Identifying the Bottlenecks of Urban Metros and Analyzing the Passenger Source

The urban metro bottleneck is a key section that is likely to affect the connectivity of urban metro network. In this study, we employ large-scale passenger flow data of Shenzhen Metro to develop a percolation theory-based method to identify urban metro bottlenecks and analyze the passenger sources. We find the bottlenecks of Shenzhen Metro are located at different urban metro sections in different time periods and their passenger sources are relatively concentrated in space. The connectivity of urban metro network can be improved through decreasing the load ratios of bottleneck sections. The passenger source information in this study can facilitate the decrease of the load ratio of bottleneck sections more efficiently and benefit the improvement of urban metro management.