Institutional Repository of Key Laboratory of Behavioral Science, CAS
Identifying Big Five Personality Traits through Controller Area Network Bus Data | |
Yameng Wang1,2; Nan Zhao1; Xiaoqian Liu1; Sinan Karaburun3; Mario Chen4; Tingshao Zhu1 | |
第一作者 | Yameng Wang |
通讯作者邮箱 | tszhu@psych.ac.cn |
心理所单位排序 | 1 |
摘要 | 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. |
2020 | |
语种 | 英语 |
DOI | 10.1155/2020/8866876 |
发表期刊 | Journal of Advanced Transportation |
ISSN | 0197-6729 |
卷号 | 2020页码:10 |
收录类别 | SCI ; EI |
资助项目 | BMW China Research Project[20170321] ; National Natural Science Foundation of China[31700984] ; Youth Innovation Promotion Association CAS |
出版者 | WILEY-HINDAWI |
WOS关键词 | DRIVING BEHAVIORS ; ATTITUDES ; DRIVERS |
WOS研究方向 | Engineering ; Transportation |
WOS类目 | Engineering, Civil ; Transportation Science & Technology |
WOS记录号 | WOS:000591575200001 |
WOS分区 | Q2 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.psych.ac.cn/handle/311026/32835 |
专题 | 中国科学院行为科学重点实验室 |
通讯作者 | Tingshao Zhu |
作者单位 | 1.CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China 2.School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China 3.BMW China Automotive Trading Ltd., Beijing, China 4.BMW China Services Ltd., Beijing, China |
第一作者单位 | 中国科学院行为科学重点实验室 |
通讯作者单位 | 中国科学院行为科学重点实验室 |
推荐引用方式 GB/T 7714 | Yameng Wang,Nan Zhao,Xiaoqian Liu,et al. Identifying Big Five Personality Traits through Controller Area Network Bus Data[J]. Journal of Advanced Transportation,2020,2020:10. |
APA | Yameng Wang,Nan Zhao,Xiaoqian Liu,Sinan Karaburun,Mario Chen,&Tingshao Zhu.(2020).Identifying Big Five Personality Traits through Controller Area Network Bus Data.Journal of Advanced Transportation,2020,10. |
MLA | Yameng Wang,et al."Identifying Big Five Personality Traits through Controller Area Network Bus Data".Journal of Advanced Transportation 2020(2020):10. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Identifying Big Five(2338KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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