Abstract

Heavy vehicle crashes are a major contributor to road-related fatalities. Representing only 3% of the total number of registered vehicles and 8% of the total vehicle kilometers traveled, heavy vehicles are involved in 18% of fatal and serious injury crashes in Australia. Given the contributing role of vehicle defects in many heavy vehicle crashes, vehicle inspection schemes have been implemented to more effectively manage heavy vehicle safety. However, there is little empirical research about the impact of periodic heavy vehicle inspections on vehicle defects and crash casualties. Hence, this research investigates the efficacy and effectiveness of periodic heavy vehicle inspections by examining their impact on the factors contributing to heavy vehicle crashes as well as the severity of these crashes. Accordingly, a partial least squares path model (PLS-PM) is proposed and evaluated using the data of periodic heavy vehicle inspections and heavy vehicle crashes in Queensland, for the period of 2011–2013. The PLS-PM results are also compared with the results of potential, alternative analysis methods to provide further insights about potential applications of PLS-PM in transportation research. Although the scheme cannot be evaluated completely through the proposed analysis approach, the findings of this study contribute to the causal theory and practice of heavy vehicle inspection protocols, especially in relation to vehicle defects and road safety outcomes.

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