Identification of Contributing Factors for Driver’s Perceptual Bias of Aggressive Driving in China

Yongfeng Ma, Xin Gu, Ya’nan Yu, Aemal J. Khattakc, Shuyan Chen and Kun Tang
Additional contact information
Yongfeng Ma: Jiangsu Key Laboratory of Urban ITS, Jiangsu Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
Xin Gu: Beijing Key Laboratory of Traffic Engineering, The College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
Ya’nan Yu: Jiangsu Key Laboratory of Urban ITS, Jiangsu Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
Aemal J. Khattakc: 330E Whittier Research Center, Nebraska Transportation Center, University of Nebraska-Lincoln, Lincoln, NE 68583-0851, USA
Shuyan Chen: Jiangsu Key Laboratory of Urban ITS, Jiangsu Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
Kun Tang: School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China

Sustainability, 2021, vol. 13, issue 2, 1-18

Abstract: Aggressive driving is common across the world. While most aggressive driving is conscious, some aggressive driving behavior may be unconscious on part of motor vehicle drivers. Perceptual bias of aggressive driving behavior is one of the main causes of traffic accidents. This paper focuses on identifying impact factors related to aggressive driving perceptual bias. Questionnaire data from 690 drivers, collected from a drivers’ retraining course administered by the Traffic Management Bureau in Nanjing, China, were used to collect drivers’ socioeconomic characteristics, personality traits, and external environment data. Actual penalty points were considered as an objective indicator and Gaussian mixture model (GMM) was used to cluster an objective indicator into different levels. The driving anger expression (DAX) was used to measure drivers’ self-assessment of aggressive driving behavior and then to identify perceptual biases. Then a binary logistic model was estimated to explore the influence of different factors on drivers’ perceptual bias of aggressive driving behavior. Results showed that bus drivers were less likely to have perceptual bias of aggressive driving behavior. Truck drivers, drivers with an extraversion characteristic, and drivers who have dissatisfaction with road infrastructure and actual work were likely to have a perceptual bias. The findings are potentially beneficial for proposing targeted countermeasures to identify dangerous drivers and improve drivers’ safety awareness.

Keywords: aggressive driving behavior; perceptual bias; penalty points; Gaussian mixture model; binary logistic model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/2/766/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/2/766/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:2:p:766-:d:480446

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().