Empirical analysis of urban road traffic network: A case study in Hangzhou city, China

Abstract

Urban road traffic system is a time-evolving, directed weighted network in which both the topological structure and traffic flow should be considered. In this work, we collect the real-time traffic data of Xiaoshan district of Hangzhou city in China, to empirically study the properties of the traffic network. We show that the traffic patterns at different times during a day vary significantly. Specifically, at rush hours, more roads with low average velocity would emerge. Correspondingly, the average weight density at rush hours becomes smaller, while the variance increases, meaning that the traffic becomes more heterogeneous. By introducing a null model in which link weights are randomly shuffled, we find that the connected links are correlated, implying that the congested roads do not emerge at random in the network. Finally, we apply the percolation theory to study the influence of weather on the traffic network. We show that, on a rainy weekday, the traffic is more congested than that on a sunny weekday; while the result is opposite for weekends.