Navigation reminding method for short-term traffic flow prediction based on SVD-PSO-LSTM

Abstract

The invention relates to a navigation reminding method for short-term traffic flow prediction based on SVD-PSO-LSTM. Firstly, an LSTM model is trained and optimized; collecting historical traffic flowdata; preprocessing the LSTM model, and inputting the preprocessed LSTM model into the trained and optimized LSTM model; the method comprises the following steps: outputting a prediction result of ashort-time traffic flow by a traffic flow sensor, publishing the prediction result of the short-time traffic flow on navigation software, displaying the prediction result of the short-time traffic flow on a road section in different colors according to the traffic flow, providing displayed information for a driver to refer to congestion, and reasonably planning travel and selecting a navigation route according to the displayed information. When the LSTM model is trained and optimized, historical traffic flow data is collected, preprocessed and then divided into a training set and a test set, and then the LSTM model is trained and optimized by adopting a PSO algorithm and the training set; wherein the preprocessing comprises the step of performing noise reduction operation on the data by adopting an SVD algorithm. The method provided by the invention is more accurate in prediction effect, and can reasonably plan a navigation route.

Description

technical field [0001] The invention belongs to the technical field of intelligent traffic systems, and relates to a navigation reminder method based on SVD-PSO-LSTM short-term traffic flow prediction. Background technique [0002] With the advancement of science and technology, the automobile industry has also achieved rapid development, and the number of automobiles in my country has continued to increase, bringing convenience to people's lives. But at the same time, the increase in the number of cars in cities has also brought a series of complex problems such as traffic congestion. When people choose a travel route, it is difficult to predict the congestion situation of future roads, which causes great trouble for people to choose a navigation route. Therefore urgently need a kind of reminding method, on the basis of forecasting traffic flow, forecast result is issued on the navigation software, for driver's reference, and reasonable choice travel route. [0003] The c...

AI Technical Summary

Problems solved by technology

Traffic flow data will produce random errors during the collection process, and in the existing prediction methods, the collected traffic flow data has not been denoised, which affects the prediction accuracy of the model to a certain extent

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