Abstract
The primary objective of this article is to investigate how survival modelling can be used in traffic accident analysis to explain driver accident risk factors. Accident records of 398 drivers from 2007 to 2009 were obtained from Motor Traffic and Transport Department (MTTD), Ghana Police Service, Northern region. Cox proportional regression model was employed for the analysis using the SAS package. The conclusion was that Survival modelling promises to be a useful tool for road safety analysis and the most significant variables to the risks of accident were driver characteristics (age, gender, experience), their behaviour in traffic (speed, use of alcohol, use of safety belt), the nature of exposure (annual kilometreage, road surface condition) and vehicle characteristics (vehicle age, weight, tyres condition). Implementation of the findings of this study will enable policy makers put up better measures to reduce accident occurrence in the region in particular and the country as a whole. Key words: Cox proportional model, accident risks, annual vehicle kilometreage, survival modelling, SAS package.
Highlights
Road transport is a predominant means of commuting in Ghana accounting for high passenger travels and carting of goods in the country
The primary objective of this article is to investigate how survival modelling can be used in traffic accident analysis to explain driver accident risk factors
The conclusion was that Survival modelling promises to be a useful tool for road safety analysis and the most significant variables to the risks of accident were driver characteristics, their behaviour in traffic, the nature of exposure and vehicle characteristics
Summary
Road transport is a predominant means of commuting in Ghana accounting for high passenger travels and carting of goods in the country. Drivers are faced with risky situations and potential accidents every time they are on the road. Accidents happen when road users cannot adapt their actions to the varying demands of the traffic environment. The risk of accident can be lowered by improving road users’ performance in traffic or by reducing system demands on road users (Elvik, 1996). Many factors affect driver accident involvement as found in literature. To prevent accident, one must know which of the numerous traffic risk factors have a real strong influence on the number and probability of accidents.
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