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A GIS-based planning approach to locating urban rail terminals

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  • Mark Horner
  • Tony Grubesic

Abstract

This paper develops a flexible GIS-based methodology for evaluating the potential locations of terminal park-and-ride facilities along urban rail lines. The methodology differs from political-based approaches and traditional travel demand modeling in its use of an objective measure of accessibility to gage the suitability of a site. The methodology begins by constructing an index of derived demand for rail usage based on the local demographics. Principal component analysis (PCA) is used as a means of constructing an index of derived demand consistent with other passenger surveys. Next, trade areas or commutersheds are calculated for each candidate park-and-ride location based on realistic measures of accessibility and network based drive times, taking into account competition among candidates for riders. Following the analysis, the candidate locations and their commutersheds are delineated and visualized in the GIS environment. In summary, application of this method produces a site-specific suitability index that may be used to rank and compare potential park-and-ride locations. We illustrate how our approach fits within the context of the larger-scale corridor study as a complimentary means of refining the location of urban rail stations. The analysis uses the proposed rail system for Columbus Ohio as a case study. Copyright Kluwer Academic Publishers 2001

Suggested Citation

  • Mark Horner & Tony Grubesic, 2001. "A GIS-based planning approach to locating urban rail terminals," Transportation, Springer, vol. 28(1), pages 55-77, February.
    • Handle: RePEc:kap:transp:v:28:y:2001:i:1:p:55-77
    DOI: 10.1023/A:1005204010958
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    Citations

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    Cited by:

    1. Du, Bo & Wang, David Z.W., 2014. "Continuum modeling of park-and-ride services considering travel time reliability and heterogeneous commuters – A linear complementarity system approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 58-81.
    2. Gao, Ge & Sun, Huijun & Wu, Jianjun & Liu, Xinmin & Chen, Weiya, 2018. "Park-and-ride service design under a price-based tradable credits scheme in a linear monocentric city," Transport Policy, Elsevier, vol. 68(C), pages 1-12.
    3. Zhao, Xinwei & Chen, Peng & Jiao, Junfeng & Chen, Xiaohong & Bischak, Chris, 2019. "How does ‘park and ride’ perform? An evaluation using longitudinal data," Transport Policy, Elsevier, vol. 74(C), pages 15-23.
    4. Changshan Wu & Alan T Murray, 2005. "Optimizing Public Transit Quality and System Access: The Multiple-Route, Maximal Covering/Shortest-Path Problem," Environment and Planning B, , vol. 32(2), pages 163-178, April.
    5. Amir Khakbaz & Ali Nookabadi & S. Shetab-bushehri, 2013. "A Model for Locating Park-and-Ride Facilities on Urban Networks Based on Maximizing Flow Capture: A Case Study of Isfahan, Iran," Networks and Spatial Economics, Springer, vol. 13(1), pages 43-66, March.
    6. Holguı´n-Veras, José & Yushimito, Wilfredo F. & Aros-Vera, Felipe & Reilly, John (Jack), 2012. "User rationality and optimal park-and-ride location under potential demand maximization," Transportation Research Part B: Methodological, Elsevier, vol. 46(8), pages 949-970.
    7. Horner, Mark W. & Groves, Sara, 2007. "Network flow-based strategies for identifying rail park-and-ride facility locations," Socio-Economic Planning Sciences, Elsevier, vol. 41(3), pages 255-268, September.
    8. Wang, Judith Y. T. & Yang, Hai & Lindsey, Robin, 2004. "Locating and pricing park-and-ride facilities in a linear monocentric city with deterministic mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 38(8), pages 709-731, September.
    9. Kimpton, Anthony & Pojani, Dorina & Sipe, Neil & Corcoran, Jonathan, 2020. "Parking Behavior: Park ‘n’ Ride (PnR) to encourage multimodalism in Brisbane," Land Use Policy, Elsevier, vol. 91(C).
    10. Israel, Emil & Cohen-Blankshtain, Galit, 2010. "Testing the decentralization effects of rail systems: Empirical findings from Israel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(7), pages 523-536, August.
    11. Yu Shen & Jinhua Zhao, 2017. "Capacity constrained accessibility of high-speed rail," Transportation, Springer, vol. 44(2), pages 395-422, March.
    12. Blainey, Simon P. & Preston, John M., 2013. "A GIS-based appraisal framework for new local railway stations and services," Transport Policy, Elsevier, vol. 25(C), pages 41-51.
    13. Samanta, Sutapa & Jha, Manoj K., 2011. "Modeling a rail transit alignment considering different objectives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 31-45, January.
    14. Guillot, Matthieu & Rey, David & Furno, Angelo & El Faouzi, Nour-Eddin, 2024. "A stochastic hub location and fleet assignment problem for the design of reconfigurable park-and-ride systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    15. L. Zhang & Y. P. Wang & J. Sun & B. Yu, 2019. "The sightseeing bus schedule optimization under Park and Ride System in tourist attractions," Annals of Operations Research, Springer, vol. 273(1), pages 587-605, February.
    16. Zhou, Yirong & Liu, Xiaoyue Cathy & Grubesic, Tony, 2021. "Unravel the impact of COVID-19 on the spatio-temporal mobility patterns of microtransit," Journal of Transport Geography, Elsevier, vol. 97(C).
    17. Mark W Horner & Alan T Murray, 2004. "Spatial Representation and Scale Impacts in Transit Service Assessment," Environment and Planning B, , vol. 31(5), pages 785-797, October.
    18. Yusuke Kono & Kenetsu Uchida & Katia Andrade, 2014. "Economical welfare maximisation analysis: assessing the use of existing Park-and-Ride services," Transportation, Springer, vol. 41(4), pages 839-854, July.

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