基于驾驶事件的驾驶风格分类与识别方法研究OA北大核心CSTPCD

Aiming at the problems that,based on data statistical characteristics,the classification and recognition method of driving style was easy to ignore the diversity of driving style during driv-ing,a classification and recognition method of driving style was proposed based on driving events,spectral clustering and random forest.Experiments were designed to collect driving data,and the data were preprocessed to extract turning events and braking events.After standardization and dimension-ality reduction,the spectral clustering algorithm was used to cluster the driving style of turning events and braking events respectively.The entropy weight method was used to obtain the driving style weights of each driver,and the accuracy of five machine learning algorithms was compared for driving style recognition.Results show that the accuracy of driving style recognition is as 92.73％based on random forest,which significantly improves the accuracy of driving style recognition.