Abstract
Introduction: As fatalities, injuries, and economic losses from road accidents are a major concern for governments and their citizens, Australia, like other countries, has designed and implemented a wide range of strategies to reduce the rate of road accidents. Methods: As part of the strategy design process, data on crash deaths were collected and then analyzed to develop more effective strategies. The data of crash deaths in Australia during the years 1965 to 2018 were analyzed based on gender, causes of crash deaths, and type of road users, and then the results were compared with global averages, then a prediction model was developed to forecast the future annual crash fatalities. Results: The results indicate that, based on gender, the rate of male road fatalities in Australia was significantly higher than that of female road fatalities. Whereas based on the cause of death, the first cause of death was over speeding. Based on the type of road users, the drivers and passengers of 4-wheel vehicles had the highest rate of fatalities. Conclusion: The prediction model was developed based on Autoregressive Integrated Moving Average (ARIMA) methodology, and annual road fatalities in Australia for the next five years 2019-2022 have been forecast using this model.
Highlights
As fatalities, injuries, and economic losses from road accidents are a major concern for governments and their citizens, Australia, like other countries, has designed and implemented a wide range of strategies to reduce the rate of road accidents
This study aims to: Analyze crash fatalities data in Australia according to several factors, including gender, age, causes of crash deaths, and type of road users; compare the results with global averages, Europe (Denmark as a representative European country), and United States’ results
The results showed that the Autoregressive Integrated Moving Average (ARIMA) (2, 2, 2) model had the lowest values for Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE); the stationary R-squared and R-squared were the highest for this model
Summary
As part of the strategy design process, data on crash deaths were collected and analyzed to develop more effective strategies. The data of crash deaths in Australia during the years 1965 to 2018 were analyzed based on gender, causes of crash deaths, and type of road users, and the results were compared with global averages, a prediction model was developed to forecast the future annual crash fatalities
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