Abstract
Road accidents in Nigeria have always been in the increase. Efforts made by Federal Road Safety Commission (FRSC) in tackling the menace have not yielded much result. This paper aims to find a suitable time series model to forecast the future characteristics of the road accident data on Oyo-Ibadan express road. The data used for this paper was monthly data collected for a period of Eleven years between 2004-2014. In achieving this, the additive model approach was adopted in the analysis. It includes the estimation of trend, seasonal variation and random variation using moving average method. Autoregressive Moving average model were also fitted to the data and the best order was choosing using Akaike Information Criteria (AIC). The order = c (1, 1, 2), seasonal = c (1, 1, 2)) gives the best description of the data with minimum (AIC). A forecast based on the model obtained was made by the use of m-step predictor. The time plot plotted shows that the graphs maintain a constant movement from 2004-2008 but increases abnormally in 2010 and later drop again maintaining appreciable downward movement as the year progresses. Judging from the result, accidents and deaths are higher during the festive period months because of the various festivities lined up during this period, which involve much more traveling than usual.
Highlights
Road traffic fatalities are forecast to increase over the ten years from a current level of more than 1.3 million to more than 1.9 million by 2020
3806.15 1.9016 The Fitted Model 0.6414. This shows that the absolute value of Augmented Dickey-Fuller (ADF) (7.3095) and Philip Perron (PP) (144.07) are still greater than all the critical values of 1%, 5% and 10% and p-value is less than all the critical values, with this, can be rejected and this implies that the data is stationary
Model Fitting, Selection and Diagnostics. We considered both the deterministic and stochastic approach
Summary
Road traffic fatalities are forecast to increase over the ten years from a current level of more than 1.3 million to more than 1.9 million by 2020. The world could prevent 5 million deaths and 50 million serious injuries by 2020 by dramatically scaling up investment in road safety, at global, regional and national levels. Each year nearly 1.3 million people die as a result of a road traffic collision, more than 3000 deaths each day and more than half of these people are not travelling in a car. According to John Cohen in his book, causes and prevention of road accidents “says if we had the will, we should find ways, for we cannot assume to the problem of road safety are beyond the wit of man to solve once they are identified. We do not have the will because we are not sufficiently moved by disaster on the road". [1] Define accident as a chance occurrence, which produce unexpected and unpleasant consequences resulting from unforeseen and often a disastrous event
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