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Who Has Better Driving Style: Let Data Tell Us

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Intelligent Systems and Applications (IntelliSys 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1037))

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Abstract

Recent researches have put a lot of effort on mining vehicle sensing data, in order to help improve the driving safety. However, due to the lack of continuously collected data, most work assumed that one particular driver would only show or hold one driving style on any trips he/she was going on. In this paper, we analyzed more than 3.5 million GPS data points and about 68,500 driving events obtained from on-board devices installed in cars running in big cities for nine months. Different than other methods, we establish the driving style vector for each driver based on the fact that the same driver performs different behaviors on different trips. We propose a two-step clustering algorithm and obtain four representative driver groups with different driving styles. In addition to “normal”, “aggressive” and “clam”, we also find out an “experienced” driving style that was never mentioned in other existing works.

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Author information

Authors and Affiliations

  1. China Academy of Information and Communications Technology, No.52, Hua Yuan Bei Road, Haidian District, Beijing, China

    Linna Wu

  2. AI Research Institute, Harbin Institute of Technology, HIT Campus of University Town of Shenzhen, Shenzhen, China

    Huan Li

  3. Beijing Bytedance Technology Co., Ltd, Building 4, Zijin Digital Park, Haidian District, Beijing, China

    Hengtian Ding

  4. Broadsense (Shenzhen) Information Technology Co. Ltd, Shenzhen, China

    Lizhuo Zhang

Authors
  1. Linna Wu
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  2. Huan Li
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  3. Hengtian Ding
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  4. Lizhuo Zhang
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Corresponding author

Correspondence to Huan Li .

Editor information

Editors and Affiliations

  1. School of Computing, Computer Science Research Institute, Ulster University, Newtownabbey, UK

    Yaxin Bi

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

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Wu, L., Li, H., Ding, H., Zhang, L. (2020). Who Has Better Driving Style: Let Data Tell Us. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1037. Springer, Cham. https://doi.org/10.1007/978-3-030-29516-5_37

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