Assessment of metro ridership fluctuation caused by weather conditions in Asian context: Using archived weather and ridership data in Nanjing
mode - subway/metro, place - asia, place - urban, ridership - modelling, ridership - behaviour
Metro, Ridership fluctuation, Benchmark, Weather, Asian context
This paper aims to assess metro ridership fluctuation caused by weather conditions in an Asian context (Nanjing, China) on metro single line and network levels. The daily ridership data utilized in the study is obtained from Nanjing Metro Agency, while meteorological data is from the Nanjing Meteorology Bureau. To address the main research questions of this paper, time-serials moving average method is extended and refined to define benchmark and to model ridership fluctuation (expressed as ridership residual). On the other hand, analyses of variance (ANOVAs) are introduced to examine meteorological events and temporal effects on ridership residuals. The data and result demonstrates that the impact of meteorological variables on daily ridership fluctuations generally results in a decrease in passengers on single lines and the travel network, especially on weekends. Precipitation related events produce more significant ridership fluctuations than temperature related events. Snowfall related events and large temperature deviations in winter account for the most dramatic changes in ridership. However, seasonality is not a significant factor in meteorological events-ridership residual relationship. This paper contributes to extending research on the weather-ridership relationship around the world especially to refining and extending the nine-term moving average method in this field. This could benefit metro operators by enabling them to add meteorological effects into their ridership prediction and budgeting work.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Li, J., Li, X., Chen, D., & Godding, L. (2017). Assessment of metro ridership fluctuation caused by weather conditions in Asian context: Using archived weather and ridership data in Nanjing. Journal of Transport Geography, Available online 26 November 2017. In Press, Corrected Proof — Note to users.