• G. NIRANJANA
• Dr. R. VIJAYABHANU

Traffic violations and offences are becoming more and more serious as the traffic volume increasing, which may bring property damage and threaten personal safety. In 2013, approximately 32,000 people died in traffic crashes in the USA. Almost 90 people on average lose their lives every day and more than 250 are injured every hour. Traffic crashes can be reduced by enhancing the Road safety. Traffic data volumes are increasing very fast and huge amount of data are generated, which could not be handled with traditional tools like excel or RDBMS. Big Data analytics tools helps us to gain useful insights to enhance road safety and decrease traffic crashes. In this paper, Hadoop and R will be used to analyse and mine the data. Analyses are done using HIVE and interpolating them using R. After doing analyses, the goal is to predict the accidents from the type of violation and other factors using different regression techniques and also to find the relation/Association between different factors on violations and accidents. The aforementioned analyses will be helpful for the decision makers and practitioners to develop new traffic rules and policies, in order to prevent accidents, and increase roadway safety

Data analytics, R tool, Data mining techniques, Regression techniques.

"Traffic Violation Data Analysis Using R and Hadoop", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.505-513, May-2019, Available :http://www.jetir.org/papers/JETIR1905D74.pdf

"Traffic Violation Data Analysis Using R and Hadoop", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp505-513, May-2019, Available at : http://www.jetir.org/papers/JETIR1905D74.pdf