Driver Modeling Based on Vehicular Sensing Data
In the past few years,the automotive electronics and sensing technologies have developed rapidly.Today,the status of most of the sub-systems in a running vehicle can be accurately monitored.This process produces a huge amount of data.Extracting the potential value of such data,to for instance support developing advanced vehicle diagnosis and active safety applications,has attracted tremendous attentions in both academia and industry.Considering that the sensing data,if sampled with sufficiently high frequency,can accurately represent how a driver maneuvers a vehicle,this paper investigates using the vehicular sensing data to exploit drivers behaviors in different traffic scenarios.We apply machine learning techniques to construct driving behavior models,and discuss their applications in driver identification.
driving behavior models vehicular sensing data machine learning driver identification
Zhuowen Wang Fuqiang Liu Xinhong Wang Yuyan Du
School of Electronics and Information Engineering,Tongji University,4800 Caoan Highway,Jiading,Shanghai
国际会议
深圳
英文
137-141
2018-01-21（万方平台首次上网日期，不代表论文的发表时间）