Olga Beatriz Barbosa Mendes, Ana Paula Camargo Larocca, Karla Rodrigues Silva, Ali Pirdavani

Assessing the Performance of Highway Safety Manual (HSM) Predictive Models for Brazilian Multilane Highways

  • Management, Monitoring, Policy and Law
  • Renewable Energy, Sustainability and the Environment
  • Geography, Planning and Development
  • Building and Construction

This paper assesses the performance of Highway Safety Manual (HSM) predictive models when applied to Brazilian highways. The study evaluates five rural multilane highways and calculates calibration factors (Cx) of 2.62 for all types of crashes and 2.35 for Fatal or Injury (FI) crashes. The Goodness of Fit measures show that models for all types of crashes perform better than FI crashes. Additionally, the paper assesses the application of the calibrated prediction model to the atypical year of 2020, in which the COVID-19 pandemic altered traffic patterns worldwide. The HSM method was applied to 2020 using the Cx obtained from the four previous years. Results show that for 2020, the observed counts were about 10% lower than the calibrated predictive model estimate of crash frequency for all types of crashes, while the calibrated prediction of FI crashes was very close to the observed counts. The findings of this study demonstrate the usefulness of HSM predictive models in identifying high-risk areas or situations and improving road safety, contributing to making investment decisions in infrastructure and road safety more sustainable.

Need a simple solution for managing your BibTeX entries? Explore CiteDrive!

  • Web-based, modern reference management
  • Collaborate and share with fellow researchers
  • Integration with Overleaf
  • Comprehensive BibTeX/BibLaTeX support
  • Save articles and websites directly from your browser
  • Search for new articles from a database of tens of millions of references
Try out CiteDrive

More from our Archive