Environmental Science
2 years ago

New method predicts winter road conditions with 95% accuracy using random forest.

Asian Transport Studies
Development of a method for estimating road surface condition in winter using random forest
Y. Takasaki, Miguel A. Saldaña, Jun Ito, Kazushi Sano

Paper Summary

Road surface snow conditions can be estimated using weather conditions and traffic volume, making winter road management more efficient. A model was created using random forest to estimate road surface conditions, achieving an accuracy of around 95%. When tire noise was included in the model, the accuracy slightly decreased.

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