The invention discloses an urban road network traffic state prediction method and device, equipment and a medium, and relates to the technical field of traffic, and the method comprises the steps: obtaining the basic parameters of a target urban region and the target traffic state data of a historical time period; determining road network density data according to the basic parameters of the target city area by using a road network density calculation formula; inputting the target traffic state data of the historical time period into the trained dynamic space-time residual convolutional neural network model to obtain traffic state prediction data of the next time period of the historical time period; the dynamic space-time residual convolutional neural network model comprises a residual convolution module, a dynamic convolution module based on road network density, a space-time attention mechanism module and a fusion module which are connected in sequence; and the weight corresponding to each dynamic convolution kernel in the dynamic convolution module based on the road network density is adjusted according to the road network density data. The prediction efficiency and accuracy are improved.
本申请公开了一种城市级路网交通状态预测方法、装置、设备及介质,涉及交通技术领域,该方法包括:获取目标城市区域的基本参数以及历史时间段的目标交通状态数据;利用路网密度计算公式,根据目标城市区域的基本参数确定路网密度数据;将历史时间段的目标交通状态数据输入训练好的动态时空残差卷积神经网络模型中,得到历史时间段的下一时间段的交通状态预测数据;动态时空残差卷积神经网络模型包括依次连接的残差卷积模块、基于路网密度的动态卷积模块、时空注意力机制模块和融合模块;根据路网密度数据调整基于路网密度的动态卷积模块中每一动态卷积核对应的权重,本申请提高了预测效率和准确度。
Urban road network traffic state prediction method, device, equipment and medium
一种城市级路网交通状态预测方法、装置、设备及介质
2025-03-04
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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