Detecting driver drowsiness based on sensors: a review.
Detecting driver drowsiness based on sensors: a review.
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DOI：
10.3390/s121216937
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发表时间：
2012-12-07
期刊：
影响因子：
--
通讯作者：
Murugappan M
中科院分区：
文献类型：
--
作者：
Sahayadhas A;Sundaraj K;Murugappan M
近年来，驾驶员困倦已成为道路交通事故的主要原因之一，可导致严重的身体伤害、死亡和重大的经济损失。统计数据表明，需要一个可靠的驾驶员困倦检测系统，可以提醒驾驶员之前，事故发生。研究人员尝试使用以下测量来确定驾驶员困倦：（1）基于车辆的测量;（2）行为测量和（3）生理测量。对这些措施进行详细审查，将有助于深入了解现行制度、与之相关的问题以及为建立一个健全的制度而需要进行的改进。在本文中，我们回顾了这三种措施所使用的传感器，并讨论了各自的优点和局限性。还讨论了通过实验操纵困倦的各种方法。我们的结论是，通过设计一个混合困倦检测系统，结合非直观的生理措施与其他措施，将准确地确定驾驶员的困倦程度。如果向被认为昏昏欲睡的司机发送警报，那么许多道路事故就可以避免。
In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens. Researchers have attempted to determine driver drowsiness using the following measures: (1) vehicle-based measures; (2) behavioral measures and (3) physiological measures. A detailed review on these measures will provide insight on the present systems, issues associated with them and the enhancements that need to be done to make a robust system. In this paper, we review these three measures as to the sensors used and discuss the advantages and limitations of each. The various ways through which drowsiness has been experimentally manipulated is also discussed. We conclude that by designing a hybrid drowsiness detection system that combines non-intusive physiological measures with other measures one would accurately determine the drowsiness level of a driver. A number of road accidents might then be avoided if an alert is sent to a driver that is deemed drowsy.
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DOI：
10.1109/titb.2011.2175742
发表时间：
2012-01-01
影响因子：
--
作者：
Baek, Hyun Jae;Chung, Gih Sung;Park, Kwang Suk
通讯作者：
Park, Kwang Suk
DOI：
10.3390/s110706799
发表时间：
2011
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Hii PC;Chung WY
通讯作者：
Chung WY
影响因子：
6
作者：
Akin, Mehmet;Kurt, Muhammed B.;Bayram, Muhittin
通讯作者：
Bayram, Muhittin
影响因子：
8.5
作者：
Hu Shuyan;Zheng Gangtie
通讯作者：
Zheng Gangtie
影响因子：
3.3
作者：
Blana, E;Golias, J
通讯作者：
Golias, J