Road icing identification method fusing image and meteorological environment data

Abstract

The invention discloses an image and meteorological environment data fused road icing identification method, which comprises the following steps of: monitoring the real-time state of a local road surface by using multiple channels such as an on-site exploration system and a remote terminal monitoring system to obtain image data and meteorological environment data, and performing feature extraction on the image data and the meteorological environment data; an image data sample and a meteorological environment data sample are obtained, the two kinds of data are fused, a brand-new machine learning model, namely a convolution-ensemble learning model, for identifying icing and snow accumulation on the road surface is constructed, the model is continuously trained and debugged by selecting a proper machine learning method, and the identification accuracy of the icing and snow accumulation on the road surface is improved. And finally, a machine learning model capable of being used for winter road surface icing identification is established. The road icing identification efficiency and accuracy can be improved, the application is simple and convenient, the model is easy to improve, and the method can be widely applied to road, bridge and airport icing prediction.

Description

technical field [0001] The invention belongs to the technical field of road traffic, and relates to a road icing recognition technology, in particular to a road icing recognition method for fusing images and meteorological environment data. Background technique [0002] Machine learning is a supervised learning method. The supervised method learns a classification model through training data, and applies the classification model to the classification of unknown data. At present, snow melting and ice melting technology is gradually applied to roads, and many major breakthroughs have been made in some fields, especially in the ice melting of bridges, as well as intelligent predictive analysis and automatic monitoring system control to achieve precise ice melting. With the continuous development of its projects, the accumulation of multi-channel monitoring images and data will increase, and the complexity of the model will increase, which will lead to cluttered images and data,...

AI Technical Summary

Problems solved by technology

With the continuous development of its projects, the accumulation of multi-channel monitoring images and data will increase, and the complexity of the model will increase, which will lead to cluttered images and data, and it is impossible to get accurate and accurate information from the live environment. Timely feedback, and the processing of image data and conventional data is only one-way, and they are not integrated and processed together. The time for software running is increased, and the work efficiency is lacking, which leads to the collapse of the system.

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