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To What Extent May Transit Stop Spacing Be Increased before Driving Away Riders? Referring to Evidence of the 2017 NHTS in the United States

Author

Listed:
  • Telan Wu

    (School of Rail Transportation, Soochow University, Suzhou 215131, China)

  • Hui Jin

    (School of Rail Transportation, Soochow University, Suzhou 215131, China)

  • Xiaoguang Yang

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201800, China)

Abstract

With the emergence of ride-sourcing and ride-splitting services, more options are available to support shifts away from transit, where maintaining transit ridership increases requirements for transit service quality, so as to promote high-capacity and sustainable transport systems. In this endeavor, proper transit stop spacing is critical for both service accessibility and in-vehicle trip efficiency, as well as operation cost. This research explores acceptable stop spacing for three kinds of transit services from the perspective of travel behavior, drawing on the 2017 National Household Travel Survey in the United States. A stochastic frontier model is developed to infer passengers’ unobservable vertex of acceptable transit access times on the basis of observed walk time, which can be converted to the tolerance with respect to stop spacing with the average walking speed. Significant explanatory variables on the vertex of acceptable transit stop spacing are further identified with their quantified impacts, including household density, household income, wait time, trip distance, transfer, and maintenance purpose, while the inefficiency variance is significantly related to traveler age, wait time, secondary walk time, and trip frequency. Recommended response strategies follow. Findings from this study provide insights, guidelines, and implementation plans for different transit agencies when considering stop spacing redesign, to strengthen transit service appeal and to promote cooperative and sustainable multi-modal urban transport systems.

Suggested Citation

  • Telan Wu & Hui Jin & Xiaoguang Yang, 2022. "To What Extent May Transit Stop Spacing Be Increased before Driving Away Riders? Referring to Evidence of the 2017 NHTS in the United States," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6148-:d:818587
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    1. Boisjoly, Geneviève & Grisé, Emily & Maguire, Meadhbh & Veillette, Marie-Pier & Deboosere, Robbin & Berrebi, Emma & El-Geneidy, Ahmed, 2018. "Invest in the ride: A 14 year longitudinal analysis of the determinants of public transport ridership in 25 North American cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 434-445.
    2. Wiegmans, Bart & Witte, Patrick, 2017. "Efficiency of inland waterway container terminals: Stochastic frontier and data envelopment analysis to analyze the capacity design- and throughput efficiency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 12-21.
    3. O'Connor, David & Caulfield, Brian, 2018. "Level of service and the transit neighbourhood - Observations from Dublin city and suburbs," Research in Transportation Economics, Elsevier, vol. 69(C), pages 59-67.
    4. Li, Jianling, 2018. "Residential and transit decisions: Insights from focus groups of neighborhoods around transit stations," Transport Policy, Elsevier, vol. 63(C), pages 1-9.
    5. Yang, Hai & Qin, Xiaoran & Ke, Jintao & Ye, Jieping, 2020. "Optimizing matching time interval and matching radius in on-demand ride-sourcing markets," Transportation Research Part B: Methodological, Elsevier, vol. 131(C), pages 84-105.
    6. Jushan Bai & Serena Ng, 2005. "Tests for Skewness, Kurtosis, and Normality for Time Series Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 49-60, January.
    7. Clewlow, Regina R. & Mishra, Gouri S., 2017. "Disruptive Transportation: The Adoption, Utilization, and Impacts of Ride-Hailing in the United States," Institute of Transportation Studies, Working Paper Series qt82w2z91j, Institute of Transportation Studies, UC Davis.
    8. David Hensher & April Reyes, 2000. "Trip chaining as a barrier to the propensity to use public transport," Transportation, Springer, vol. 27(4), pages 341-361, December.
    9. Owen, Andrew & Levinson, David M., 2015. "Modeling the commute mode share of transit using continuous accessibility to jobs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 110-122.
    10. David A. Kodde & Jozef M. M. Ritzen, 1988. "Direct and Indirect Effects of Parental Education Level on the Demand for Higher Education," Journal of Human Resources, University of Wisconsin Press, vol. 23(3), pages 356-371.
    11. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464.
    12. Johnson, Daniel & Ercolani, Marco & Mackie, Peter, 2017. "Econometric analysis of the link between public transport accessibility and employment," Transport Policy, Elsevier, vol. 60(C), pages 1-9.
    13. Daganzo, Carlos F., 2010. "Structure of competitive transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 434-446, May.
    14. Baum-Snow, Nathaniel & Kahn, Matthew E., 2000. "The effects of new public projects to expand urban rail transit," Journal of Public Economics, Elsevier, vol. 77(2), pages 241-263, August.
    15. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    16. Tirachini, Alejandro, 2014. "The economics and engineering of bus stops: Spacing, design and congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 37-57.
    17. Muhammad Ibrahim, 2003. "Car ownership and attitudes towards transport modes for shopping purposes in Singapore," Transportation, Springer, vol. 30(4), pages 435-457, November.
    18. Pueboobpaphan, Rattaphol & Pueboobpaphan, Suthatip & Sukhotra, Suthasinee, 2022. "Acceptable walking distance to transit stations in Bangkok, Thailand: Application of a stated preference technique," Journal of Transport Geography, Elsevier, vol. 99(C).
    19. Jiang, Yang & Christopher Zegras, P. & Mehndiratta, Shomik, 2012. "Walk the line: station context, corridor type and bus rapid transit walk access in Jinan, China," Journal of Transport Geography, Elsevier, vol. 20(1), pages 1-14.
    20. McIntosh, James & Trubka, Roman & Newman, Peter, 2014. "Can value capture work in a car dependent city? Willingness to pay for transit access in Perth, Western Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 320-339.
    21. Bent Flyvbjerg & Nils Bruzelius & Bert van Wee, 2013. "Comparison of Capital Costs per Route-Kilometre in Urban Rail," Papers 1303.6569, arXiv.org.
    22. Alsnih, Rahaf & Hensher, David A., 2003. "The mobility and accessibility expectations of seniors in an aging population," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 903-916, December.
    23. Vukan R. Vuchic & Gordon F. Newell, 1968. "Rapid Transit Interstation Spacings for Minimum Travel Time," Transportation Science, INFORMS, vol. 2(4), pages 303-339, November.
    24. Mulley, Corinne & Ho, Chinh & Ho, Loan & Hensher, David & Rose, John, 2018. "Will bus travellers walk further for a more frequent service? An international study using a stated preference approach," Transport Policy, Elsevier, vol. 69(C), pages 88-97.
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