A dynamic network partition method for heterogenous urban traffic networks

Recently, it has been shown that Macroscopic Fundamental Diagrams(MFDs) existing in large scale urban traffic networks paly an important role in dynamic traffic management, traffic signal control and mitigation of urban traffic congestion. A well defined MFD can be derived from a homogeneous urban traffic network with similar traffic conditions. In reality, however, most large scale traffic networks are usually heterogeneous networks with various road types and uneven distribution of congestion. In order to use the MFD concept for controlling the large scale urban traffic network through hierarchical or decentralized methods, it is necessary to exploit a network partition method, which should be both effective in extracting homogeneous sub-networks and fast to compute. In this paper, a new approach to calculate the correlation degree, which describes the traffic conditions between two adjacent intersections quantitatively, is first proposed. Then, a fast network division approach by optimizing the modularity, which is a criterion to distinguish the quality of the partition results, is applied to identify the homogeneous sub-networks for large scale urban traffic networks. Finally, an application to a specified urban traffic network is investigated by using the proposed algorithm. The results show that it is an effective and efficient method for partitioning heterogeneous urban traffic networks automatically.