@article{ref1,
title="Prediction of road accidents trend in Tanzania using ARIMA model: the road safety implication by 2021-2030",
journal="International journal of traffic and transportation engineering (Rosemead, Calif.)",
year="2022",
author="Ndume, Vitalis Agati and Rutalebwa, Edwin C. and Runyoro, Angela-Aida K.",
volume="11",
number="1",
pages="1-7",
abstract="The purpose of this study is to predict the road accidents and justify whether Tanzania can reach the target of the global Second Decade of Action for Road Safety 2021-2030 calls. The study applied time-series modeling to determine and predict road traffic accidents patterns in the selected regions in Tanzania. Regions selection was based on those with the high rate of accidents. The secondary data obtained from Tanzania Road Safety Squad were used in analysis. Data were then loaded on R- packages for analysis. A time-series analysis using ARIMA Model was conducted to characterize and predict the frequency of road traffic accidents that lead to injury. The traffic accidents were categorized into four separate groups; these are accidents related to the car driver's behavior, motorcyclists, bicyclists and pedestrian. ARIMA model was used to model time series in each group from 2013 to 2021 and to predict the accidents up to 10 years later (2030). The analysis was carried out using R-4.1.1 statistical software package. The main contribution of our study in the field of road safety is estimation of number of death that can occur due to road accidents by 2030 which is estimated to decrease by 97%.<p /> <p>Language: en</p>",
language="en",
issn="2325-0062",
doi="10.5923/j.ijtte.20221101.01",
url="http://dx.doi.org/10.5923/j.ijtte.20221101.01"
}