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A Study on Driving Behavior Intelligence Recognition Based on Discrete Wavelet Transform and Support Vector Machine Algorithm
| 题名： | A Study on Driving Behavior Intelligence Recognition Based on Discrete Wavelet Transform and Support Vector Machine Algorithm |
| 正文语种： | 中文 |
| 作者： | Zhu Xianglei Zhao Shuai Zhang Lu Zhou Bolin Wen Quan Hao Jianye |
| 作者单位： | Automotive Technology & Research Center University |
| 关键词： | driving behavior model machine learning discrete wavelet transform support vector machine model optimization |
| 摘要： | With the rapid development of Artificial Intelligence,big data analysis,smart recognition of driving behaviors becomes the new focus of Intelligence and Connected Vehicles researches.The state-of-the-art research in this direction is to recognize driving scenes to support driving decisions,based on driver's driving data.This study used CATARC collected Controller Area Network(CAN)bus and CARTAC driving scene standard labeled data,implemented discrete wavelet transform(DWT)and support vector machine(SVM)algorithm,constructed a machine learning model with the ability of detecting 16 different driving behaviors.With details of fea-ture selection,filter selection,SVC parameters selection and many others techniques to optimize the model,achieved cross validation accuracy rate around 88%.This method can be applied to vehicles' security warnings and intelligence control,therefore to improve ve-hicle safety performance. |
| 会议日期： | 20171024 |
| 会议举办地点： | 上海 |
| 会议名称： | 第19届亚太汽车工程年会暨2017中国汽车工程学会年会 |
| 出版日期： | 1024-01-20 |
| 母体文献： | 第19届亚太汽车工程年会暨2017中国汽车工程学会年会论文集 |
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