Prediction of the cause of accident and accident prone location on roads using data mining techniques

Abstract

Road Accident is a specific instance of traumatic events that constitute major loss. Data mining tools and techniques are used to predict the likelihood of accident and accident prone locations. This paper sheds light on predicting the probability of accidents on roads with special emphasis on STATE HIGHWAYS (SHs) and ORDINARY DISTRICT ROADS (ODRs) by estimating the severity of accidents based on the type of accident, type of spot using the R tool. Pointing out the traffic collision data of roads the frequency of traffic collision of roads is analyzed using correlation analysis and exploratory visualization techniques. Finally, methodology has been proposed to analyze road traffic accidents. Using this methodology, improvement can be promised at the level and extent of road traffic safety management effectively and efficiently. The present study modeled accident and incident data gathered from the traffic data and data related to construction sectors.