Analysis of Driving Behavior Based on Dynamic Changes of Personality States

Fanyu Wang, Junyou Zhang, Shufeng Wang, Sixian Li and Wenlan Hou
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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

IJERPH, 2020, vol. 17, issue 2, 1-17

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.

Keywords: dynamic personality; driving behavior; personality baseline; K-means clustering algorithm; simulated scenarios (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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