A correlated random parameters approach to investigate large truck rollover crashes on mountainous interstates

Abstract

Rollover risk on mountainous interstates is a major concern for transportation agencies due to the combined mixed effects of adverse weather conditions and complex topography. Such crashes incur hazardous consequences on road users' lives. Therefore, a correlated random parameters logit modeling framework was employed to investigate the influences of crash precursors on rollover risk to identify effective safety countermeasures. This approach was selected to account for both the crash contributing factors' unobserved heterogeneity effects and the correlations among those effects. The data, used in this study, were those of single-truck crashes on Wyoming's interstate curved sections. The traditional logit and uncorrelated random parameters, or mixed, logit models were attempted as well. With that, the analysis results indicated that the fit of the correlated random parameters logit model was superior to those of the others. It also revealed insights regarding correlations among random parameters that were obscure in the other models. According to its results, on average, veering off the road, overcorrections and severe winds raised the risk of single-truck rollover crashes. On the other hand, median barriers, roadside guardrails, tight horizontal curves, icy road surfaces, wet surfaces and surfaces covered by loose material, in general, reduced the likelihood of rollovers. Correlations, such as those between severe winds and icy surfaces and those between roadside guardrails and icy surfaces, were inferred as well. This study's results will assist transportation officials in efficiently identifying appropriate countermeasures to mitigate the impact of truck rollovers particularly during adverse weather conditions.

Keywords: Adverse weather; Correlated random parameters; Mountainous terrain; Rollover crashes; Unobserved heterogeneity effects.