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城市快速路交通拥挤现象越来越普遍,不同类型的交通拥挤对快速路的交通流影响也不同,也要采取针对性的改善措施。因此,研究能够有效识别城市快速路交通拥挤的方法也是很有意义的。本文首先分析了城市快速路产生交通拥挤的成因,然后介绍了城市快速路交通拥挤状态的参数,最后结合神经网络对城市快速路采集的动态交通参数进行了案例分析。结果表明:可以有效得识别城市快速路的交通拥挤,对缓解城市交通拥堵具有显著的意义。
The phenomenon of traffic congestion in urban expressways is more and more common. Different types of traffic congestion have different impacts on the traffic flow of expressways. We also need to take targeted improvement measures. Therefore, it is also meaningful to study ways to effectively identify traffic congestion in urban expressways. This paper first analyzes the causes of traffic congestion in urban expressway, then introduces the parameters of urban expressway traffic congestion, and finally analyzes the dynamic traffic parameters collected by urban expressway with neural network. The results show that traffic congestion in urban expressway can be recognized effectively, which is of great significance to alleviate urban traffic congestion.