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Access to transit? Validating local transit accessibility measures using transit ridership

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  • Bree, Sarah
  • Fuller, Daniel
  • Diab, Ehab

Abstract

Local transit accessibility measures are important tools used by planners to understand the effects of changes to public transit systems. Several local transit accessibility measures exist in the literature, however, it is not clear how these measures relate to public transit usage. Therefore, the aim of this study is to evaluate several transit accessibility measures that are commonly used in the literature by examining their associations with ridership levels at the dissemination area level. The assessed transit accessibility measures ranged from a basic stop count, to gravity-based measures which use distance decay functions from a local household survey, and Walkscore.com’s Transit Score. Using several land use and transit service datasets, including data collected from the fare box systems onboard the Saskatoon Transit buses, three types of models were tested. These models include ordinary least square models (OLS), spatial lag models (SLM), and spatial error models (SEM). The results from the models suggest that we can more closely predict actual public transit ridership when including a gravity-based accessibility measure in the model, while controlling for several household socioeconomic factors and built environment characteristics. In all cases, the measure that best fit the variation in ridership was the filtered frequency accessibility measure calculated using a 400 m network buffer and a Butterworth filter with a distance decay bandpass value of 250 m. This study offers transit planners and practitioners a better understanding of the performance of different transit local accessibility measures in relationship to actual transit ridership.

Suggested Citation

  • Bree, Sarah & Fuller, Daniel & Diab, Ehab, 2020. "Access to transit? Validating local transit accessibility measures using transit ridership," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 430-442.
    • Handle: RePEc:eee:transa:v:141:y:2020:i:c:p:430-442
    DOI: 10.1016/j.tra.2020.09.019
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    References listed on IDEAS

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    Cited by:

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    3. Du, Qiang & Zhou, Yuqing & Huang, Youdan & Wang, Yalei & Bai, Libiao, 2022. "Spatiotemporal exploration of the non-linear impacts of accessibility on metro ridership," Journal of Transport Geography, Elsevier, vol. 102(C).
    4. Jianming Le & Kunhui Ye, 2022. "Measuring City-Level Transit Accessibility Based on the Weight of Residential Land Area: A Case of Nanning City, China," Land, MDPI, vol. 11(9), pages 1-17, September.
    5. Lingyi Qiu & Xuemei Zhu, 2021. "Housing and Community Environments vs. Independent Mobility: Roles in Promoting Children’s Independent Travel and Unsupervised Outdoor Play," IJERPH, MDPI, vol. 18(4), pages 1-17, February.
    6. Singh, Suraj Shirodkar & Javanmard, Reyhane & Lee, Jinhyung & Kim, Junghwan & Diab, Ehab, 2021. "The new BRT system has led to an overall increase in transit-based accessibility to essential services during the COVID-19 pandemic: Empirical evidence from Winnipeg, Canada," OSF Preprints anjd7, Center for Open Science.
    7. Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
    8. Merlin, Louis A. & Singer, Matan & Levine, Jonathan, 2021. "Influences on transit ridership and transit accessibility in US urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 63-73.

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