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Transit ridership estimation with network Kriging: a case study of Second Avenue Subway, NYC

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  • Zhang, Dapeng
  • Wang, Xiaokun (Cara)

Abstract

An attractive topic in transportation practice is transit ridership estimation. Reliable estimates are beneficial to spatial structuring, facility design, and vehicle operation, as well as financial and labor management. Traditional ridership estimation approaches mainly rely on regression models that consider subway fares, population, and employment distribution in surrounding areas. Yet consideration of ridership’s spatial dependency is largely lacking in these models. This paper recognizes the spatial effect by estimating the ridership of the new Second Avenue Subway in New York City using a network Kriging method. Network distance, instead of Euclidean distance, is used to reflect the fact that subway stations are only connected by subway tunnels. Results show that the new service should effectively relieve the traffic burden on other currently crowded subway lines.

Suggested Citation

  • Zhang, Dapeng & Wang, Xiaokun (Cara), 2014. "Transit ridership estimation with network Kriging: a case study of Second Avenue Subway, NYC," Journal of Transport Geography, Elsevier, vol. 41(C), pages 107-115.
  • Handle: RePEc:eee:jotrge:v:41:y:2014:i:c:p:107-115
    DOI: 10.1016/j.jtrangeo.2014.08.021
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    14. Tu, Wei & Cao, Rui & Yue, Yang & Zhou, Baoding & Li, Qiuping & Li, Qingquan, 2018. "Spatial variations in urban public ridership derived from GPS trajectories and smart card data," Journal of Transport Geography, Elsevier, vol. 69(C), pages 45-57.
    15. Jeongwoo Lee & Marlon Boarnet & Douglas Houston & Hilary Nixon & Steven Spears, 2017. "Changes in Service and Associated Ridership Impacts near a New Light Rail Transit Line," Sustainability, MDPI, vol. 9(10), pages 1-27, October.
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