Random Forest based Prediction Method and System of Road Surface Condition Using Spatio-Temporal Features

摘要

The present invention relates to a method and system for predicting a road surface condition based on a random forest using spatiotemporal characteristics, the steps of collecting road surface condition data including coordinate information of the road surface condition and the point at which the road surface condition is collected, precipitation in a predetermined area Collecting weather data including information and temperature information, converting the coordinate information included in the road surface condition data into a predetermined index value, using the road surface condition data and the weather data in which the coordinate information is converted into a predetermined index value and learning the road surface condition prediction model using the learning data constructed by the method, and predicting the road surface condition at the road surface condition prediction point using the road surface condition prediction model. The coordinate information may be converted into an index value corresponding to a grid in which a predetermined area is divided into a predetermined size. The index value may use a Morton Code.