ArticleInternational journal of environmental research and public health2020
Analysis of Driving Behavior Based on Dynamic Changes of Personality States.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 21 citations in OpenAlex.
- A visualization-supported, hierarchical, action-learning model for driving behavior in a V2X environment.PloS one · 2026Article
- Association of personality traits and traffic accident involvement: a multicenter case-control study in Iran.Journal of injury & violence research · 2025Article
- A study on the correlation between MBTI dimensions and driving behavior characteristics.Scientific reports · 2025Article
- Article
- Association between psychological symptoms and illegal driving behaviors in a sample of Chinese private car drivers.Frontiers in psychiatry · 2022Article
- Born to Be a Risky Driver? The Relationship Between Cloninger's Temperament and Character Traits and Risky Driving.Frontiers in psychology · 2022Article
- Risky Driver Recognition with Class Imbalance Data and Automated Machine Learning Framework.International journal of environmental research and public health · 2021Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.