A Predictive Model for Road Traffic Data Analysis and Visualization to Detect Accident Zones

The usage of vehicles were increased throughout the world, the count of accidents is also increased globally. One of the world's major concerns is recognized to be the number of traffic accidents. In each year, there are increasingly more traffic accidents. Consequently, it has a significant impact on a nation's society, economy, and progress. As accidents occur in various places and at various times, identifying where they are more likely to occur can be complicated. This paper presents a Predictive Model to analyze and visualize road traffic accident zones in Tamil Nadu. The zones are categorized by four different attributes such as low, medium, high and very high. Data analysis is done in order to make a determination. The Real time data are acquired and interpreted using Latent Class Clustering Analysis (LCA). The outcome is represented through Cartogram visualization technique. Accident analysis is done to identify the reason or causes of an accident in attempt to prevent similar instances from occurring repeatedly. As a result, it is simpler to recognize the zones so the data is easier for the users to absorb.