The invention discloses a dynamic graph structure attention mechanism short-time traffic flow prediction method, and relates to the technical field of intelligent traffic, and the method comprises the steps: taking a sensor on a traffic road section as a node, taking a road section connected with the sensor as an edge, and carrying out the pre-modeling of a traffic map, and obtaining the traffic map; constructing a dynamic graph structure attention mechanism short-term traffic flow prediction model; inputting traffic flow data in the traffic map into the dynamic graph structure attention mechanism short-term traffic flow prediction model, and performing back propagation through a graph neural network to learn traffic flow features; inputting traffic flow data in a traffic map of a to-be-predicted area into the trained dynamic graph structure attention mechanism short-term traffic flow prediction model to obtain a short-term traffic flow prediction result; in a comprehensive view, the traffic flow prediction accuracy is improved by extracting the time features and the space features of the traffic and then continuously updating the traffic map, so that traffic emergencies are added in the flow prediction.
本发明公开了一种动态图结构注意力机制短时交通流预测方法,涉及智能交通技术领域,本发明包括将交通路段的上的传感器作为节点,传感器与传感器相连的路段作为边对交通图进行预建模,获得交通图;构建动态图结构注意力机制短时交通流预测模型;将交通图中的交通流数据输入动态图结构注意力机制短时交通流预测模型,通过图神经网络进行反向传播学习交通流特征;将待预测区域的交通图中的交通流数据输入训练后的动态图结构注意力机制短时交通流预测模型,获得短时交通流预测结果;综合来看,本发明通过提取交通的时间特征,和空间特征,然后不断更新交通图,从而在流量预测中加入交通突发事件,来提高交通流预测的准确性。
Dynamic graph structure attention mechanism short-term traffic flow prediction method
一种动态图结构注意力机制短时交通流预测方法
2023-12-22
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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