Citation

Wang F, Zhang J, Wang S, Li S, Hou W. Int. J. Environ. Res. Public Health 2020; 17(2): e17020430.

Affiliation

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

Copyright

(Copyright © 2020, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph17020430

PMID

31936406

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.

Language: en

Keywords

K-means clustering algorithm; driving behavior; dynamic personality; personality baseline; simulated scenarios