Predicting driving speed from psychological metrics in a virtual reality car driving simulation
Why do some people tend to drive faster than others? Personality characteristics such as the evaluation of risk to oneself or to others, impulsivity, adherence to norms, but also other personal factors such as gender, age, or driving experience all may play a role in determining how fast people drive. Since driving speed is a critical factor underlying accident prevalence, identifying the psychological metrics to predict individual driving speed is an important step that could aid in accident prevention. To investigate this issue, here, the authors used an immersive virtual reality driving simulation to analyze average driving speed. A total of 124 participants first took a comprehensive set of personality and background questionnaires and a behavioral risk-taking measure. In the virtual reality experiment, participants were required to navigate a difficult driving course in a minimally-restricted, non-urban setting in order to provide baseline results for speed selection. Importantly, the authors found that sensation seeking and gender significantly predicted the average driving speed, and that sensation seeking and age were able to predict the maximum driving speed.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/20452322
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Supplemental Notes:
- Copyright © 2022. The Author(s).
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Authors:
- Ju, Uijong
- Williamson, John
- Wallraven, Christian
- Publication Date: 2022
Language
- English
Media Info
- Media Type: Digital/other
- Features: References;
- Pagination: 10044
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Serial:
- Scientific Reports
- Volume: 12
- Issue Number: 1
- Publisher: Nature Publishing Group
- ISSN: 2045-2322
- Serial URL: http://www.nature.com/srep/index.html
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Behavior; Driver performance; Personality; Risk taking; Speed; Virtual reality
- Subject Areas: Highways; Safety and Human Factors;
Filing Info
- Accession Number: 01861144
- Record Type: Publication
- Files: TRIS
- Created Date: Oct 14 2022 8:53AM