Temporal Variation and Spatial Heterogeneity in Boarding/Alighting Patterns at Urban Railway Stations: Implications for Estimating Optimal Construction Scale—A Case Study in Seoul, South Korea

Table 1

Literature review of congestion in railway stations.

Research	Research objective	Data	Methodology
Ahn et al. [1]	Analysis of passenger pedestrian flow for railway station planning and management	Survey data (walking path)	Gravity model, VISSIM simulation
Yang and Tang [2]	Analysis of peak-hour passenger departure time adjustment effects due to fare discounts	OD, network	Traffic assignment (UE), queuing theory
Teng et al. [3]	Analysis of psychological factors influencing passengers’ perception of pedestrian environment within railway stations	Survey data (SP, RP)	Perceived congestion quantization model (regression model)
Li et al. [4]	Analysis of the correlation between land use and railway station utilization patterns	Bike-sharing usage history data	Random forest model
Li et al. [5]	Development of methodology for analyzing congestion patterns in urban rail networks due to train delays	Rail network data	Passenger flow congestion model
Wang et al. [6]	Analysis of the characteristics of sudden passenger flow and proposal of congestion management methods in an intelligent urban rail transit network	Simulation data	Statistical analysis
Jiao et al. [7]	Analysis of the correlation between land use and boarding/alighting patterns based on spatiotemporal similarity in boarding/alighting patterns	Smart card data	Clustering algorithm