Software System for Road Condition Forecast Correction
This work addresses road safety for drivers and authorities, but it appears incremental as it integrates existing methods rather than introducing a new approach.
The paper tackles the problem of predicting ice formation on roads to increase safety by combining physical models with machine learning for data correction, achieving improved forecast accuracy.
In this paper, we present a monitoring system that allows increasing road safety by predicting ice formation. The system consists of a network of road weather stations and intelligence data processing program module. The results were achieved by combining physical models for forecasting road conditions based on measurements from stations and machine learning models for detecting incorrect data and forecast correction.