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Analysis of Driving Behavior Based on Dynamic Changes of Personality States

Author

Listed:
  • Fanyu Wang

    (College of Transportation, Shandong University of Science and Technology, Huangdao District, Qingdao 266590, China)

  • Junyou Zhang

    (College of Transportation, Shandong University of Science and Technology, Huangdao District, Qingdao 266590, China)

  • Shufeng Wang

    (College of Transportation, Shandong University of Science and Technology, Huangdao District, Qingdao 266590, China)

  • Sixian Li

    (College of Transportation, Shandong University of Science and Technology, Huangdao District, Qingdao 266590, China)

  • Wenlan Hou

    (College of Foreign Language, Shandong University of Science and Technology, Huangdao District, Qingdao 266590, China)

Abstract

This study investigated the relationship between personality states and driving behavior from a dynamic perspective. A personality baseline was introduced to reflect the driver’s trait level and can be used as a basic reference for the dynamic change of personality states. Three kinds of simulated scenarios triggered by pedestrian crossing the street were established using a virtual reality driving simulator. Fifty licensed drivers completed the driving experiments and filled in the Neuroticism Extraversion Openness Five-Factor Inventory (NEO-FFI) questionnaire to measure the drivers’ personality baselines. Key indicators were quantified to characterize the five types of personality states by K-means clustering algorithm. The results indicated that the high-risk situation had a greater impact on the drivers, especially for drivers with openness and extroversion. Furthermore, for the drivers of extroverted personality, the fluctuation of personality states in the high-risk scenario was more pronounced. This paper put forward a novel idea for the analysis of driving behavior, and the research results provide a personalized personality database for the selection of different driving modes.

Suggested Citation

  • Fanyu Wang & Junyou Zhang & Shufeng Wang & Sixian Li & Wenlan Hou, 2020. "Analysis of Driving Behavior Based on Dynamic Changes of Personality States," IJERPH, MDPI, vol. 17(2), pages 1-17, January.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:2:p:430-:d:306590
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    References listed on IDEAS

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    Cited by:

    1. Ke Wang & Qingwen Xue & Jian John Lu, 2021. "Risky Driver Recognition with Class Imbalance Data and Automated Machine Learning Framework," IJERPH, MDPI, vol. 18(14), pages 1-18, July.
    2. Pereira, Vijay & Bamel, Umesh & Paul, Happy & Varma, Arup, 2022. "Personality and safety behavior: An analysis of worldwide research on road and traffic safety leading to organizational and policy implications," Journal of Business Research, Elsevier, vol. 151(C), pages 185-196.

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