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We present a method of predicting the distribution of passenger throughput across stations and lines of a city rapid transit system by calculating the normalized betweenness centrality of the nodes (stations) and edges of the rail network. The method is evaluated by correlating the distribution of betweenness centrality against throughput distribution which is calculated using actual passenger ridership data. Our ticketing data is from the rail transport system of Singapore that comprises more than 14 million journeys over a span of one week. We demonstrate that removal of outliers representing about 10% of the stations produces a statistically significant correlation above 0.7. Interestingly, these outliers coincide with stations that opened six months before the time the ridership data was collected, hinting that travel routines along these stations have not yet settled to its equilibrium. The correlation is improved significantly when the data points are split according to their separate lines, illustrating differences in the intrinsic characteristics of each line. The simple procedure established here shows that static network analysis of the structure of a transport network can allow transport planners to predict with sufficient accuracy the passenger ridership, without requiring dynamic and complex simulation methods

A Method to Ascertain Rapid Transit Systems’ throughput Distribution Using Network Analysis