Application of big data visualization in passenger flow analysis of Shanghai Metro network

The passenger flow data of urban rail transit (URT) network has the characteristics of large scale, fast-update, multi-mode, difficult to identify and great value, the same as Big Data. It is meaningful and effective to use big data visualization in passenger flow analysis. In this paper, with high visualization frameworks, the massive data of passenger flow in Shanghai Metro network is highly graphical in time-space, which is processing from four aspects: the network, line, station and section. It is efficient in mining the passenger flow data further and showing more information and laws. The research results provide new means for passenger flow analysis and operation aid decision making (ADM) of urban rail transit operation and management department.