Unveiling Travel Mobility and Network Robustness of Sustainable Bus System: From the Perspectives of Flow, Transfer and Structure

The bus system is considered a green transportation mode to alleviate traffic congestion in big cities. Understanding travel mobility and network robustness contributes to the design, management and sustainability of the bus system. This paper proposes a framework to evaluate the spatiotemporal characteristics of bus ridership and network robustness based on real-world trip data. First, we analyze the spatiotemporal characteristics of passenger flow, including transfer times, equity, spatial autocorrelation and complex network features. Second, the k-means algorithm is adopted to cluster the passengers according to travel attributes in a week. Finally, a node failure process is introduced to evaluate the robustness of the bus network. The bus network of Beijing is taken as an example to test the model. The results show that the passenger flow is concentrated in the central area and approximately 85% of passengers have no intra-bus transfer during a day. Moreover, we find that the bus passengers can be divided into four groups. In addition, the bus network is mostly vulnerable when subjected to degree-based and betweenness-based attacks from the perspective of structures, while it is mostly vulnerable to strength-based attacks from the perspective of transfers.