Abstract
AbstractMost road accidents occur due to human errors. The analysis of accidents with respect to different dimensions will help concerned authorities in taking necessary steps to make roads safer. In this paper, we used Apriori algorithm to mine frequent road accident patterns in Dubai during 2017. The features used are the time of accident, accident cause, accident type, age category, road type, day of accident and whether the driver was intoxicated or not. Studies were conducted to identify the accident patterns pertaining to different categories of roads. In E-Route and D-Route roads, less inter-vehicular space resulted in many accidents, whereas in non-major roads, influence of alcohol caused majority of the vehicular collisions. The accidents involving intoxicated drivers were analysed on the basis of time, road type and day of the week. Majority of the intoxication-related accidents were caused by youth. Major chunk of these accidents occured in non-major roads during late night/week hours. Some measures which may help in decreasing accidents are also suggested.KeywordsRoad accidentsApriori algorithmFrequent itemset mining
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