Published Paper Details:

Road accidents were always a calamity with a continually growing pattern. According to the Indian road safety campaign, a road accident happens every minute in India, more than 17 people die in road accidents every hour. There are several kinds of automotive incidents, including rear-end, head-on, and rollover collisions. State-recorded police reports, commonly termed as FIRs, are records that contain information regarding accidents. The people may report the occurrence themselves or the state police may record it. The frequency patterns of car crashes are estimated using Apriori and Nave Bayesian approaches in this paper. This pattern will aid the government or non-governmental organisations in improving road safety and taking prevention action in high density areas. At this era, street mobility security is one of the most severe social issues in the world. For every death as a result, there are expected to be approximately four handicap injuries, like damage to the brain or neurological line, 10 genuine wounds, and 60 minor injuries. The rate of crashes occurring on a daily is also growing at an alarming rate owing to the exponentially growing number of automobiles on the road. With the rising traffic accidents and death these days, the transportation department's ability to predict the accident rate over a duration of time is critical for making scientific decisions. In this case, it would be beneficial to investigate the causes of road accidents such that we can create methods to reduce them. Several stakeholders, but are not limited to government civil works departments, contractors, or other automobile industries, can gain from the results of this study in better designing highways and automobiles depending on the values predicted.