Road Accident Prediction Model Using Machine Learning

Abstract

Abstract: Last year, the number of traffic accidents declined to 3.66 lakh,the lowest level in the last 20 years. The strong rules buried in these common item sets frequently reveal the relationship between influencing variables of accidents, which may be exploited to break them and limit the incidence of accidents. The guidelines may also be used to investigate common accident sites, and appropriate security improvements can be implemented to prevent accidents and, as a result, enhance thecity's traffic safety. In general, association rule mining can generate many weak rules; thus, the study first devised a technique for calculating the minimum Support value of training parameters, then proposed a method for extracting strong rules automatically. The experiment results revealed that the strategies provided in the research are successful. As a result, an automatic modelling technique based on association rules was developed to help promote the successful use of association rule mining in intelligent transportation systems.