A Data Mining Framework to Analyze Road Accident Data Using Map Reduce CCMF and TCAMP Algorithms

Abstract

Accident prediction is an important safety issue to raise alarms before accidents happen. In this paper we formulate relevant questions to anticipate the occurrence of accidents and process the available information using Hadoop. We examine the execution time on Hadoop when compared with other methods, and propose 2 algorithms to use Congestion Control Machine Framework (CCMF) and Traffic Congestion Analyzer using Map Reduce (TCAMP) to effectively analyze the available data and assess road accident reasons and advise authorities to take appropriate actions to increase road safety. We apply information mining to examine recorded road attributes to reduce road accidents specifically in India, and formulate a set of standards that can be utilized by the National Highway Authority of India to improve safety.