Time Series Analysis of Road Accidents Using Autoregressive Integrated Moving Average (ARIMA) Model

Joel Cheruiyot Chelule ^[5] | Meshack Kipchumba Ngetich | Ayubu Anapapa ^[5] | Herbert Imboga ^[4]

Abstract: The road transport industry in Kenya plays a vital role in the life of the majority of her citizens. Many Kenyans utilize different transport modes to reach their various destinations daily. Nearly 3000 people killed on Kenyan roads per year. The objective of this study was a time series analysis of road accidents trend in Kenya using the Autoregressive Integrated Model (ARIMA) model. This study used time series techniques which can better describe and model the accident data. This is achieved using suitable techniques whose performances are subsequently analyzed. The study utilized accident data between the years 2014-2017 obtained from National Transport Safety Authority. In this research project, the time series with Box Jenkins method applied to 4 years of annual road accident data from 2014 2017 to determine the trend of road traffic accident cases and deaths in Kenya. ARIMA models subsequently fitted for accident cases and deaths.

Keywords: Time Series Analysis, Road Accidents, Autoregressive Integrated Moving Average model ARIMA

Edition: Volume 8 Issue 4, April 2019,

Pages: 1747 - 1755