Exploring the topological characteristics of urban trip networks based on taxi trajectory data

As an essential mode of travel for city residents, taxis play a significant role in meeting travel demands in an urban city. Understanding the modal characteristics of taxis is vital to addressing many difficulties regarding urban sustainability. The movement trajectory of taxis reflects not only the operating features of taxis themselves but also urban structure and human mobility. In this work, the taxi trajectory data of Chengdu and New York City is processed, and the corresponding urban trip networks are constructed based on geographic information systems. We empirically and systematically analyze these urban trip networks according to the network hierarchy based on complex network theory. First, we studied the low-order organization of the urban trip networks (i.e., degree distribution, cluster-degree coefficient, rich-club coefficient, and so on.). We uncover the nontrivial relationship between network density and trip distance and find that the urban trip network in Chengdu is more heterogeneous than that in New York City. Second, we investigate the meso-order organization of the urban trip networks by using community detection. The community detection results show that the community boundaries are more or less mismatched with the administrative boundaries. Finally, we detect the higher-order organizations of the urban trip networks and find some critical nodes and regions. These empirical results from the perspective of complex networks provide insight to better understand the urban structure and human mobility, and potentially amend urban planning.