• Sagar Penumala
• Dr. G. Prasanna Lakshmi

Roadway traffic safety is a major concern for Road Transport agencies as well as ordinary citizens. There are a lot of vehicles driving on the roadway every day, and traffic accidents could happen at any time anywhere. Some accident involves a fatality, means people die in that accident. Today, traffic safety is one of the main priorities of governments. In order to give Tips to driving safe and preventing accidents on the road, careful analysis of roadway traffic data is critical to find out variables that are closely related to fatal accidents. Considering the importance of the topic, identifying the factors of road accidents has become the main aim to reduce the damage caused by traffic accidents. This paper proposing a combination of clustering (Eclat) association rule mining(Clara) algorithms to find the rules that are mostly contributing the road accidents. The main aim of the proposed system is to find the most important patterns in road accident data.

Association rule mining, Data mining, Clustering, Clara, Eclat

"ADVANCED TRAFFIC CONGESTION AVOIDANCE ALGORITHMS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.123-126, January-2019, Available :http://www.jetir.org/papers/JETIRT006020.pdf

"ADVANCED TRAFFIC CONGESTION AVOIDANCE ALGORITHMS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp123-126, January-2019, Available at : http://www.jetir.org/papers/JETIRT006020.pdf