AUTOMATED REAL-TIME DRIVING BEHAVIOURAL MODELLING ANALYSIS AND REPORTING IN DENSER TRAFFIC USING DATA MINING

摘要

#$%^&*AU2020101738A420200917.pdf#####AUTOMATED REAL-TIME DRIVING BEHAVIOURAL MODELLING ANALYSIS AND REPORTING IN DENSER TRAFFIC USING DATA MINING Abstract For emergency management, traffic safety is an essential component, and to improve the safe transit, the driving risk prediction should be sufficient. In recent days, the roads and transportation capabilities are not evolved effectively according to the expanding number of vehicles and population increase. Road traffic accidents have become the most significant health issue throughout the world. The extension of the present roads has become insufficient. Traffic congestion has become the main issue throughout the entire globe. The issues present due to traffic congestion are noise, pollution, and an increase in traveling time. Traffic prediction had paid attention and became a vital issue in smart cities. The technologies had developed so far as to know the driver behavior analysis. This research addresses the real-time driver behavioral analysis and the denser traffic using data mining technologies. The data mining emulsions are considerably used to establish and forecast the factors amongst the motor vehicle, human, and environmental considerations. The data mining algorithms are used to analyze and predict the driving risk to improve the driver's behavior by analyzing driving behavior data. This research explores the technologies to overwhelm indirect and direct traffic problems on civilization and the world. The classifiers are used to predict whether the traffic rule is violated. The classifier techniques are Decision Tree (Random Forest), SVM, and Neural network is used to know the driver behavior, prediction, and analysis and for prediction of road traffic accidents. 11 P a g eAUTOMATED REAL-TIME DRIVING BEHAVIOURAL MODELLING ANALYSIS AND REPORTING IN DENSER TRAFFIC USING DATA MINING Drawings: Data Set IFeature Engineeririg FaueS co ----------------------------------------------------------------Pre1icionandCasifiratiori USin Daando Forestae1u Figure 1: Framework ofproposedmethodology 1aPaagae