engleski

Prediction of Traffic Accidents Severity Based on Machine Learning and Multiclass Classification Model

Road traffic accidents are a common and seemingly inevitable problem. While its occurrences rely on many unpredictable factors, this paper shows how to utilize machine learning to predict the severity of the accident. The dataset used was related to road accidents in the United Kingdom over a period of a few years. Some of the parameters observed were the weather conditions, sun position, speed limit, and time of the day. To predict the severity of the accident given the circumstances and road conditions, a multiclass classification model is used. Different datasets were combined to cover different situations and scenarios that happen in traffic and taking the severity of accidents in prediction. The dataset values were normalized before the training process and the training set and validated on the validation dataset. The prediction results show the correlation between used weather conditions, daylight time, and traffic accident severity.

multiclass classification ; deep learning ; road accidents

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