Forecasting Road Traffic Accidents in the Socioeconomic Context

• Main Authors: Alba, Ervin Raphael R., Chua, Trevor Jalen O., Hong, Johannes Nathan C.
• Format: text
• Published: Animo Repository 2021
• Subjects: road traffic accidents, accident modeling, road safety, ARIMA, socioeconomic impact
• Online Access: https://animorepository.dlsu.edu.ph/conf_shsrescon/2021/paper_spl/1; https://animorepository.dlsu.edu.ph/context/conf_shsrescon/article/1703/viewcontent/Alba_et_al.pdf
• Institution: De La Salle University

Road traffic accidents not only take lives, but they also have a vast impact on the economy of the nation. This study aims to provide the appropriate agencies with statistical models of road traffic accidents and the most prevalent causes of motorcycle accidents. To achieve that, the researchers applied certain statistical procedures such as the Moving Average, Weighted Moving Average, Exponential Weighted Moving Average, Chi Square Test of Multiple Proportions, ARIMA Modelling, and Measures of Forecasting Accuracy. These were conducted through softwares like Microsoft Excel and SAS. The researchers identified the most accurate model to be the 6-month Exponential Weighted Moving Average and used it for forecasting. The forecast showed that by the end of 2021, road accidents would have increased from the end of 2019. However, the researchers are aware that the forecast may be inaccurate as more people are impelled to stay at home with the ongoing pandemic; therefore, road accidents have lessened. Despite the reduced economic impact due to road accidents, the Asian Development Bank estimates that the pandemic will deter the GDP growth of the nation by 10%. Furthermore, with the data available, the researchers identified human error to be the prevalent cause of road traffic accidents. However, no known causation factor “No Accident Factor” comprised 99% of the data, thus the researchers highly recommend the Philippine National Police and Metropolitan Manila Development Authority to thoroughly investigate road traffic accidents to identify their cause in order for engineers and road safety practitioners to resolve them.