Exploring changes in station catchment areas after opening new urban rail transit lines using cellular signalling data

Abstract

Improving the accuracy of demand forecasting and increasing ridership are imperative for ensuring urban rail transit’s sustainable development. However, the station catchment area, which is important for planning and operation in URT, was commonly oversimplified in previous studies and cannot be validated due to limited data availability and accuracy. Furthermore, how station catchment areas change with topological changes in urban rail transit networks has been sparsely investigated. This study explores changes in station catchment areas after opening new urban rail transit lines. Using cellular signalling data from Shanghai in November 2019 and 2023, it analysed passenger trips related to three new lines (Lines 15, 14, and 18) and their adjacent stations. Comparative analysis and visualisation techniques were employed to analyse the changes in areas and centroids of station catchment areas, the source of induced passengers and the diversion patterns among new and existing stations. Results show significant differences in area and centroid changes between existing stations within and outside the influential area of new lines. The relative location of existing and new lines and transfer status change were key factors influencing the changes of existing stations affected by new lines. Among frequent and super passengers of new lines, approximately 75 % had infrequent usage of the entire rail transit system before the opening of new lines, and about 5 % who used the system frequently developed new travel demands associated with the new lines. Notably, only 2 % diverted from existing lines. Both the average access and egress distance of induced passengers and the weighted average diversion distance were influenced by the station density of the areas that new lines pass through. Although the majority of diverted passengers were from close stations on parallel existing lines, some passengers who lived in the previously underserved areas may divert from distant stations to the new lines. The findings can facilitate a more accurate station ridership forecasting for proactive planning of URT and can provide policy implications for increasing ridership.