基于车辆行驶数据的驾驶风格识别

Driving Style Recognition Based on Vehicle Driving Data

车辆驾驶员驾驶风格对于汽车的燃油经济性和行驶安全性有重要的影响。文章就基于车辆行驶数据在驾驶风格识别方面的研究进行综述,首先介绍了驾驶员驾驶风格识别的基本流程,接着论述不同学者在驾驶风格识别方面使用的算法模型,包括支持向量机(SVM)算法、反向传播(BP)神经网络算法、随机森林模型算法,然后基于实际车辆行驶数据,利用不同驾驶风格识别模型对其进行实现分析,最后对驾驶员驾驶风格识别的研究工作进行了展望。

Driver's driving style is an important impact on fuel economy and driving safety.This paper summarizes the research on driving style recognition based on vehicle driving data.Firstly,it introduces the basic process of driver's driving style recognition,and then discusses the algorithm models used by different scholars in driving style recognition,including support vector machine(SVM)algorithm,back propagation(BP)neural network algorithm and random forest model algorithm.Then,based on the actual vehicle driving data,different driving style recognition models are used to realize the analysis,and finally the research work of driver driving style recognition is prospected.