摘要
基于脑电信号对紧急制动行为的分类识别和预测,是开发以人为中心的智能辅助驾驶系统的关键问题。为实现对驾驶过程中紧急制动和正常驾驶行为的分类识别,提出了基于PLV的特征表示方法来构建功能性脑网络,结合对网络特征参数的统计分析,确定显著性差异的特征参数,以及通过对数欧式距离提取脑电信号空域特征,并结合机器学习算法完成对紧急制动和正常驾驶行为的分类识别。实验结果表明,针对17名被试的紧急制动和正常驾驶的分类准确率均高于84%,最高准确率达到95.7%;对功能性脑网络的分析结果表明,在两种驾驶行为过程中,脑区间的交互都涉及全脑区,且在紧急制动过程中,脑区间的交互主要出现在额-中央-颞叶区,这与紧急制动下大脑更专注于判断决策相符。研究结果对理解驾驶过程中,尤其是紧急制动过程中驾驶员对应脑区间的依赖关系,以及开发智能辅助驾驶系统在驾驶过程中提前识别紧急制动意图具有一定的参考价值。
The classification and recognition of emergency braking behavior based on electroencephalography(EEG)is a key issue in the development of human-centered intelligent assisted driving systems.In order to realize the classification and recognition of emergency braking and normal driving behaviors during driving,a feature representation method based on Phase Locking Value(PLV)was proposed to construct functional brain networks,the feature parameters of significant differences are determined via statistical analysis of the network feature parameters,and the spatial features of EEG were extracted through Log-Euclidean distance.Combined with machine learning algorithm,emergency braking and normal driving behavior are classified and recognized.The results show that the accuracy of emergency braking and normal driving for 17 participants is higher than 84%,and the highest accuracy rate reaches 95.7%,and the analysis of functional brain network results show that in the process of two driving behaviors,the interaction between brain regions involves the whole brain area,and in the emergency braking process,the interaction between brain regions mainly occurs in the frontal-central-temporal lobe area,which is consistent with the brain focusing more on judgment and decision-making under emergency braking.The results of this paper have certain reference value for understanding the dependence between the driver’s corresponding brain zones during driving,especially during emergency braking,and for developing intelligent assisted driving systems to identify emergency braking intentions in advance during driving.
作者
袁月婷
闫光辉
常文文
张玉婵
YUAN Yueting;YAN Guanghui;CHANG Wenwen;ZHANG Yuchan(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Gansu Provincial Key Laboratory of Media Convergence Technology and Communication,Gansu Daily Newspaper Group,Lanzhou 730030,China)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2024年第1期84-91,共8页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(62062049,62366028)
甘肃省教育厅青年博士支持项目(2023QB-038)。
关键词
驾驶行为
紧急制动
脑电信号
脑功能网络
对数欧式距离
driving behavior
emergency braking
electroencephalography(EEG)
functional brain network
Log-Euclidean distance
作者简介
袁月婷,主要从事脑电信号分析方面的研究;通信作者:闫光辉,E-mail:yanghacademic@163.com。
