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

• Main Authors: Yongfeng Ma, Xin Gu, Ya’nan Yu, Aemal J. Khattakc, Shuyan Chen, Kun Tang
• Format: Article
• Language: English
• Published: MDPI AG 2021-01-01
• Series: Sustainability
• Subjects: aggressive driving behavior; perceptual bias; penalty points; Gaussian mixture model; binary logistic model
• Online Access: https://www.mdpi.com/2071-1050/13/2/766

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.