Analysing the main and interaction effects of commercial vehicle mix and roadway attributes on crash rates using a Bayesian random-parameter Tobit model

Tiantian Chen, N. N. Sze, Sikai Chen, Samuel Labi, Qiang Zeng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

In previous research, the effects of commercial vehicle proportions (CVP) on overall crash propensity have been found to be significant, but the results have been varied in terms of the effect direction. In addition, the mediating or moderating effects of roadway attributes on the CVP-vs-safety relationships, have not been investigated. In addressing this gap in the literature, this study integrates databases on crashes, traffic, and inventory for Hong Kong road segments spanning 2014–2017. The classes of commercial vehicles considered are public buses, taxi, and light-, medium- and heavy-goods vehicles. Random-parameter Tobit models were estimated using the crash rates. The results suggest that the CVP of each class show credible effects on the crash rates, for the various crash severity levels. The results also suggest that the interaction between CVP and roadway attributes is credible enough to mediate the effect of CVP on crash rates, and the magnitude and direction of such mediation varies across the vehicle classes, crash severity levels, and roadway attribute type in four ways. First, the increasing effect of taxi proportion on slight-injury crash rate is magnified at road segments with high intersection density. Second, the increasing effect of light-goods vehicle proportion on slight-injury crash rate is magnified at road segments with on-street parking. Third, the association between the medium- and heavy-goods vehicle proportion and killed/severe injury (KSI) crash rate, is moderated by the roadway width (number of traffic lanes). Finally, a higher proportion of medium- and heavy-goods vehicles generally contributes to increased KSI crash rate at road segments with high intersection density. Overall, the findings of this research are expected not only to help guide commercial vehicle enforcement strategy, licensing policy, and lane control measures, but also to review existing urban roadway designs to enhance safety.

Original languageEnglish
Article number106089
JournalAccident Analysis and Prevention
Volume154
DOIs
Publication statusPublished - May 2021

Keywords

  • Commercial vehicle
  • Crash rate
  • Mediating effect
  • Random-parameter Tobit model
  • Roadway attribute

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health

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