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Non-intrusive Methods used to Determine the Driver Drowsiness: Narrative Review Articles

机译:用于确定驾驶员睡意的非侵入性方法:叙事评论文章

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REVIEW ARTICLE Driver drowsiness has been one of the main causes of on-road crashes which can lead to death, physical injuries and impose significant costs on the societies. The development of non-intrusive methods to be able to detect driver drowsiness in the early stages of drowsiness is great of importance. This is an educational review and its purpose is to provide recent achievements about non-intrusive techniques used to detect driver drowsiness. Recently published related articles were searched in the scientific databases such as Web of Sciences, Scoupous, Pubmed and Google scholar. By studying the articles and extracting the important information, non-intrusive drowsiness detection methods has classified in three distinct categories: Vehicle based measures, behavioral measures and non-intrusive physiologic methods. Each of mentioned categories has its own advantages and limitations. Vehicle based methods are strongly influenced by the road geometry, whether condition and lighting. By tracking the facial expression of the driver, drowsiness can be detected. The main limitation of this method is lighting, because the cameras do not function well at night. However, physiological parameters such as electroencephalography are more reliable than vehicle and behavioral measures, the intrusive nature of these methods limit their applications. In summary, combination of the mentioned method can reliably detect the drowsiness of the driver and further studies about the efficiency of the mentioned techniques in real environments are required.
机译:复习文章驾驶员的困倦一直是导致道路交通事故的主要原因之一,可能导致死亡,人身伤害并给社会带来沉重的代价。为了在睡意的早期阶段检测驾驶员的睡意,非侵入性方法的发展非常重要。这是一项教育性评论,其目的是提供有关用于检测驾驶员睡意的非侵入式技术的最新成果。在科学数据库(例如Web of Sciences,Scoupous,Pubmed和Google Scholar)中搜索了最近发表的相关文章。通过研究文章并提取重要信息,非侵入式睡意检测方法已分为三类:基于车辆的措施,行为措施和非侵入式生理方法。每个提到的类别都有其自身的优点和局限性。基于车辆的方法会受到道路几何形状(条件和照明)的强烈影响。通过跟踪驾驶员的面部表情,可以检测到睡意。这种方法的主要局限性是照明,因为相机在夜间无法正常工作。但是,诸如脑电图之类的生理参数比车辆和行为测量更可靠,这些方法的侵入性限制了它们的应用。总而言之,上述方法的组合可以可靠地检测驾驶员的睡意,并且需要进一步研究在实际环境中上述技术的效率。

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