Time series based road traffic accidents forecasting via SARIMA and Facebook Prophet model with potential changepoints
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
Heliyon
Abstract
Road traffic accident (RTA) is a critical global public health concern, particularly in developing
countries. Analyzing past fatalities and predicting future trends is vital for the development
of road safety policies and regulations. The main objective of this study is to assess the
effectiveness of univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) and
Facebook (FB) Prophet models, with potential change points, in handling time-series road
accident data involving seasonal patterns in contrast to other statistical methods employed by
key governmental agencies such as Ghana’s Motor Transport and Traffic Unit (MTTU). The
aforementioned models underwent training with monthly RTA data spanning from 2013 to
2018. Their predictive accuracies were then evaluated using the test set, comprising monthly
RTA data from 2019. The study employed the Box-Jenkins method on the training set, yielding
the development of various tentative time series models to effectively capture the patterns in
the monthly RTA data. 𝑆𝐴𝑅𝐼𝑀𝐴 (0, 1, 1) × (1, 0, 0)12 was found to be the suitable model for
forecasting RTAs with a log-likelihood value of −266.28, AIC value of 538.56, AICc value of
538.92, BIC value of 545.35. The findings disclosed that the 𝑆𝐴𝑅𝐼𝑀𝐴 (0, 1, 1) × (1, 0, 0)12 model
developed outperforms FB-Prophet with a forecast accuracy of 93.1025% as clearly depicted by
the model’s MAPE of 6.8975% and a Theil U1 statistic of 0.0376 compared to the FB-Prophet
model’s respective forecasted accuracy and Theil U1 statistic of 84.3569% and 0.1071. A Ljung Box test on the residuals of the estimated 𝑆𝐴𝑅𝐼𝑀𝐴 (0, 1, 1) × (1, 0, 0)12 model revealed that
they are independent and free from auto/serial correlation. A Box-Pierce test for larger lags also
revealed that the proposed model is adequate for forecasting. Due to the high forecast accuracy
of the proposed SARIMA model, the study recommends the use of the proposed SARIMA model
in the analysis of road traffic accidents in Ghana
Description
Research Article
Keywords
Road traffic accident, SARIMA, Facebook Prophet, Potential changepoints, Ghana