Author
Listed:
- Hasan, Nurul
- Nirmale, Sangram Krishna
- Deepa, L.
- Pinjari, Abdul Rawoof
Abstract
Transit ridership modeling is essential for informing service planning and infrastructure investments in public transport systems. This study develops and applies direct demand models of metro rail ridership, disaggregated by station and travel direction, to capture directional variation in boardings and alightings at the station level. Unlike most prior studies that aggregate station-level ridership regardless of travel direction, the proposed approach enables a richer analysis of ridership at the granularity of station and travel direction as a function of direction-specific accessibility measures and inter-route interactions (competition and complementarity) between metro and bus networks. Separate log-linear regression models are estimated for boarding and alighting, incorporating station-level catchment characteristics, direction-specific accessibility metrics (downstream accessibility for boardings model and upstream accessibility for alightings model), interactions between metro and bus networks, spatial dependencies among closely spaced stations, and station-level random effects. The models are applied to data from 40 metro stations along two corridors of Bengaluru, India. Model estimation results and prediction exercises highlight the significance of accounting for downstream accessibility in boardings model and upstream accessibility in alightings model, along with competition and complementarity between metro and bus networks. Policy simulations suggest that increasing feeder bus services and land-use densification around stations can help enhance metro ridership in the city.
Suggested Citation
Hasan, Nurul & Nirmale, Sangram Krishna & Deepa, L. & Pinjari, Abdul Rawoof, 2025.
"Modelling metro rail ridership at the station- and route-level: an application to analysis of metro ridership in Bengaluru, India,"
Transportation Research Part A: Policy and Practice, Elsevier, vol. 200(C).
Handle:
RePEc:eee:transa:v:200:y:2025:i:c:s0965856425002666
DOI: 10.1016/j.tra.2025.104638
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