Method for maximizing traffic capacity of key road based on traffic flow prediction

Abstract

The invention relates to a solution based on the Internet of Things and the big data information technology, in particular to a deep neural network, which comprises the following steps of: acquiring short-time and long-time historical data of road network traffic flow, and performing deep learning by using a Node2vec and graph multi-attention neural network (GMAN) fusion mechanism; training a prediction model, predicting the traffic flow states of the target road section and nodes of the road network for 30 minutes after the current time point, and carrying out the real-time intelligent feedback of the green signal ratio of the signal lamp according to the prediction result, thereby achieving the purposes of precisely limiting the flow, mining the traffic capacity of the road network to the maximum degree, and reducing the congestion and traffic paralysis caused by an accident. According to the method, traffic data acquisition and conversion are converted into adjustment and control ofthe traffic signal lamps, a set of complete method for maximizing the traffic capacity of the key road is formed, application verification is carried out in actual engineering, and the effects of accurate flow limiting, maximum excavation of the traffic capacity of the road network and reduction of congestion and traffic paralysis caused by accidents are achieved.

Description

technical field [0001] The invention relates to the technical field of intelligent traffic system operation and safety management control, in particular to a method for maximizing key road traffic capacity based on traffic flow prediction. Background technique [0002] With the rapid growth of car ownership and the diversification and enrichment of travel demand, road traffic flow is showing a migration to the direction of space-time multi-dimensional dynamic development. There are multiple factors such as the surge in road traffic travel demand, the negative impact of bad weather, and the limited service functions of traffic facilities. Under the coupling effect, the traffic capacity and safe operation of the road are greatly challenged, such as: holidays, rush hour, and rain, fog, ice and snow, strong wind and other harsh weather conditions, resulting in the demand for efficient and safe operation of the road and the limitation of traffic facilities. The contradiction betw...

AI Technical Summary

Problems solved by technology

However, this kind of management scheme is relatively extensive. On the one hand, limiting the flow too early or canceling it too late will limit the maximum traffic rate; on the other hand, limiting the flow too late or canceling it too early will cause congestion and paralysis of key roads. It cannot be solved at all. At

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