use DMS in a driving context (e.g., driving simulator and driver interviews) passed the screening. Data on study details, state detection methods, and interventions were extracted.

Results: Twenty studies qualified for inclusion. Majority of interventions involved warnings (n = 16) with an auditory component (n = 14). Feedback displays (n = 4) and automation takeover (n = 4) were also investigated. Multistage interventions (n = 12) first cautioned the driver, then urged them to take an action, or initiated an automation takeover. Overall, interventions had a positive impact on sleepiness levels, driving performance, and user evaluations. Whether interventions effective for one type of sleepiness (e.g., passive vs. active fatigue) will perform well for another type is unclear.

Conclusion: Literature mainly focused on developing sensors and improving the accuracy of DMS, but not on the driver interactions with these technologies. More intervention studies are needed in general and for investigating their long-term effects.

Application: We list gaps and limitations in the DMS literature to guide researchers and practitioners in designing and evaluating effective safety systems for drowsy driving.

通过驾驶员状态监测系统缓解困倦:范围审查。
目的:探索现有研究的范围,并确定利用驾驶员监测系统(DMS)对车内困倦进行干预的研究差距。背景:DMS作为一种对抗困倦的方法越来越受欢迎。然而,如何最好地利用这些系统来引导驾驶员的注意力尚不清楚。方法:根据PRISMA指南进行范围审查。五个电子数据库(ACM Digital Library, Scopus, IEEE Xplore, TRID和SAE Mobilus)于2022年4月进行了系统检索。在驾驶环境中使用DMS检查车内困倦干预的原始研究(例如驾驶模拟器和驾驶员访谈)通过了筛选。提取了有关研究细节、状态检测方法和干预措施的数据。结果:20项研究符合纳入条件。大多数干预包括警告(n = 16)和听觉成分(n = 14)。反馈显示(n = 4)和自动化接管(n = 4)也进行了调查。多阶段干预(n = 12)首先警告司机,然后敦促他们采取行动,或者启动自动化接管。总体而言,干预措施对困倦程度、驾驶性能和用户评价有积极影响。干预措施是否对一种类型的困倦有效(例如,被动与主动疲劳),是否对另一种类型的困倦效果良好尚不清楚。结论:文献主要集中在传感器的开发和DMS精度的提高上,而不是驾驶员与这些技术的相互作用。总的来说,需要更多的干预研究,并调查其长期影响。应用:我们列出了DMS文献中的差距和局限性,以指导研究人员和从业人员设计和评估有效的疲劳驾驶安全系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Human Factors
Human Factors 管理科学-行为科学
CiteScore
10.60
自引率
6.10%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Human Factors: The Journal of the Human Factors and Ergonomics Society publishes peer-reviewed scientific studies in human factors/ergonomics that present theoretical and practical advances concerning the relationship between people and technologies, tools, environments, and systems. Papers published in Human Factors leverage fundamental knowledge of human capabilities and limitations – and the basic understanding of cognitive, physical, behavioral, physiological, social, developmental, affective, and motivational aspects of human performance – to yield design principles; enhance training, selection, and communication; and ultimately improve human-system interfaces and sociotechnical systems that lead to safer and more effective outcomes.
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