Investigating Contributing Factors on Aggressive Driving Based on a Structural Equation Model

• Published in: Journal of advanced transportation 2022-03, Vol.2022, p.1-14
• Main Authors: Xu, Wenxiang, Wang, Junhua, Fu, Ting, Sobhani, Anae, Nabavi Niaki, Matin
• Format: Article
• Language: English
• Subjects: Acceleration; Advanced driver assistance systems; Age; Aggressive behavior; Aggressiveness; Behavior; Case studies; Control systems; Driver behavior; Driving ability; Factor analysis; Global positioning systems; GPS; Investigations; Law enforcement; Literature reviews; Mathematical models; Multivariate statistical analysis; Roads & highways; Safety; Safety critical; Safety factors; Speed limits; Statistical analysis; Structural equation modeling; Support vector machines; Traffic accidents & safety; Traffic control; Traffic flow; Traffic safety; Transportation; Vehicle safety; Weather
• ISSN: 0197-6729; 2042-3195
• DOI: 10.1155/2022/1783392

Tailored countermeasures that may significantly improve road traffic safety can be proposed and implemented if the relationship between various associated factors and aggressive driving is well understood. However, this relationship remains unknown, as driving behavior is complex, and the interrelationships among variables are not easy to identify. Considering this situation, this paper constructed a model based on a structural equation model (SEM) and factor analysis (FA), which is a multivariate statistical analysis technique used to analyze structural relationships. The model is applied in a case study using data from the Shanghai Naturalistic Driving Study. In the case study, 16 variables were grouped into five latent factors in the SEM, and the model fits the data well. Compared with other variables, the results show that age had the most significant positive impact on aggressive driving behavior (older drivers exhibited high aggressive driving frequency). Adverse weather negatively impacted driver behavior (lower speed and high longitude acceleration), which in turn negatively affected aggressive driving behavior. In addition, the results show that driver factors (such as age and sex) were the main factors influencing vehicle use (such as hard acceleration), and the environment was the main factor determining risky scenarios, where safety-critical situations increase. This paper provides a reference for defining and determining aggressive driving and a model for exploring the relationship between driving safety factors and aggressive driving, which can be used in real-world applications for improving driving safety with applications in advanced driver-assistance (ADAS) and traffic enforcement safety control systems.