Urban road network global traffic state prediction method, electronic device and storage medium

Abstract

The invention relates to a method for predicting the global traffic state of an urban road network, an electronic device and a storage medium, and the method for predicting the traffic state through a trained traffic state prediction model comprises the steps: receiving to-be-predicted data through a signal timing detection module, the to-be-predicted data comprises an adjacent matrix of a road network unweighted directed graph, historical traffic state data and historical signal timing data; the signal timing detection module judges whether road network level signal timing change is detected or not according to historical signal timing data, if not, the passive prediction module generates a predicted traffic state through an adjacent matrix of a road network unauthorized directed graph and historical traffic state data, and if yes, the passive prediction module generates a predicted traffic state; if not, the active prediction module generates the predicted traffic state through the adjacent matrix of the road network unweighted directed graph, the historical traffic state data and the historical signal timing data, that is, the traffic state prediction model in the application predicts the traffic state not only based on the traffic flow characteristics, but also based on the traffic signal control, so that the prediction accuracy is improved.

Description

technical field [0001] The present application relates to the technical field of traffic forecasting, in particular to a method, an electronic device and a storage medium for forecasting traffic conditions in the entire area of ​​an urban road network. Background technique [0002] Traffic state prediction is one of the most challenging tasks in the development of intelligent transportation systems. Traffic state prediction is based on historical observations to predict the traffic state (such as link speed, traffic flow and delay, etc.) in the future traffic network. In engineering practice, traffic status is regarded as one of the main indicators of urban traffic signal control. At the level of the entire traffic network, traffic status is an important indicator for identifying traffic congestion, and it can predict the traffic status of road network-level sections in the near future. Control, operations and management are critical. [0003] In related technologies, the ...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a method, an electronic device, and a storage medium for predicting the traffic state in the entire urban road network, so as to at least solve the problem of only considering the traffic flow characteristics and not considering the traffic signal control when predicting the traffic state based on a passive model in the related art. The problem of low accuracy

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