高速公路城市化路段短时交通量预测方法研究

摘要

We construct a short-term traffic volume forecasting model based on the analysis of the cause of the congestion of the urbanized section of a freeway and RBF neural network.It will provide basic theory and technical support for the evaluation of the service level and the traffic control and pilot of a freeway.We eventually verify the effectiveness of the model,taking Jingjintang freeway as an example.Result shows that the model is reasonable and feasible.%在对高速公路进出城路段交通拥堵现象产生原因进行分析的基础上,基于径向基神经网络的思想,建立了适用于高速公路城市化路段的短时交通量预测模型,为高速公路服务水平判定、交通控制与诱导提供理论依据和技术支持。最后,以京津塘高速公路城市化路段为例,对建立的模型进行效果验证,结果证明所建立的方法是有效性的、可行的。