The spatial partitioning problem of urban traffic network sub-regions has been mainly researched in static mode by considering traffic conditions at a certain time. Nevertheless, traffic flow has strong dynamic characteristics running in urban network; it is necessary to divide the sub-regions according to the correlation of traffic flow in spatiotemporal dimension. Dynamic partitioning is of great significance for capturing the evolution of traffic sub-region and designing the peripheral control strategies in real time. In this paper, a large heterogeneous traffic network is divided into several uniform sub-regions by analyzing the temporal similarity and spatial heterogeneity of the link characteristics to reveal the evolution process of traffic flow. Firstly, a similarity model is defined by the analysis of link autocorrelation based on Moran’s I index, and the slow coherency theory combining with \(\alpha \)-Cut theory (called \(\alpha \)-SC) is implemented to establish the framework of static partitioning. Secondly, a fine-tuning procedure is designed to maintain the homogeneity and compactness of the sub-regions. Finally, the links with high heterogeneity in the sub-regions are identified by heuristic algorithm and then iteratively adjusted, merged and cut to realize the dynamic updating of sub-regions. A case study using the real data set of Farmers Branch city is conducted to verify the effectiveness of the proposed method.

城市交通网络子区域的空间划分问题主要是在静态模式下考虑某一时刻的交通状况进行研究。然而，交通流在城市网络中运行具有很强的动态特性；需要根据交通流在时空维度上的相关性来划分子区域。动态分区对于实时捕捉交通子区域的演变和设计外围控制策略具有重要意义。本文通过分析链路特征的时间相似性和空间异质性，将大型异构交通网络划分为若干统一的子区域，揭示交通流的演化过程。首先，\(\alpha \) -Cut 理论（称为\(\alpha \) -SC）被实现来建立静态划分的框架。其次，设计了微调程序以保持子区域的均匀性和紧凑性。最后，通过启发式算法识别子区域内异质性高的链接，然后进行迭代调整、合并和切割，实现子区域的动态更新。使用农民分支城市的真实数据集进行案例研究，以验证所提出方法的有效性。