An investigation of relationships between aberrant driving behavior and crash risk among long-haul truck drivers traveling across India: A Structural Equation Modeling approach

Introduction

Road Traffic Crashes (RTC) are showing an increasing trend around the world. Empirical evidence suggests that the majority of the crashes are attributed to unsafe or dangerous driving behaviors among drivers. However, little is known about the crash risk among professional drivers such as Long-Haul Truck Drivers (LHTDs) considering aberrant driving behaviors in developing countries like India. Objectives: This study aims to investigate the direct effects of characteristics of LHTDs including socio-demographic, work and vehicle, health-related lifestyle on crash risk. This study also attempts to investigate the indirect impacts of socio-demographic characteristics on crash involvement among LHTDs mediated through aberrant driving behaviors.

Methods

Using cross sectional study design, face-to-face interviews were conducted among LHTDs in Salem city, Tamil Nadu, India. A Driver Behavior Questionnaire (DBQ) consisting of 23 items was utilized to measure aberrant driving behaviors among LHTDs and information related to background variables was also collected. A total of 756 valid samples were used for analysis purpose. Exploratory factor analysis confirmed a four-factor solution including errors, lapses, ordinary, and aggressive violations and the identified structure was validated using confirmatory factor analysis. The deployment of Structural Equation Model (SEM) enabled identification of interrelationships among identified latent and observed variables. Results: The developed SEM model showed that all the identified four latent constructs were positively associated with crash involvement among LHTDs. The results further revealed that age and marital status were found to exhibit an indirect impact on crash involvement in addition to direct effects.

Conclusion

The findings from this study could serve road safety authorities and Indian trucking industries to target risky driving behaviors in order to develop engineering and interventional countermeasures.