计算机应用与软件2011，Vol.28Issue(10)：43-46,4.
基于HMM的驾驶员疲劳识别在智能汽车空间的应用
APPLYING HMM-BASED DRIVER FATIGUE RECOGNITION IN SMART VEHICLE SPACE
摘要
Abstract
Smart vehicle space is a specific and focused performance of pervasive computing; this paper presents an application about driver fatigue recognition based on hidden Markov model ( HMM). The authors select PERCLOS feature variable as a low-level context of driver fatigue evaluation, and establish the HMM through a large number of sample data training. Then they identify the most likely driver's hidden state from the observation sequence using Viterbi algorithm,and remind drivers to ensure their safe driving behaviour. Finally, a case study in simulation environment confirmed the validity of the scheme.关键词
智能汽车空间/隐马尔科夫模型/上下文推理/驾驶员疲劳/PERCLOSKey words
Smart vehicle space/HMM/Context reasoning/Driver fatigue/PERCLOS分类
信息技术与安全科学引用本文复制引用
郁伟炜,吴卿..基于HMM的驾驶员疲劳识别在智能汽车空间的应用[J].计算机应用与软件,2011,28(10):43-46,4.基金项目
国家自然科学基金项目(60703088) （60703088）
