Key factors affecting motorcycle-barrier crash severity: an innovative cluster-regression technique

Reuben Tamakloe, Subasish Das, Emmanuel Kofi Adanu, Dongjoo Park

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Highway motorcycle-barrier crashes are uncommon but are associated with severe ramifications. Little has been done to understand the factors related to these crashes, making it difficult to establish appropriate mitigation policies. This study identifies homogeneous groups of motorcycle-barrier crashes on highways and investigates cluster-specific key factor associations and the determinants of injury severity. Cluster Correspondence Analysis was employed to discover latent clusters and cluster-specific key factor associations using motorcycle-barrier crashes from Massachusetts. Further, an ordered probit regression technique was employed to investigate the effect of factors on injury severity outcomes at the cluster level. Three highway access control type-related clusters were identified. While seniors, collectors, intersections/roundabouts, daylight, and summer were associated with no/partial access-controlled segment crashes, interstates, ramps, medians, dark-lighted roads, and winter correlated with full access-controlled segment crashes. Factors influencing fatalities differed for each cluster. From the insightful findings, targeted countermeasures geared at improving motorcycle safety are suggested.

Original languageEnglish
JournalTransportmetrica A: Transport Science
DOIs
StateAccepted/In press - 2023

Keywords

  • Motorcycle
  • access control
  • cluster correspondence analysis
  • injury severity
  • ordered probit regression

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