Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/25951
Title: Statistical Analysis of Road Traffic Accidents (RTAs) in Sri Lanka
Authors: Kodithuwakku, D.S.
Peiris, T.S.G.
Keywords: Data Driven Decision Making, Road Traffic Accidents, Severity of Accident
Issue Date: 2021
Publisher: Department of Social Statistics, Faculty of Social Sciences, University of Kelaniya Sri Lanka
Citation: Kodithuwakku D.S.; Peiris T.S.G. (2021), Statistical Analysis of Road Traffic Accidents (RTAs) in Sri Lanka, Volume 03, Issue 01, December 2021, Department of Social Statistics, Faculty of Social Sciences, University of Kelaniya Sri Lanka. 43-56
Abstract: Road Traffic Accidents (RTAs) are one of the most prominent public health problems as it is a leading cause of death by injury and all deaths globally. This study, therefore, intended to determine the significant factors associated with RTAs in Sri Lanka (2005 - 2019) and the impact of those factors using data obtained from the Department of Police, Sri Lanka. The leading causes for RTAs are overtaking, speed driving and diversion and about 80% RTAs are due to these factors. The percentage of RTAs due to alcohol consumption by the driver is around 9%. Both exploratory and confirmatory factors analysis found that the causes for RTAs can be classified into two independent factors namely, (i) negligence of pedestrians & drivers and (ii) lack of attention of the driver. These factors are invariant by the factor extraction method and the type of orthogonal rotation. The condition of road the surface, light condition of the road, the situation of weather, type of vehicle and age of the driver are significantly influential factors in fatal accidents. The highest percentage of fatal accidents have occurred when the road is wet and light condition is poor during night. The inferences derived from this study can be effectively used for policy decisions related to traffic in order to minimize RTAs in Sri Lanka. The study confirmed the benefits of data-driven decision-making for policy decision process.
URI: http://repository.kln.ac.lk/handle/123456789/25951
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