The invention discloses a traffic flow prediction method, and relates to the technical field of intelligent traffic, and the method specifically comprises the steps: S1, constructing a traffic flow prediction model; s2, acquiring related data of an urban regional traffic network and a traffic jam condition; s3, training the traffic flow prediction model, inputting traffic flow sequences into an embedding layer in sequence to fuse space-time information, extracting spatial features through a multi-graph convolution layer, and introducing a dynamic adaptive adjacency matrix to capture real-time changes in a traffic network and a complex dependency relationship between nodes especially for a traffic jam problem, so as to obtain a traffic flow prediction result; capturing space-time correlation through a space-time multi-head self-attention layer; and S4, acquiring traffic data at the current moment, inputting the acquired traffic data at the current moment into the trained traffic flow prediction model, and outputting traffic flow in a future time period, thereby more effectively solving the problem of urban traffic congestion and improving the accuracy of traffic flow prediction.
本发明公开了一种交通流量预测方法,涉及智能交通技术领域,其具体步骤包括:S1、构建交通流量预测模型;S2、获取城市区域交通网络的相关数据,以及交通拥堵情况;S3、对交通流量预测模型进行训练,将交通流序列依次输入进嵌入层来融合时空信息,通过多图图卷积层来提取空间特征,特别是针对交通拥堵问题,引入动态的自适应邻接矩阵以捕捉交通网络中的实时变化和节点间的复杂依赖关系,通过时空多头自注意力层来捕获时空相关性;S4、获取当前时刻的交通数据,将获取的当前时刻的交通数据输入训练好的交通流量预测模型,输出未来时间段的交通流量,从而更加有效的解决城市交通拥堵问题,并提高交通流量预测的准确性。
Traffic flow prediction method
一种交通流量预测方法
2024-11-15
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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