A Study on Correlation of Traffic Accident Tendency with Driver Characters Using In-Depth Traffic Accident Data
Joint Authors
Wu, Hequan
Hu, Lin
Bao, Xingqian
Wu, Wenguang
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-02
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Traffic accidents are often related to the driver’s driving behavior, which is mainly decided by his or her characters.
In order to explore the correlation of traffic accident risk with driver characters, the age, driving experience, and driving style were statistically analyzed based on the China In-Depth Accident Study (CIDAS) database.
Taking the number of casualties in the accident as evaluation indicators, the grey cluster analysis was used to classify the drivers into four accident risk ranks: low, medium to low, medium to high, and high.
The results show that drivers aged 18–30 years are more likely to induce accidents; drivers with 6–10 years of driving experience have the highest risk to accidents, followed by drivers with 4-5 years of driving experience; and the driving style is also highly correlated with accident risk tendency.
American Psychological Association (APA)
Hu, Lin& Bao, Xingqian& Wu, Hequan& Wu, Wenguang. 2020. A Study on Correlation of Traffic Accident Tendency with Driver Characters Using In-Depth Traffic Accident Data. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1181063
Modern Language Association (MLA)
Hu, Lin…[et al.]. A Study on Correlation of Traffic Accident Tendency with Driver Characters Using In-Depth Traffic Accident Data. Journal of Advanced Transportation No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1181063
American Medical Association (AMA)
Hu, Lin& Bao, Xingqian& Wu, Hequan& Wu, Wenguang. A Study on Correlation of Traffic Accident Tendency with Driver Characters Using In-Depth Traffic Accident Data. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1181063
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181063