Skip to main content
SpringerLink
Log in

Cycling Analytics for Urban Environments: From Vertical Models to Horizontal Innovation

  • Conference paper
  • First Online:
Intelligent Transport Systems (INTSYS 2021)

Included in the following conference series:

Abstract

The full potential of Intelligent Transport Systems (ITS) can only be achieved by combining the efforts and the knowledge of multiple entities. This is also true for the current efforts towards the application of data, communications and services to improve cycling and its integration into general mobility systems. The currently prevailing paradigm is based on dispersed and self-contained custom processes, which fail to promote distributed and open innovation. These models are hard to reproduce, generalize, recombine or improve outside the context for which they were originally implemented. A digital platform strategy might offer a viable and scalable way to support convergence between multiple models and promote their usage as shared references for cycling ecosystems. In this work, we aim to validate our assumptions about the limitations of current development paradigms and analyse the extent to which a platform strategy could offer a fundamentally different approach to address those limitations. To validate the problem and uncover generalisation opportunities, we study 3 cycling mobility models and make an initial analysis of how the general principles of digital platforms could offer an alternative solution for cycling analytics. The results confirm a high potential for horizontal features and outline a set of key design principles for the development of a digital platform strategy for cycling analytics. This should constitute a contribution to inform the development of a new generation of cycling platforms for urban environments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Bulc, V.: Cycling: green and efficient transport for the future, European Commission. (2016). https://ec.europa.eu/commission/commissioners/2014-2019/bulc/blog/cycling-green-and-efficient-transport-future_en. Accessed 31 Oct 2019

  2. Fishman, E., Washington, S., Haworth, N.: Bike share: a synthesis of the literature. Transp. Rev. 33(2) (2013)

    Google Scholar 

  3. Neves, A., Brand, C.: Assessing the potential for carbon emissions savings from replacing short car trips with walking and cycling using a mixed GPS-travel diary approach. Trans. Res. Part A: Policy Pract. 123, 130–146 (2019)

    Google Scholar 

  4. Oja, P., et al.: Health benefits of cycling: a systematic review. Scand. J. Med. Sci. Sports 21(4), 496–509 (2011)

    Article  Google Scholar 

  5. Penedo, F.J., Dahn, J.R.: Exercise and well-being: a review of mental and physical health benefits associated with physical activity. Curr. Opin. Psychiat. 18(2), 189–193 (2005)

    Article  Google Scholar 

  6. Blondiau, T., van Zeebroeck, B., Haubold, H.: Economic benefits of increased cycling. In: Transportation Research Procedia. pp. 2306–2313 (2016)

    Google Scholar 

  7. Arancibia, D., Savan, B., Ledsham, T., Bennington, M.: Economic impacts of cycling in dense urban areas: literature review. In: Transportation Research Board 94th Annual Meeting (2015)

    Google Scholar 

  8. Stratta, P.: Towards a Smarter Cycling. On the brink of a Smart (R)evolution, European Cyclists’ Federation. https://ecf.com/what-we-do/cycling-new-technologies/towards-smarter-cycling, Accessed 30 June 2020

  9. Gholamialam, A., Matisziw, T.C.: Modeling bikeability of urban systems. Geogr. Anal. 51(2), 73–89 (2019)

    Article  Google Scholar 

  10. Grigore, E., Garrick, N., Fuhrer, R., Axhausen, I.K.W.: Bikeability in basel. Trans. Res. Record J. Trans. Res. Board. 2673(6), 607–617 (2019)

    Google Scholar 

  11. de Matos, F.L., Fernandes, J.M., Sampaio, C., Macedo, J., Coelho, M.C., Bandeira, J.: Development of an information system for cycling navigation. Trans. Res. Procedia. 52(2020), 107–114 (2021)

    Article  Google Scholar 

  12. Copenhagenize: 2019 Copenhagenize Index - Copenhagenize, Copenhagenize index. https://copenhagenizeindex.eu/, Accessed 28 July 2020 (2019)

  13. WalkScore: Bike Score Methodology. https://www.walkscore.com/bike-score-methodology.shtml. Accessed 18 May 2021 (2018)

  14. Figueiredo, A.P. e Vale, D.S.: BikeFriendlyIndex – Um indíce para avaliação da amigabilidade de um concelho para a utilização da bicicleta enquanto modo de transporte urbano. www.bikefriendlyindex.com (2018)

  15. PCT.BIKE: Welcome to the Propensity to Cycle Tool (PCT). https://www.pct.bike/. Accessed May 04 2021

  16. Silva, C., S. Marques, J., Lopes, M., M. Dias, A.: The gross potential for cycling: planning for human scale urban mobility. In: Mladenović, M.N., Toivonen, T., Willberg, E., Geurs, K.T. (eds.) Transport in Human Scale Cities. pp. 157–168. Edward Elgar Publishing, United Kingdom (2021)

    Google Scholar 

  17. Ferreira, J.P., Isidoro, C., Moura Sá, F., Baptista Da Mota, J.C.: The economic value for cycling – a methodological assessment for Starter Cities. Hábitat y Sociedad. 13, (2020)https://doi.org/10.12795/HabitatySociedad.2020.i13.03

  18. Lee, K., Sener, I.N.: Strava Metro data for bicycle monitoring: a literature review. Transp. Rev. 41(1), 27–47 (2021)

    Article  Google Scholar 

  19. U-Shift lab: Declives-RedeViaria. https://github.com/U-Shift/Declives-RedeViaria. Accessed 28 May 2021 (2020)

  20. Tran, P.T.M., Zhao, M., Yamamoto, K., Minet, L., Nguyen, T., Balasubramanian, R.: Cyclists’ personal exposure to traffic-related air pollution and its influence on bikeability. Transp. Res. Part D Transp. Environ. 88, 102563 (2020). https://doi.org/10.1016/j.trd.2020.102563

    Article  Google Scholar 

  21. Alattar, M.A., Cottrill, C., Beecroft, M.: Modelling cyclists’ route choice using Strava and OSMnx: A case study of the city of Glasgow. Trans. Res. Inter. Persp. 9 (March), 100301 (2021)

    Google Scholar 

  22. Berger, M., Dörrzapf, L.: Sensing comfort in bicycling in addition to travel data. Trans. Res. Proc. 32, 524–534 (2018)

    Google Scholar 

  23. David Vale: Calculate accessibility from an OD matrix on python (version 2.0). https://github.com/davidsvale/calculate-accessibility. Accessed 24 June 2021 (2020)

  24. Ciriello, R.F., Richter, A., Schwabe, G.: Digital innovation. Bus. Inf. Syst. Eng. 60(6), 563–569 (2018). https://doi.org/10.1007/s12599-018-0559-8

    Article  Google Scholar 

  25. Zittrain, J.L.: The generative Internet (2006)

    Google Scholar 

  26. Lovelace, R., Goodman, A., Aldred, R., Berkoff, N., Abbas, A., Woodcock, J.: The propensity to cycle tool: An open source online system for sustainable transport planning. J. Trans. Land Use. 10(1), 505–528 (2017)

    Google Scholar 

  27. Porter, A.K., Kohl, H.W., Pérez, A., Reininger, B., Pettee Gabriel, K., Salvo, D.: Bikeability: assessing the objectively measured environment in relation to recreation and transportation bicycling. Environ. Behav. 52(8), 861–894 (2020)

    Article  Google Scholar 

  28. Kamel, M.B., Sayed, T., Bigazzi, A.: A composite zonal index for biking attractiveness and safety. Accid. Anal. Prevent. 137(October 2019), 105439 (2020)

    Google Scholar 

  29. Saghapour, T., Moridpour, S., Thompson, R.G.: Measuring cycling accessibility in metropolitan areas. Int. J. Sustain. Transp. (2017)

    Google Scholar 

  30. Lowry, M., Callister, D., Gresham, M., Moore, B.: Assessment of communitywide bikeability with bicycle level of service. Transp. Res. Rec. 2314(2314), 41–48 (2012)

    Article  Google Scholar 

  31. Gu, P., Han, Z., Cao, Z., Chen, Y., Jiang, Y.: Using open source data to measure street walkability and bikeability in China: a case of four cities. Transp. Res. Rec. 2672(31), 63–75 (2018)

    Article  Google Scholar 

  32. Schmid-Querg, J., Keler, A., Grigoropoulos, G.: The munich bikeability index: A practical approach for measuring urban bikeability. Sustainability 13(1), 428 (2021). https://doi.org/10.3390/su13010428

    Article  Google Scholar 

  33. Lin, J.J., Wei, Y.H.: Assessing area-wide bikeability: a grey analytic network process. Transp. Res. Part A: Policy Pract. 113(1), 381–396 (2018)

    Google Scholar 

  34. Arellana, J., Saltarín, M., Larrañaga, A.M., González, V.I., Henao, C.A.: Developing an urban bikeability index for different types of cyclists as a tool to prioritise bicycle infrastructure investments. Trans. Res. Part A Policy Pract. 139, 310–334 (2020)

    Article  Google Scholar 

  35. Tran, P.T.M., Zhao, M., Yamamoto, K., Minet, L., Nguyen, T., Balasubramanian, R.: Cyclists’ personal exposure to traffic-related air pollution and its influence on bikeability. Trans. Res. Part D Trans. Environ. 88 (November), 102563 (2020)

    Google Scholar 

  36. Resch, B., Puetz, I., Bluemke, M., Kyriakou, K., Miksch, J.: An interdisciplinary mixed-methods approach to analyzing urban spaces: the case of urban walkability and bikeability. Int. J. Environ. Res. Public Health 17(19), 6994 (2020). https://doi.org/10.3390/ijerph17196994

    Article  Google Scholar 

  37. Walk Score: Bike Score Methodology. https://www.walkscore.com/bike-score-methodology.shtml. Accessed 10 May, 2021 (2018)

  38. Coya: Global Bicycle Cities Index 2019 | Coya. https://www.coya.com/bike/index-2019. Accessed 18 May 2021 (2019)

  39. Krenn, P.J., Oja, P., Titze, S.: Development of a bikeability index to assess the bicycle-friendliness of urban environments. Open J. Civil Eng. 05(04), 451–459 (2015)

    Article  Google Scholar 

  40. KAPPO: Ciclistas - KAPPO Bike. https://www.kappo.bike/web/app.php. Accessed 05 May 2021

  41. Bike Citizens: The GPS cycling data analysis tool - for evidence based transport planning. https://cyclingdata.net/. Accessed 18 May 2021 (2017)

  42. Hevner, M., Park, R.: Design science in information systems research. MIS Quart. 28(1), 75–105 (2004)

    Article  Google Scholar 

  43. Peffers, K., et al.: Design science research process: a model for producing and presenting information systems research. ArXiv (2020)

    Google Scholar 

  44. Jittrapirom, P., Caiati, V., Feneri, A.-M., Ebrahimigharehbaghi, S., Alonso-González, M.J., Narayan, J.: Mobility as a service: a critical review of definitions, assessments of schemes, and key challenges. Urban Planning. 2(2), 13–25 (2017)

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by: European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039334; Funding Reference: POCI-01-0247-FEDER-039334].

Author information

Authors and Affiliations

  1. Algoritmi Research Centre, University of Minho, Braga, Portugal

    Carlos Carvalho & Rui José

  2. Bosch Car Multimedia, Braga, Portugal

    Ricardo Pessoa

Authors
  1. Carlos Carvalho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ricardo Pessoa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rui José
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Carlos Carvalho .

Editor information

Editors and Affiliations

  1. Lisbon University Institute, Lisbon, Portugal

    Ana Lúcia Martins

  2. Lisbon University Institute, Lisbon, Portugal

    Joao C Ferreira

  3. University of Pisa, Pisa, Italy

    Alexander Kocian

Rights and permissions

Reprints and permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Carvalho, C., Pessoa, R., José, R. (2022). Cycling Analytics for Urban Environments: From Vertical Models to Horizontal Innovation. In: Martins, A.L., Ferreira, J.C., Kocian, A. (eds) Intelligent Transport Systems. INTSYS 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 426. Springer, Cham. https://doi.org/10.1007/978-3-030-97603-3_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-97603-3_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-97602-6

  • Online ISBN: 978-3-030-97603-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation