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Modeling and clustering network-level urban traffic status based on traffic flow assignment ratios

机译:基于交通流分配比率的网络级城市交通状况建模和聚类

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The detected traffic data for single point or link cannot satisfy the needs for network-level traffic status information with the rapid development of the traffic control and guidance systems. This paper proposed a modeling and clustering method for network-level urban traffic status based on the dynamic traffic flow assignment ratios. The traffic assignment ratio matrix model integrates traffic status, topology and relation between links, with the dynamic traffic assignment ratios estimated by Linear Programming. The network-level traffic status is clustered by Self-Organizing Map and the typical patterns are discovered. The experiment proves the efficiency and applicability of this method for network-level traffic status modeling and analyzing.
机译:随着交通控制和引导系统的快速发展,针对单点或链路的检测到的交通数据不能满足对网络级交通状态信息的需求。提出了一种基于动态交通流量分配比的网络级城市交通状态建模与聚类方法。流量分配比率矩阵模型将流量状态,拓扑和链路之间的关系集成在一起,并通过线性规划估算出动态流量分配比率。通过自组织映射对网络级别的流量状态进行聚类,并发现典型的模式。实验证明了该方法在网络级流量状态建模和分析中的有效性和适用性。

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