关键词: 数据处理；特征选择；驾驶风格聚类；NGSIM 数据库

Abstract: Driving style is used to represent the behavior characteristics of drivers. It is of great value to develop automatic driving technology and formulate personalized driving strategies. Based on the vehicle driving state data in the American NGSIM database, this paper selects nine statistics such as the mean of the absolute value of transverse speed, the standard deviation of the absolute value of transverse speed and the standard deviation of the absolute value of longitudinal speed as the characteristic variables, and uses the dimension reduction algorithm of principal component analysis and K-means clustering algorithm to classify the driving style of the driving data, and divides the driving styles into conservative, general, radical three types. The data analysis shows that the statistics of the mean transverse speed, the mean longitudinal acceleration and the mean transverse and longitudinal impact of the conservative driver are the minimum of the three types, while the corresponding statistics of the radical driver is the maximum of the three, and the general driver is in the middle, which verifies the rationality of this clustering result.

Key words: Data processing; Feature selection; Driving style clustering; NGSIM database