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Dynamic transit accessibility and transit gap causality analysis

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  • Fayyaz, S. Kiavash
  • Liu, Xiaoyue Cathy
  • Porter, Richard J.

Abstract

Public Transit Accessibility (PTA) analysis helps transit agencies and planners identify areas in need of transit service improvements and prioritize transit investments. To evaluate the accessibility of existing transit services and identify access gaps, it is critical to accurately estimate travel times between transit stops, which change throughout the day due to transit schedule variations. Commonly used methods in PTA ignore such temporal fluctuation. Moreover, these methods are unable to elucidate the causes of poor PTA. To address these issues, we first implemented an algorithm to effectively compute travel times at multiple departure times throughout the day in order to enable spatiotemporal PTA analysis. A series of indicators that are intuitive to interpret were developed to determine the varying causes of poor PTA and identify areas with immediate needs for improvements. We showcase the analytical framework using a transit network in the State of Utah operated by the Utah Transit Authority. The analysis is based solely on publicly-available open datasets, which makes it generally adaptable to other transit networks. Results can assist transit agencies with identifying areas in need of service improvement and prioritizing future investments.

Suggested Citation

  • Fayyaz, S. Kiavash & Liu, Xiaoyue Cathy & Porter, Richard J., 2017. "Dynamic transit accessibility and transit gap causality analysis," Journal of Transport Geography, Elsevier, vol. 59(C), pages 27-39.
    • Handle: RePEc:eee:jotrge:v:59:y:2017:i:c:p:27-39
    DOI: 10.1016/j.jtrangeo.2017.01.006
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    Cited by:

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    7. Kelobonye, Keone & McCarney, Gary & Xia, Jianhong (Cecilia) & Swapan, Mohammad Shahidul Hasan & Mao, Feng & Zhou, Heng, 2019. "Relative accessibility analysis for key land uses: A spatial equity perspective," Journal of Transport Geography, Elsevier, vol. 75(C), pages 82-93.
    8. Arbex, Renato & Cunha, Claudio B., 2020. "Estimating the influence of crowding and travel time variability on accessibility to jobs in a large public transport network using smart card big data," Journal of Transport Geography, Elsevier, vol. 85(C).
    9. Cheng, Shaowu & Xie, Bing & Bie, Yiming & Zhang, Yaping & Zhang, Shen, 2018. "Measure dynamic individual spatial-temporal accessibility by public transit: Integrating time-table and passenger departure time," Journal of Transport Geography, Elsevier, vol. 66(C), pages 235-247.
    10. Wei, Ran & Liu, Xiaoyue & Mu, Yongjian & Wang, Liming & Golub, Aaron & Farber, Steven, 2017. "Evaluating public transit services for operational efficiency and access equity," Journal of Transport Geography, Elsevier, vol. 65(C), pages 70-79.
    11. Shi, Yuji & Blainey, Simon & Sun, Chao & Jing, Peng, 2020. "A literature review on accessibility using bibliometric analysis techniques," Journal of Transport Geography, Elsevier, vol. 87(C).
    12. Kim, Junghwan & Lee, Bumsoo, 2019. "More than travel time: New accessibility index capturing the connectivity of transit services," Journal of Transport Geography, Elsevier, vol. 78(C), pages 8-18.
    13. Jairo Ortega & János Tóth & Tamás Péter, 2021. "A Comprehensive Model to Study the Dynamic Accessibility of the Park & Ride System," Sustainability, MDPI, vol. 13(7), pages 1-17, April.
    14. Weckström, Christoffer & Kujala, Rainer & Mladenović, Miloš N. & Saramäki, Jari, 2019. "Assessment of large-scale transitions in public transport networks using open timetable data: case of Helsinki metro extension," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    15. Luis A. Guzman & Daniel Oviedo & Rafael Cardona, 2018. "Accessibility Changes: Analysis of the Integrated Public Transport System of Bogotá," Sustainability, MDPI, vol. 10(11), pages 1-15, October.
    16. Stępniak, Marcin & Pritchard, John P. & Geurs, Karst T. & Goliszek, Sławomir, 2019. "The impact of temporal resolution on public transport accessibility measurement: Review and case study in Poland," Journal of Transport Geography, Elsevier, vol. 75(C), pages 8-24.
    17. Sharma, Gajanand & Patil, Gopal R., 2024. "Urban spatial structure and equity for urban services through the lens of accessibility," Transport Policy, Elsevier, vol. 146(C), pages 72-90.
    18. Meijie Chen & Yumin Chen & Xiaoguang Wang & Huangyuan Tan & Fenglan Luo, 2019. "Spatial Difference of Transit-Based Accessibility to Hospitals by Regions Using Spatially Adjusted ANOVA," IJERPH, MDPI, vol. 16(11), pages 1-20, May.
    19. Handley, John C. & Fu, Lina & Tupper, Laura L., 2019. "A case study in spatial-temporal accessibility for a transit system," Journal of Transport Geography, Elsevier, vol. 75(C), pages 25-36.
    20. Barajas, Jesus M. & Brown, Anne, 2021. "Not minding the gap: Does ride-hailing serve transit deserts?," Journal of Transport Geography, Elsevier, vol. 90(C).
    21. Sharma, Gajanand & Patil, Gopal R., 2021. "Public transit accessibility approach to understand the equity for public healthcare services: A case study of Greater Mumbai," Journal of Transport Geography, Elsevier, vol. 94(C).
    22. Shixiong Jiang & Wei Guan & Liu Yang & Wenyi Zhang, 2020. "Feeder Bus Accessibility Modeling and Evaluation," Sustainability, MDPI, vol. 12(21), pages 1-17, October.
    23. Kim, Hyun & Lee, Keumsook & Park, Jong Soo & Song, Yena, 2018. "Transit network expansion and accessibility implications: A case study of Gwangju metropolitan area, South Korea," Research in Transportation Economics, Elsevier, vol. 69(C), pages 544-553.
    24. N. Nima Haghighi & Xiaoyue Cathy Liu & Ran Wei & Wenwen Li & Hu Shao, 2018. "Using Twitter data for transit performance assessment: a framework for evaluating transit riders’ opinions about quality of service," Public Transport, Springer, vol. 10(2), pages 363-377, August.

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