Prediction of Road Accidents Using Correlation Based on Map Reducing

Abstract

In developing countries, the issue of road accidents are a major concern. Increasing road traffic/vehicle occupancy could be the reason behind this. There is an increase in accidents over the years. It is very important to regulate traffic on roads to reduce accidents in accident prone zones. To reduce accidents, it is very important to analyze and identify such road accident prone features. Based on intersection parameters and number of accidents a model was developed by correlation analysis where the data to be analyzed is huge and the prediction model based on correlation analysis should result in vary less time. Map Reducing algorithm is used. The time consuming with different clusters configurations are analyzed.