Predicting driving speed from psychological metrics in a virtual reality car driving simulation

Uijong Ju; John Williamson; Christian Wallraven

doi:10.1038/s41598-022-14409-1

Predicting driving speed from psychological metrics in a virtual reality car driving simulation

Uijong Ju, John Williamson, Christian Wallraven

Department of Brain and Cognitive Engineering

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

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, we 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, we 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.

Original language	English
Article number	10044
Journal	Scientific reports
Volume	12
Issue number	1
DOIs	https://doi.org/10.1038/s41598-022-14409-1
Publication status	Published - 2022 Dec

Bibliographical note

Funding Information:
This study was supported by the National Research Foundation of Korea, Grants NRF-2017M3C7A1041824, 2020R1I1A1A01057915 and by two Institute of Information & Communications Technology Planning & Evaluation (IITP) Grants funded by the Korea government (MSIT) (No. 2017-0-00451; Development of BCI based Brain and Cognitive Computing Technology for Recognizing User’s Intentions using Deep Learning and No. 2019-0-00079; Artificial Intelligence Graduate School Program (Korea University)).

Publisher Copyright:
© 2022, The Author(s).

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abstract = "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, we 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, we 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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Predicting driving speed from psychological metrics in a virtual reality car driving simulation

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