IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v134y2020icp164-183.html
   My bibliography  Save this article

Development of a large-scale transport model with focus on cycling

Author

Listed:
  • Liu, Chengxi
  • Tapani, Andreas
  • Kristoffersson, Ida
  • Rydergren, Clas
  • Jonsson, Daniel

Abstract

This study presents a transport model to better model cycling demand. The model improves modelling of cycling in several ways compared to a conventional transport model. First, it uses a detailed bicycle network containing information about existing bicycle infrastructure. Second, generalised cost measures based on different bicycle route choice models are calculated and compared to evaluate how to best represent the impact of bicycle infrastructure in the model. Third, the model utilizes a refined zone system with smaller zones of size 250 m × 250 m. Using these smaller zones, more short-distance tours are included in the model, and these are predominantly walking and cycling trips. Fourth, the model considers cycling also as an access mode choice to public transport. Therefore, the model treats cycling and public transport as both competing and complementary modes.

Suggested Citation

  • Liu, Chengxi & Tapani, Andreas & Kristoffersson, Ida & Rydergren, Clas & Jonsson, Daniel, 2020. "Development of a large-scale transport model with focus on cycling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 164-183.
    • Handle: RePEc:eee:transa:v:134:y:2020:i:c:p:164-183
    DOI: 10.1016/j.tra.2020.02.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096585641930374X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2020.02.010?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Menghini, G. & Carrasco, N. & Schüssler, N. & Axhausen, K.W., 2010. "Route choice of cyclists in Zurich," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 754-765, November.
    2. J. Hunt & J. Abraham, 2007. "Influences on bicycle use," Transportation, Springer, vol. 34(4), pages 453-470, July.
    3. Ralph Buehler & John Pucher, 2012. "Cycling to work in 90 large American cities: new evidence on the role of bike paths and lanes," Transportation, Springer, vol. 39(2), pages 409-432, March.
    4. Broach, Joseph & Dill, Jennifer & Gliebe, John, 2012. "Where do cyclists ride? A route choice model developed with revealed preference GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1730-1740.
    5. Kristoffersson, Ida & Daly, Andrew & Algers, Staffan, 2018. "Modelling the attraction of travel to shopping destinations in large-scale modelling," Transport Policy, Elsevier, vol. 68(C), pages 52-62.
    6. Álvaro Fernández-Heredia & Sergio Jara-Díaz & Andrés Monzón, 2016. "Modelling bicycle use intention: the role of perceptions," Transportation, Springer, vol. 43(1), pages 1-23, January.
    7. Álvaro Fernández-Heredia & Sergio Jara-Díaz & Andrés Monzón, 2016. "Modelling bicycle use intention: the role of perceptions," Transportation, Springer, vol. 43(1), pages 1-23, January.
    8. Cooper, Crispin H.V., 2017. "Using spatial network analysis to model pedal cycle flows, risk and mode choice," Journal of Transport Geography, Elsevier, vol. 58(C), pages 157-165.
    9. Wang, Haizhong & Palm, Matthew & Chen, Chen & Vogt, Rachel & Wang, Yiyi, 2016. "Does bicycle network level of traffic stress (LTS) explain bicycle travel behavior? Mixed results from an Oregon case study," Journal of Transport Geography, Elsevier, vol. 57(C), pages 8-18.
    10. Chatterjee, Kiron & Sherwin, Henrietta & Jain, Juliet, 2013. "Triggers for changes in cycling: the role of life events and modifications to the external environment," Journal of Transport Geography, Elsevier, vol. 30(C), pages 183-193.
    11. Börjesson, Maria & Eliasson, Jonas, 2012. "The value of time and external benefits in bicycle appraisal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 673-683.
    12. Daly, Andrew, 1982. "Estimating choice models containing attraction variables," Transportation Research Part B: Methodological, Elsevier, vol. 16(1), pages 5-15, February.
    13. Eva Heinen & Bert van Wee & Kees Maat, 2009. "Commuting by Bicycle: An Overview of the Literature," Transport Reviews, Taylor & Francis Journals, vol. 30(1), pages 59-96, June.
    14. Elliot Fishman, 2016. "Cycling as transport," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 1-8, January.
    15. Begoña Muñoz & Andres Monzon & Ricardo A. Daziano, 2016. "The Increasing Role of Latent Variables in Modelling Bicycle Mode Choice," Transport Reviews, Taylor & Francis Journals, vol. 36(6), pages 737-771, November.
    16. Ton, Danique & Duives, Dorine C. & Cats, Oded & Hoogendoorn-Lanser, Sascha & Hoogendoorn, Serge P., 2019. "Cycling or walking? Determinants of mode choice in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 123(C), pages 7-23.
    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. Elisa Conticelli & Gianluca Gobbi & Paula Isabella Saavedra Rosas & Simona Tondelli, 2021. "Assessing the Performance of Modal Interchange for Ensuring Seamless and Sustainable Mobility in European Cities," Sustainability, MDPI, vol. 13(2), pages 1-24, January.
    2. Bialkova, Svetlana & Ettema, Dick & Dijst, Martin, 2022. "How do design aspects influence the attractiveness of cycling streetscapes: Results of virtual reality experiments in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 315-331.

    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. Yeran Sun & Yunyan Du & Yu Wang & Liyuan Zhuang, 2017. "Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data," IJERPH, MDPI, vol. 14(6), pages 1-12, June.
    2. Márquez, Luis & Soto, Jose J., 2021. "Integrating perceptions of safety and bicycle theft risk in the analysis of cycling infrastructure preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 285-301.
    3. Anowar, Sabreena & Eluru, Naveen & Hatzopoulou, Marianne, 2017. "Quantifying the value of a clean ride: How far would you bicycle to avoid exposure to traffic-related air pollution?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 66-78.
    4. Paulsen, Mads & Rich, Jeppe, 2023. "Societally optimal expansion of bicycle networks," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    5. McArthur, David Philip & Hong, Jinhyun, 2019. "Visualising where commuting cyclists travel using crowdsourced data," Journal of Transport Geography, Elsevier, vol. 74(C), pages 233-241.
    6. Scorrano, Mariangela & Danielis, Romeo, 2021. "Active mobility in an Italian city: Mode choice determinants and attitudes before and during the Covid-19 emergency," Research in Transportation Economics, Elsevier, vol. 86(C).
    7. Mahdi Rashidi & Seyed-Mohammad Seyedhosseini & Ali Naderan, 2023. "Defining Psychological Factors of Cycling in Tehran City," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
    8. Felipe González & Carlos Melo-Riquelme & Louis Grange, 2016. "A combined destination and route choice model for a bicycle sharing system," Transportation, Springer, vol. 43(3), pages 407-423, May.
    9. Ruiz, Tomás & Bernabé, José C., 2014. "Measuring factors influencing valuation of nonmotorized improvement measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 195-211.
    10. Scott, Darren M. & Lu, Wei & Brown, Matthew J., 2021. "Route choice of bike share users: Leveraging GPS data to derive choice sets," Journal of Transport Geography, Elsevier, vol. 90(C).
    11. Seungkyu Ryu, 2020. "A Bicycle Origin–Destination Matrix Estimation Based on a Two-Stage Procedure," Sustainability, MDPI, vol. 12(7), pages 1-14, April.
    12. Hallberg, Martin & Rasmussen, Thomas Kjær & Rich, Jeppe, 2021. "Modelling the impact of cycle superhighways and electric bicycles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 397-418.
    13. Bram Boettge & Damon M. Hall & Thomas Crawford, 2017. "Assessing the Bicycle Network in St. Louis: A PlaceBased User-Centered Approach," Sustainability, MDPI, vol. 9(2), pages 1-18, February.
    14. Tomás Rossetti & Verónica Saud & Ricardo Hurtubia, 2019. "I want to ride it where I like: measuring design preferences in cycling infrastructure," Transportation, Springer, vol. 46(3), pages 697-718, June.
    15. Lu, Wei & Scott, Darren M. & Dalumpines, Ron, 2018. "Understanding bike share cyclist route choice using GPS data: Comparing dominant routes and shortest paths," Journal of Transport Geography, Elsevier, vol. 71(C), pages 172-181.
    16. Teixeira, Inaian Pignatti & Rodrigues da Silva, Antônio Nélson & Schwanen, Tim & Manzato, Gustavo Garcia & Dörrzapf, Linda & Zeile, Peter & Dekoninck, Luc & Botteldooren, Dick, 2020. "Does cycling infrastructure reduce stress biomarkers in commuting cyclists? A comparison of five European cities," Journal of Transport Geography, Elsevier, vol. 88(C).
    17. Milakis, Dimitris & Athanasopoulos, Konstantinos, 2014. "What about people in cycle network planning? applying participative multicriteria GIS analysis in the case of the Athens metropolitan cycle network," Journal of Transport Geography, Elsevier, vol. 35(C), pages 120-129.
    18. Damant-Sirois, Gabriel & El-Geneidy, Ahmed M., 2015. "Who cycles more? Determining cycling frequency through a segmentation approach in Montreal, Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 113-125.
    19. Chen, Chen & Wang, Haizhong & Roll, Josh & Nordback, Krista & Wang, Yinhai, 2020. "Using bicycle app data to develop Safety Performance Functions (SPFs) for bicyclists at intersections: A generic framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 1034-1052.
    20. Michał Adam Kwiatkowski & Elżbieta Grzelak-Kostulska & Jadwiga Biegańska, 2021. "Could It Be a Bike for Everyone? The Electric Bicycle in Poland," Energies, MDPI, vol. 14(16), pages 1-19, August.

    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:eee:transa:v:134:y:2020:i:c:p:164-183. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.