中文摘要：

采用主成分分析法研究了驾驶员的操纵动作模式主要成分结构,采用Matlab编写了主成分分析算法对问卷调查获得的数据进行了分析,并着重选取问卷中超车、转向和并线3种驾驶行为的数据,分析得到这3种驾驶行为对应的驾驶操纵动作模式的主成分载荷矩阵和贡献率。结果表明：通过研究驾驶行为及其对应的驾驶操纵动作模式,可以发现对特定驾驶行为影响较大的驾驶操纵动作,进而根据两者之间的关系反向实现个性化驾驶行为的识别,为后续设计先进的辅助驾驶系统提供技术依据。

英文摘要：

Principal component analysis （PCA） is adopted to study the main constitution structures of driver＇s operation modes and a PCA algorithm created with Matlab is used to analyze the data obtained by questionnaire, from which three sets of driver behavior data of overtaking, steering and cutting-in maneuver are in particular selected for analysis to obtain the loading matrix and contribution rate of PCA corresponding to those three operation modes. The results show that through the study on driver＇s behaviors and corresponding operation modes, the driving operation actions having more significant effects on specific driving behaviors can be found and hence the identification of personalized driving behaviors can be achieved inversely based on the relationship between them, providing a technique basis for subsequent design of advanced driver assistant system.