Impact Analysis of Large Shopping Malls on Inbound and Outbound Passenger Flow Rates at Urban Rail Transit Stations

［Objective］ It is aimed to reveal the impact of large shopping malls on daily passenger flow and evening peak-hour outbound passenger flow at urban rail transit stations. Based on these findings, a revised passenger flow prediction model for urban rail transit stations, incorporating the concept of generalized commercial jobs is constructed and its prediction accuracy is enhanced. ［Method］ Using the ArcGIS platform, the influential scopes of urban rail transit stations is delineated to statistically map out the residential population and employment scales within these areas. Mobile signaling data is analyzed to extract the scale of commercial jobs and visitor volumes in nearby malls, as well as medical jobs and visitor volumes in surrounding hospitals. The concept of generalized commercial jobs is introduced to describe the contribution of customer activities to passenger flow at urban rail transit stations. The influence of generalized commercial jobs on the inbound/outbound passenger flow rates of urban rail transit interchange and non-interchange stations in different regions is analyzed. One-way ANOVA (analysis of variance) is conducted to investigate the relationship between inbound/outbound passenger flow rates and generalized commercial jobs. ［Result & Conclusion］ The analysis results show that replacing conventional commercial jobs with generalized commercial jobs as a fundamental model parameter improves the accuracy of urban rail transit station inbound/outbound passenger flow prediction models. Calibration results of the passenger flow prediction revised model based on data from Shanghai downtown and urban areas demonstrates a high degree of fit. Due to the high accessibility and multiple interchange lines at interchange stations in downtown and urban areas, the influence of generalized commercial jobs on inbound/outbound passenger flow rates at urban rail transit interchange stations is not particularly significant compared to other factors.