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驾驶人疲劳监测预警技术研究与应用综述
引用本文:程文冬,付锐,袁伟,郭应时.驾驶人疲劳监测预警技术研究与应用综述[J].中国安全科学学报,2013(1):155-160.
作者姓名:程文冬  付锐  袁伟  郭应时
作者单位:长安大学汽车运输保障技术交通行业重点实验室;西安工业大学机电工程学院
基金项目:长江学者和创新团队发展计划项目(IRT1286);陕西省自然科学基础研究计划重点项目(2012JZ8004);汽车运输安全保障技术交通行业重点实验室2013年开放基金
摘    要:基于各种物理传感器的疲劳驾驶监测预警技术(DFMP),是交通安全领域的研究重点。这类技术主要包括基于驾驶人生理特征、车辆运行状态以及驾驶人行为特征的疲劳监测。分析论述各种疲劳监测技术的研究现状与进展、优缺点以及应用状况,介绍目前世界上常用的疲劳监测系统。通过分析比较得出:车道偏离监测、车辆运动参数监测、基于人眼、头部运动以及面部状态的疲劳监测等是目前的热点研究方向;系统软硬件的提升、基于机器视觉的多传感器多参数信息融合等是疲劳监测技术重要的发展趋势;更强的实时性、准确性和鲁棒性是疲劳监测技术的发展目标。

关 键 词:疲劳驾驶  生理指标  车道偏离  行为特征  信息融合

Overview of Researches on Driver Fatigue Monitoring and Prewarning Technologies and Their Applications
CHENG Wen-dong,FU Rui,YUAN Wei,GUO Ying-shi.Overview of Researches on Driver Fatigue Monitoring and Prewarning Technologies and Their Applications[J].China Safety Science Journal,2013(1):155-160.
Authors:CHENG Wen-dong  FU Rui  YUAN Wei  GUO Ying-shi
Institution:1(1 Key Laboratory of Automotive Transportation Safety Technology,Ministry of Communication, Chang’an University,Xi’an Shaanxi 710064,China 2 School of Mechatronic Engineering,Xi’an Technological University,Xi’an Shaanxi 710032,China)
Abstract:One of the important development trends in traffic safety research is developing driver fatigue monitoring and prewarning(DFMP) technologies.The technologies typically include three categories being based respectively on driver's physical character,vehicle driving status and driver's behavior features.The necessity,present status and progress,advantage and disadvantage and application of the fatigue monitoring technologies were discussed.Some systems in common use in the world were introduced.Some important conclusions were obtained through a comparative analysis of all kinds of methods.The prevalent research area includes lane departure monitoring and warning,vehicle motion parameters monitoring,eye status,head motion and facial expression monitoring and so on.The advancement of hardware and software,information fusion with multiple sensors and multi-parameter based on machine vision are development trends of this technology.Much more powerful real-time performance,accuracy and robustness are development goals.
Keywords:fatigue driving  psychology index  lane departure  behavior feature  information fusion
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