Identifying Big Five Personality Traits through Controller Area Network Bus Data
Joint Authors
Wang, Yameng
Zhao, Nan
Liu, Xiaoqian
Karaburun, Sinan
Chen, Mario
Zhu, Tingshao
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-20
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
As adapting vehicles to drivers’ preferences has become an important focus point in the automotive sector, a more convenient, objective, real-time method for identifying drivers’ personality traits is increasingly important.
Only recently has increased availability of driving signals obtained via controller area network (CAN) bus provided new perspectives for investigating personality differences.
This study proposes a new methodology for identifying drivers’ Big Five personality traits through driving signals, specifically accelerator pedal angle, frontal acceleration, steering wheel angle, lateral acceleration, and speed.
Data were collected from 92 participants who were asked to drive a car along a pre-defined 15 km route.
Using statistical methods and the discrete Fourier transform, some time-frequency features related to driving were extracted to establish models for identifying participants’ Big Five personality traits.
For these five personality trait dimensions, the coefficients of determination of effective predictive models were between 0.19 and 0.74, the root mean squared errors were between 2.47 and 4.23, and the correlations between predicted scores and self-reported questionnaire scores were considered medium to strong (0.56–0.88).
The results showed that personality traits can be revealed through driving signals, and time-frequency features extracted from driving signals are effective in characterizing and identifying Big Five personality traits.
This approach could be of potential value in the development of in-car integration or driver assistance systems and indicates a possible direction for further research on convenient psychometric methods.
American Psychological Association (APA)
Wang, Yameng& Zhao, Nan& Liu, Xiaoqian& Karaburun, Sinan& Chen, Mario& Zhu, Tingshao. 2020. Identifying Big Five Personality Traits through Controller Area Network Bus Data. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1180796
Modern Language Association (MLA)
Wang, Yameng…[et al.]. Identifying Big Five Personality Traits through Controller Area Network Bus Data. Journal of Advanced Transportation No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1180796
American Medical Association (AMA)
Wang, Yameng& Zhao, Nan& Liu, Xiaoqian& Karaburun, Sinan& Chen, Mario& Zhu, Tingshao. Identifying Big Five Personality Traits through Controller Area Network Bus Data. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1180796
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1180796