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Transportation Analytics in the Era of Big Data pp 121–151Cite as

Analyzing the Spatial and Temporal Characteristics of Subway Passenger Flow Based on Smart Card Data

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Part of the book series: Complex Networks and Dynamic Systems ((CNDS,volume 4))

Abstract

Passenger flow is a core feature of rail transportation stations, and its station-level fluctuation is strongly influenced by its surrounding land-use types. This study develops a sequential K-means clustering algorithm that utilizes smart card data to categorize Beijing subway stations. The temporal characteristics of daily inbound and outbound subway passenger flows are considered in the clustering. The stations are divided into 10 groups that are classified under three categories: employment-oriented, dual-peak, and residence-oriented stations. We analyze how these categories differ in terms of station-level passenger flow. In addition, a station-level buffer area calculation method is used to estimate the land-use density around each subway station. Considering the spatial nonstationarity of passenger flow, we employ a geographically weighted regression (GWR) model to determine the correlation effect between peak-hour passenger flow and land-use density. We then analyze the spatial distribution of the correlation coefficients. Results demonstrate that most residents commute via rail transportation, and the passenger flows for the different categories of stations exhibit distinct characteristics of residences and workplaces. The findings of this study provide insightful information and theoretical foundation for rail transportation network design and operation management.

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Acknowledgment

This work is partly supported by the National Natural Science Foundation of China (51408019, U1564212, and 71503018), Beijing Nova Program (z151100000315048).

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Authors and Affiliations

  1. School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, Beihang University, Beijing, China

    Xiaolei Ma, Jiyu Zhang & Chuan Ding

Authors
  1. Xiaolei Ma
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  2. Jiyu Zhang
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  3. Chuan Ding
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Corresponding author

Correspondence to Xiaolei Ma .

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Editors and Affiliations

  1. School of Civil Engineering, Purdue University, West Lafayette, Indiana, USA

    Satish V. Ukkusuri

  2. Tongji University, Shanghai, China

    Chao Yang

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Ma, X., Zhang, J., Ding, C. (2019). Analyzing the Spatial and Temporal Characteristics of Subway Passenger Flow Based on Smart Card Data. In: Ukkusuri, S., Yang, C. (eds) Transportation Analytics in the Era of Big Data. Complex Networks and Dynamic Systems, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-75862-6_6

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