We evaluated the overall and class-level performance of the machine learning models based on accuracy and mean squared error scores. Our aim is to resolve the bias that happens in the favor of the majority class as well as performance improvement. We proposed an informative negative data generator using feature weights derived from multinomial logit regression to balance the non-fatal accident data. The trained model provides timely and accurate predictions on accident occurrence and injury severity using real-world traffic accident datasets. This study applied various machine learning models, including neural network, ordinal regression, decision tree, support vector machines, and logistic regression to have a robust prediction model in injury severity. Combining these patterns and the prediction model into an accident prevention system can assist in reducing and preventing traffic accidents.
Traffic data analysis provided insights into significant factors and driver behavioral patterns causing accidents. Therefore, analyzing traffic data is essential to prevent fatal accidents. Traffic accidents are inevitable events that occur unexpectedly and unintentionally. In all EU member states, without exception, technical means of ensuring road safety have become widely used. In this area, it is impossible to do without the achievements of technological progress. Prevention of offenses is determined by the general goal of social prevention - to prevent offenses, to prevent antisocial behavior, and is carried out at the same levels, in the same forms and by the same means, taking into account the delicacy. The core of the prevention system is the development and implementation of a set of preventive measures.
Organizational support of preventive measures is the content of road accident prevention and it is in their implementation that the specific features of this type of prevention as an independent subsystem of social prevention are revealed. Since the line between them lies in the sphere of consequences, and violations can be and often are completely identical, preventive work aimed at preventing road accidents can be generally qualitatively homogeneous. Accident prevention activities directly affect their dynamics. Therefore, measures to prevent road accidents (hereinafter referred to as road accidents) should be comprehensive. Ensuring road safety is a complex and multifaceted problem.
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