IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v47y2020i7p1237-1259.html
   My bibliography  Save this article

Optimizing bus stop locations for walking access: Stops-first design of a feeder route to enhance a residential plan

Author

Listed:
  • John HE Taplin
  • Yuchao Sun

Abstract

Feeder buses provide a small but important part of the public transport system by carrying people between residential areas and transport interchanges. A feeder bus to a train station planned in advance will attract new residents of a housing development to use the bus. The bus route can influence the location choice of a buyer concerned about access for children, the elderly or anyone not wishing to drive a car. Our bus route modelling starts with the bus stops – not the route – to be reached from each dwelling by the shortest possible walk. In demand terms, people locating close to bus stops are more likely to use the service than those choosing more distant locations, and the nearby residences have higher values. The stops-first application determines a feeder bus route to enhance an irregular residential plan covering an area of one square kilometre. The planned road and housing lot locations provide the data for calculating the access measure from each dwelling to each potential bus stop, the closest stop being used. A genetic algorithm tests potential bus stops to find demand maximizing locations, the propensity to use the bus being formulated as an exponential (increasing elasticity) function of walking distance. Then a ‘travelling salesman’ genetic algorithm finds the shortest route linking the stops, so that an efficient circuit route is generated for each alternative number of bus stops, ranging from 7 to 11. More stops not only give better access but also increase the route length, so that total accessibility must be assessed against route length. The distribution of walking distances shows most between 150 and 240 metres, with none more than 400 metres. The results indicate that planning policy should require prior design of a bus route to achieve good walking accessibility, so that residents become accustomed to the convenience of using the bus. This study shows that, at the planning stage, estimating a bi-objective model giving a Pareto front between accessibility and route length can reveal a policy compromise that shortens the route with little reduction in expected patronage.

Suggested Citation

  • John HE Taplin & Yuchao Sun, 2020. "Optimizing bus stop locations for walking access: Stops-first design of a feeder route to enhance a residential plan," Environment and Planning B, , vol. 47(7), pages 1237-1259, September.
  • Handle: RePEc:sae:envirb:v:47:y:2020:i:7:p:1237-1259
    DOI: 10.1177/2399808318824108
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2399808318824108
    Download Restriction: no

    File URL: https://libkey.io/10.1177/2399808318824108?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Glaister, Stephen & Graham, Daniel J., 2005. "An evaluation of national road user charging in England," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 632-650.
    2. Attila A. Kovacs & Bruce L. Golden & Richard F. Hartl & Sophie N. Parragh, 2015. "The Generalized Consistent Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 796-816, November.
    3. Daniel Hess, 2012. "Walking to the bus: perceived versus actual walking distance to bus stops for older adults," Transportation, Springer, vol. 39(2), pages 247-266, March.
    4. Ahmed El-Geneidy & Michael Grimsrud & Rania Wasfi & Paul Tétreault & Julien Surprenant-Legault, 2014. "New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas," Transportation, Springer, vol. 41(1), pages 193-210, January.
    5. Xu, Wangtu (Ato) & Li, Yongling & Wang, Hui, 2016. "Transit accessibility for commuters considering the demand elasticities of distance and transfer," Journal of Transport Geography, Elsevier, vol. 56(C), pages 138-156.
    6. Guihaire, Valérie & Hao, Jin-Kao, 2008. "Transit network design and scheduling: A global review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(10), pages 1251-1273, December.
    7. Gutiérrez, Javier & Cardozo, Osvaldo Daniel & García-Palomares, Juan Carlos, 2011. "Transit ridership forecasting at station level: an approach based on distance-decay weighted regression," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1081-1092.
    8. Rizzi, Luis Ignacio & De La Maza, Cristobal, 2017. "The external costs of private versus public road transport in the Metropolitan Area of Santiago, Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 123-140.
    9. 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.
    10. Schittekat, Patrick & Kinable, Joris & Sörensen, Kenneth & Sevaux, Marc & Spieksma, Frits & Springael, Johan, 2013. "A metaheuristic for the school bus routing problem with bus stop selection," European Journal of Operational Research, Elsevier, vol. 229(2), pages 518-528.
    11. Steven I. Chien * & Zhaoqiong Qin, 2004. "Optimization of bus stop locations for improving transit accessibility," Transportation Planning and Technology, Taylor & Francis Journals, vol. 27(3), pages 211-227, June.
    12. Currie, Graham & Wallis, Ian, 2008. "Effective ways to grow urban bus markets – a synthesis of evidence," Journal of Transport Geography, Elsevier, vol. 16(6), pages 419-429.
    13. Ibarra-Rojas, O.J. & Delgado, F. & Giesen, R. & Muñoz, J.C., 2015. "Planning, operation, and control of bus transport systems: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 38-75.
    14. Alexander Erath & Michael Löchl & Kay Axhausen, 2009. "Graph-Theoretical Analysis of the Swiss Road and Railway Networks Over Time," Networks and Spatial Economics, Springer, vol. 9(3), pages 379-400, September.
    15. Park, Junhyuk & Kim, Byung-In, 2010. "The school bus routing problem: A review," European Journal of Operational Research, Elsevier, vol. 202(2), pages 311-319, April.
    16. Ceder, Avishai & Wilson, Nigel H. M., 1986. "Bus network design," Transportation Research Part B: Methodological, Elsevier, vol. 20(4), pages 331-344, August.
    17. Ceder, Avishai (Avi) & Butcher, Matthew & Wang, Lingli, 2015. "Optimization of bus stop placement for routes on uneven topography," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 40-61.
    18. John Zacharias & Qi Zhao, 2018. "Local environmental factors in walking distance at metro stations," Public Transport, Springer, vol. 10(1), pages 91-106, May.
    19. Banister, David, 2008. "The sustainable mobility paradigm," Transport Policy, Elsevier, vol. 15(2), pages 73-80, March.
    20. Qiu, Min, 1997. "Prioritising and scheduling road projects by genetic algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 569-574.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sajjakaj Jomnonkwao & Chinnakrit Banyong & Supanida Nanthawong & Thananya Janhuaton & Vatanavongs Ratanavaraha & Thanapong Champahom & Pornsiri Jongkol, 2022. "Perceptions of Parents of the Quality of the Public Transport Services Used by Children to Commute to School," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    2. Xinhua Gao & Song Liu & Shan Jiang & Dennis Yu & Yong Peng & Xianting Ma & Wenting Lin, 2024. "Optimizing the Three-Dimensional Multi-Objective of Feeder Bus Routes Considering the Timetable," Mathematics, MDPI, vol. 12(7), pages 1-27, March.
    3. Yi Cao & Dandan Jiang & Shan Wang, 2022. "Optimization for Feeder Bus Route Model Design with Station Transfer," Sustainability, MDPI, vol. 14(5), pages 1-15, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Proboste, Francisco & Muñoz, Juan Carlos & Gschwender, Antonio, 2020. "Comparing social costs of public transport networks structured around an Open and Closed BRT corridor in medium sized cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 187-212.
    2. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
    3. Manser, Patrick & Becker, Henrik & Hörl, Sebastian & Axhausen, Kay W., 2020. "Designing a large-scale public transport network using agent-based microsimulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 1-15.
    4. Luo, Sida & Nie, Yu (Marco), 2020. "Paired-line hybrid transit design considering spatial heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 320-339.
    5. Benjamin Otto, 2019. "Aggregation techniques for frequency assignment in public transportation," Public Transport, Springer, vol. 11(1), pages 51-87, June.
    6. 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).
    7. David Schmaranzer & Roland Braune & Karl F. Doerner, 2021. "Multi-objective simulation optimization for complex urban mass rapid transit systems," Annals of Operations Research, Springer, vol. 305(1), pages 449-486, October.
    8. Sunhyung Yoo & Jinwoo Brian Lee & Hoon Han, 2023. "A Reinforcement Learning approach for bus network design and frequency setting optimisation," Public Transport, Springer, vol. 15(2), pages 503-534, June.
    9. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.
    10. Evert Vermeir & Javier Durán-Micco & Pieter Vansteenwegen, 2022. "The grid based approach, a fast local evaluation technique for line planning," 4OR, Springer, vol. 20(4), pages 603-635, December.
    11. Ahmed, Leena & Mumford, Christine & Kheiri, Ahmed, 2019. "Solving urban transit route design problem using selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 274(2), pages 545-559.
    12. Prasanta K. Sahu & Babak Mehran & Surya P. Mahapatra & Satish Sharma, 2021. "Spatial data analysis approach for network-wide consolidation of bus stop locations," Public Transport, Springer, vol. 13(2), pages 375-394, June.
    13. Javier Durán-Micco & Pieter Vansteenwegen, 2022. "A survey on the transit network design and frequency setting problem," Public Transport, Springer, vol. 14(1), pages 155-190, March.
    14. Yuji Shi & Simon Blainey & Nick Hounsell, 2017. "Using GIS to assess the potential for centralised planning of bus networks," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(1), pages 119-142, January.
    15. MELIS, Lissa & SÖRENSEN, Kenneth, 2020. "The on-demand bus routing problem: A large neighborhood search heuristic for a dial-a-ride problem with bus station assignment," Working Papers 2020005, University of Antwerp, Faculty of Business and Economics.
    16. Loder, Allister & Bliemer, Michiel C.J. & Axhausen, Kay W., 2022. "Optimal pricing and investment in a multi-modal city — Introducing a macroscopic network design problem based on the MFD," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 113-132.
    17. David Schmaranzer & Roland Braune & Karl F. Doerner, 2020. "Population-based simulation optimization for urban mass rapid transit networks," Flexible Services and Manufacturing Journal, Springer, vol. 32(4), pages 767-805, December.
    18. Andrés Fielbaum & Sergio Jara-Diaz & Antonio Gschwender, 2017. "A Parametric Description of Cities for the Normative Analysis of Transport Systems," Networks and Spatial Economics, Springer, vol. 17(2), pages 343-365, June.
    19. Arbex, Renato Oliveira & da Cunha, Claudio Barbieri, 2015. "Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 355-376.
    20. Liwei Zeng & Sunil Chopra & Karen Smilowitz, 2019. "The Covering Path Problem on a Grid," Transportation Science, INFORMS, vol. 53(6), pages 1656-1672, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envirb:v:47:y:2020:i:7:p:1237-1259. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.