Dangerous Driving Behavior Recognition and Prevention Using an Autoregressive Time-Series Model

Dangerous Driving Behavior Recognition and Prevention Using an Autoregressive Time-Series

Model

Hongxin Chen;Shuo Feng;Xin Pei;Zuo Zhang;Danya Yao

【期刊名称】《清华大学学报（英文版）》 【年(卷),期】2017(022)006

【摘要】Time headway is an important index used in characterizing dangerous driving behaviors.This research focuses on the decreasing tendency of time headway and investigates its association with crash occurrence.An autoregressive (AR) time-series model is improved and adopted to describe the dynamic variations of average daily time headway.Based on the model,a simple approach for dangerous driving behavior recognition is proposed with the aim of significantly decreasing headway.The effectivity of the proposed approach is validated by means of empirical data collected from a medium-sized city in northern China.Finally,a practical early-warning strategy focused on both the remaining life and low headway is proposed to remind drivers to pay attention to their driving behaviors and the possible occurrence of crash-related risks. 【总页数】9页(682-690) 【关键词】

【作者】Hongxin Chen;Shuo Feng;Xin Pei;Zuo Zhang;Danya Yao

【作者单位】Department of Automation,Tsinghua University,Beijing 100084,China;Department of Automation,Tsinghua University,Beijing 100084,China;Department of Automation,Tsinghua University,Beijing 100084,China;Department of Automation,Tsinghua University,Beijing 100084,China;Department of Automation,Tsinghua University,Beijing 100084,China 【正文语种】英文 【中图分类】 【文献来源】

https://www.zhangqiaokeyan.com/academic-journal-cn_tsinghua-science-technology_thesis/0201250458805.html 【相关文献】

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