Short-time traffic flow control method based on deep learning and spatio-temporal data fusion

Abstract

The invention belongs to the field of short-time intelligent traffic control, and particularly relates to a short-time traffic flow control method based on deep learning and spatio-temporal data fusion. The method comprises the steps of: obtaining a data source; analyzing the time and space relevance of the historical data of an intersection; respectively establishing a time dimension GRU model and a space dimension CNN regression model according to the historical data of a prediction checkpoint and the related intersection thereof; fusing output results of the time dimension GRU model and thespace dimension CNN regression model to obtain an adaptive spatio-temporal data fusion model; and counting the prediction result of the adaptive spatio-temporal data fusion model, and sending the prediction result to a traffic department. According to the method, on the space-time level, the space-time dependence of a road traffic flow in a complex road network is analyzed, the network representation learning is used for screening the traffic data, and the screened data is used for inputting the model, so that the accuracy of the traffic flow prediction result of the intersection is improved.

Description

technical field [0001] The invention belongs to the field of short-term intelligent traffic control, and in particular relates to a short-term traffic flow control method based on deep learning and spatio-temporal data fusion. Background technique [0002] With the sustained and rapid development of the social economy, the number of cars continues to increase, and the traffic flow on the road also increases, which brings a series of traffic problems. At present, it is one of the effective ways to solve traffic problems to realize the control and induction of road traffic status through intelligent traffic control system. At the same time, accurate traffic flow forecast information can not only improve the travel efficiency of the public, but also provide a reference for the transportation department to formulate management plans and rationally allocate traffic resources. As a key technology of intelligent transportation research, short-term traffic flow analysis and predict...

AI Technical Summary

Problems solved by technology

[0004] However, this method ignores the actual connectivity of the location when analyzing the spatial correlation between intersections, and selects all relevant data in the research range as the input of the model without screening, which will not only increase the The complexity of the model will also bring in some point data that is not strongly correlated, which will affect the prediction accuracy

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