基于面部多特征融合的驾驶员疲劳驾驶监测系统  

Driver Fatigue Driving Monitoring System Based on Facial Multi-feature Fusion

作　　者：徐光光 张晶晶 刘姗姗 胥迅科 张娓娓[1] Xu Guangguang;Zhang Jingjing;Liu Shanshan;Xu Xunke;Zhang Weiwei

机构地区：[1]西安思源学院,陕西西安710038

出　　处：《时代汽车》2024年第22期186-188,共3页Auto Time

基　　金：2023年陕西国家级大学生创新创业训练计划项目(S202313121005)。

摘　　要：文章介绍了一种基于面部多特征融合的驾驶员疲劳驾驶监测系统。该系统通过分析驾驶员的驾驶行为,包括方向盘操作、车辆速度和驾驶员面部表情等,利用机器学习算法、标定算法、中值滤波算法对驾驶员的疲劳状态进行实时监测,并在发现驾驶员疲劳时给予提醒,从而降低因疲劳驾驶引发的交通事故的风险。文章详细阐述了系统的设计原理、实现方法和实验结果,并讨论了该系统的优缺点以及在实际应用中的适用性。This paper introduces a driver fatigue driving monitoring system based on facial multi-feature fusion.By analyzing the driver's driving behavior,including steering wheel operation,vehicle speed and driver's facial expression,the system uses machine learning algorithms,calibration algorithms,and median filtering algorithms to monitor the driver's fatigue state in real time,and reminds the driver when fatigue is found,so as to reduce the risk of traffic accidents caused by fatigue driving.In this paper,the design principle,implementation method and experimental results of the system are elaborated in detail,and the advantages and disadvantages of the system and its applicability in practical application are discussed.

关 键 词：机器学习 中值滤波算法 疲劳驾驶 监测系统 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]