Analysis of Road Traffic Accidents to Improve Safety and Protection

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Hassan Tariq
Muhammad Munwar Iqbal
Umair Khadam
Muhammad A. Al Ghamdi

Abstract

The objective of this study was that road safety is one of the global issues in the world during travelling. The road accident causes critical effects in the lives of travellers. Hundreds of people are injured, and thousands of people lost lives in road accidents every day. In view of the importance of the problem, identifying the causes of traffic accidents is the main objective in order to reduce traffic accidents.   In this paper, apply data mining algorithms and some statistical analysis of road traffic accident datasets to find patterns and useful information and also compare two-year datasets. Different attributes like weather condition, road surface, light condition and severity of Casualty is investigated. Apriori and ZeroR algorithms are used to build the Classification Model, and discovers association rule. Our empirical results show that the proposed model could classify road traffic accidents within reasonable accuracy and find out association rules which help to improve safety and prevention from accidents. Compare two datasets of different years 2015 and 2016 on the bases of casualty severity. As seen in the experiential setup we find casualty severity from both datasets on bases of different attributes like road surface, weather condition, light condition and type of vehicles. Association rules are applied to find out the best rules which prevent accidents and improve safety.

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Section
COMPUTER SCIENCE