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author:

Yang, Liu (Yang, Liu.) [1] | Li, Xiaomeng (Li, Xiaomeng.) [2] | Guan, Wei (Guan, Wei.) [3] | Jiang, Shixiong (Jiang, Shixiong.) [4]

Indexed by:

SSCI Scopus

Abstract:

Aggressive driving is a common phenomenon with potential safety hazards. The primary aim of this study is to investigate the relationship among driving skill, driving behavior and driving aggressiveness. A questionnaire survey consisting of three subscales was conducted. Subscale 1 is about driving skill; Subscale 2 is associated with daily driving behavior, while Subscale 3 focuses on aggressive driving behaviors. A total of 239 licensed drivers completed the survey. The five-factor structure was extracted by factor analysis. Then, the correlation analysis method was used to explore the relationship between these factors and drivers' demographic characteristics. K-means cluster was adopted to classify drivers' driving aggressiveness into different levels using behavioral aggressiveness and emotional aggressiveness as the input features. Finally, an ordinal regression model for predicting drivers' driving aggressiveness levels was established by driving skill factor, driving behavior factors and demographic information. The results indicated that more experienced drivers (i.e., drivers with older age, longer driving years or professional drivers) reported better driving behavior and less aggression. Male drivers were more aggressive than female drivers, especially on behavioral aggressiveness. In addition, drivers' profession, driving years, penalty points, errors/lapses and violations can be used to predict their driving aggressiveness levels.

Keyword:

Aggressive driving correlation analysis driving behavior driving skill regression analysis

Community:

  • [ 1 ] [Yang, Liu]Wuhan Univ Technol, Sch Transportat, Wuhan, Peoples R China
  • [ 2 ] [Li, Xiaomeng]Queensland Univ Technol QUT, Inst Hlth & Biomed Innovat IHBI, Ctr Accid Res & Rd Safety Queensland CARRS Q, Kelvin Grove, Qld, Australia
  • [ 3 ] [Guan, Wei]Beijing Jiaotong Univ, Minist Transport, Key Lab Transport Ind Big Data Applicat Technol C, Beijing 100044, Peoples R China
  • [ 4 ] [Jiang, Shixiong]Fuzhou Univ, Coll Math & Comp Sci, Fuzhou, Peoples R China

Reprint 's Address:

  • [Guan, Wei]Beijing Jiaotong Univ, Minist Transport, Key Lab Transport Ind Big Data Applicat Technol C, Beijing 100044, Peoples R China

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Source :

JOURNAL OF TRANSPORTATION SAFETY & SECURITY

ISSN: 1943-9962

Year: 2020

3 . 0

JCR@2020

2 . 4 0 0

JCR@2023

ESI Discipline: SOCIAL SCIENCES, GENERAL;

ESI HC Threshold:91

JCR Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 14

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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