IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i16p10172-d889638.html
   My bibliography  Save this article

Dimensioning of Cycle Lanes Based on the Assessment of Comfort for Cyclists

Author

Listed:
  • Darja Šemrov

    (Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova Cesta 2, 1000 Ljubljana, Slovenia)

  • Robert Rijavec

    (Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova Cesta 2, 1000 Ljubljana, Slovenia)

  • Peter Lipar

    (Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova Cesta 2, 1000 Ljubljana, Slovenia)

Abstract

In a century where mobility is becoming more sustainable in terms of energy transition, emissions reduction, and a healthy quality of life, the use of bicycles is increasing and has many advantages over other modes of transport that have been underused. The bicycle is an excellent alternative for short distances of up to five kilometers. In combination with public transportation, it can also successfully compete with motorized transport for longer distances. For the adequate development of cycling, it is necessary to create the right conditions in terms of accessibility and road safety. This means planning appropriate cycling infrastructure where cyclists feel comfortable and safe, which can lead to additional increased use in bicycles for everyday trips. Comfort for cyclists is a concept supported by road safety, a pleasant environment, connectivity, and the attractiveness of cycling infrastructure. In other words, cyclists respond to the physical, psychological, and sociological aspects of the cycling experience that are also related to the cycling infrastructure and environment: where I am, what I see and perceive, and how I feel. This paper presents the concept of the level of service for cyclists (BLOS) as a unified method for defining the comfort of cyclists. This paper presents the method for determining the level of service or comfort for bicyclists as a function of road width, width of the cycling area, traffic volume, and the speed and structure of motorized traffic flow. The result of BLOS, the mathematical model used, is graphically presented and allows decision-makers and designers of cycling infrastructure to easily assess the suitability of cycling infrastructure. Different diagrams for different input data are presented in the paper.

Suggested Citation

  • Darja Šemrov & Robert Rijavec & Peter Lipar, 2022. "Dimensioning of Cycle Lanes Based on the Assessment of Comfort for Cyclists," Sustainability, MDPI, vol. 14(16), pages 1-12, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10172-:d:889638
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/16/10172/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/16/10172/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mora, Rodrigo & Truffello, Ricardo & Oyarzún, Gabriel, 2021. "Equity and accessibility of cycling infrastructure: An analysis of Santiago de Chile," Journal of Transport Geography, Elsevier, vol. 91(C).
    2. Ana María Pérez-Zuriaga & Sara Moll & Griselda López & Alfredo García, 2021. "Driver Behavior When Overtaking Cyclists Riding in Different Group Configurations on Two-Lane Rural Roads," IJERPH, MDPI, vol. 18(23), pages 1-18, December.
    3. 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.
    4. Ipek Sener & Naveen Eluru & Chandra Bhat, 2009. "An analysis of bicycle route choice preferences in Texas, US," Transportation, Springer, vol. 36(5), pages 511-539, September.
    5. Rossetti, Tomás & Guevara, C. Angelo & Galilea, Patricia & Hurtubia, Ricardo, 2018. "Modeling safety as a perceptual latent variable to assess cycling infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 252-265.
    6. Michael Hardinghaus & Panagiotis Papantoniou, 2020. "Evaluating Cyclists’ Route Preferences with Respect to Infrastructure," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
    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. Sebastian Seriani & Vicente Perez & Vicente Aprigliano & Taku Fujiyama, 2022. "Experimental Study of Cyclist’ Sensitivity When They Are Overtaken by a Motor Vehicle: A Pilot Study in a Street without Cycle Lanes," Sustainability, MDPI, vol. 14(24), pages 1-20, December.

    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. 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).
    2. Stefan Flügel & Nina Hulleberg & Aslak Fyhri & Christian Weber & Gretar Ævarsson, 2019. "Empirical speed models for cycling in the Oslo road network," Transportation, Springer, vol. 46(4), pages 1395-1419, August.
    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. Rupi, Federico & Freo, Marzia & Poliziani, Cristian & Postorino, Maria Nadia & Schweizer, Joerg, 2023. "Analysis of gender-specific bicycle route choices using revealed preference surveys based on GPS traces," Transport Policy, Elsevier, vol. 133(C), pages 1-14.
    5. Yeran Sun & Amin Mobasheri, 2017. "Utilizing Crowdsourced Data for Studies of Cycling and Air Pollution Exposure: A Case Study Using Strava Data," IJERPH, MDPI, vol. 14(3), pages 1-19, March.
    6. Meister, Adrian & Felder, Matteo & Schmid, Basil & Axhausen, Kay W., 2023. "Route choice modeling for cyclists on urban networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    7. Liu, Yanan & Yang, Dujuan & Timmermans, Harry J.P. & de Vries, Bauke, 2020. "Analysis of the impact of street-scale built environment design near metro stations on pedestrian and cyclist road segment choice: A stated choice experiment," Journal of Transport Geography, Elsevier, vol. 82(C).
    8. 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.
    9. Lixuan Zhao & Dewei Fang & Yang Cao & Shan Sun & Liu Han & Yang Xue & Qian Zheng, 2023. "Impact-Asymmetric Analysis of Bike-Sharing Residents’ Satisfaction: A Case Study of Harbin, China," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    10. Ralph Buehler & Jennifer Dill, 2016. "Bikeway Networks: A Review of Effects on Cycling," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 9-27, January.
    11. George Liu & Samuel Nello‐Deakin & Marco te Brömmelstroet & Yuki Yamamoto, 2020. "What Makes a Good Cargo Bike Route? Perspectives from Users and Planners," American Journal of Economics and Sociology, Wiley Blackwell, vol. 79(3), pages 941-965, May.
    12. Fitch, Dillon T. & Handy, Susan L., 2020. "Road environments and bicyclist route choice: The cases of Davis and San Francisco, CA," Journal of Transport Geography, Elsevier, vol. 85(C).
    13. Faghih Imani, Ahmadreza & Miller, Eric J. & Saxe, Shoshanna, 2019. "Cycle accessibility and level of traffic stress: A case study of Toronto," Journal of Transport Geography, Elsevier, vol. 80(C).
    14. 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.
    15. Yan Wang & Yibin Ao & Yuting Zhang & Yan Liu & Lei Zhao & Yunfeng Chen, 2019. "Impact of the Built Environment and Bicycling Psychological Factors on the Acceptable Bicycling Distance of Rural Residents," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    16. Alexander Bigazzi & Robin Lindsey, 2019. "A utility-based bicycle speed choice model with time and energy factors," Transportation, Springer, vol. 46(3), pages 995-1009, June.
    17. Bhat, Chandra R. & Dubey, Subodh K. & Nagel, Kai, 2015. "Introducing non-normality of latent psychological constructs in choice modeling with an application to bicyclist route choice," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 341-363.
    18. 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.
    19. Michael Hardinghaus & Simon Nieland & Marius Lehne & Jan Weschke, 2021. "More than Bike Lanes—A Multifactorial Index of Urban Bikeability," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    20. 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.

    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:gam:jsusta:v:14:y:2022:i:16:p:10172-:d:889638. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.