For the issue of driving style identification, this paper proposes a method based on subjective and objective fusion. Firstly, the subjective style scale is developed and transformed into subjective factors. Secondly, a data acquisition system is implemented to gather the natural driving data and the basic behavior scenarios of car following and lane changing are mined. Thirdly, the fusion of subjective and objective identification system of driving style is constructed by extracting the key behavioral characteristics and subjective factors. Based on Principal Component Analysis (PCA) and K-means methods, the sample set is processed and the clustering results are verified. Finally, specific characteristics with physical significance are introduced to identify radical, moderate and conservative driving styles. The results reveal a strong correlation between the distribution of subjective style factors and objective behavioral characteristics, and the fusion method can be used to identify driving style effectively.

Driving style  /  Subjective factor  /  Natural driving data  /  Key behavioral characteristic  /  Fusion of subjective and objective