Time-series projecting road traffic fatalities in Australia: Insights for targeted safety interventions

Ali Soltani, Saeid Afshari, Mohammad Amin Amiri

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
27 Downloads (Pure)

Abstract

Despite substantial progress in road safety, road traffic fatalities (RTFs) continue to be a persistent issue in Australia. This study aims to forecast RTFs trends up to 2050 by analyzing factors such as geographic location, age, gender, speed limits, and time of occurrence. Utilizing historical data from 1989 to 2024, fatalities were categorized by road user type, demographics, and day of the week. The Facebook Prophet time series model, incorporating categorical variables like region, age, and speed limits, was employed to predict future trends. The analysis reveals significant regional disparities in fatality reduction rates, with some areas lagging others. Gender-specific forecasts indicate a sharper decline in male fatalities compared to females, while projections highlight persistent risks for older drivers. Additionally, highways with higher speed limits are expected to see a substantial decrease in fatalities. These insights emphasize the need for targeted interventions in areas with slower reductions and high-risk demographic groups, aiding policymakers in refining safety measures, enforcing speed limits, and enhancing public awareness campaigns.

Original languageEnglish
Article number112166
Number of pages17
JournalInjury
Volume56
Issue number3
DOIs
Publication statusPublished - Mar 2025

Keywords

  • Australia
  • Fatalities
  • Machine learning
  • Road user
  • Time series
  • Traffic safety
  • Zero-fatality vision

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