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Combining environmental quality assessment of bicycle infrastructures with vertical acceleration measurements

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  • Nuñez, Javier Yesid Mahecha
  • Bisconsini, Danilo Rinaldi
  • Rodrigues da Silva, Antônio Nélson

Abstract

Growing interest in zero emission transport modes, such as cycling, is currently generating motivation to construct new cycle paths. However, transportation planners and managers cannot always rely on practical methods for allocating the resources (often limited) needed for inventories and assessing cycling infrastructures. The aim of this study is to develop a method for classifying cycle paths in terms of roughness and general conditions of the pavement surface. Inventory data and information regarding the infrastructure conditions were collected on-site using video recordings taken by an action camera directly mounted on a bicycle. Georeferenced vertical acceleration data were collected using a smartphone. Acceleration data of three different pavement surfaces (asphalt, concrete and concrete bricks) were registered. The results showed the lowest acceleration values for concrete pavement and the highest values for interlocking concrete pavement. The proposed method can be a practical and efficient approach to evaluate cycling infrastructures in terms of pavement condition.

Suggested Citation

  • Nuñez, Javier Yesid Mahecha & Bisconsini, Danilo Rinaldi & Rodrigues da Silva, Antônio Nélson, 2020. "Combining environmental quality assessment of bicycle infrastructures with vertical acceleration measurements," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 447-458.
  • Handle: RePEc:eee:transa:v:137:y:2020:i:c:p:447-458
    DOI: 10.1016/j.tra.2018.10.032
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    References listed on IDEAS

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    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. Calvey, J.C. & Shackleton, J.P. & Taylor, M.D. & Llewellyn, R., 2015. "Engineering condition assessment of cycling infrastructure: Cyclists’ perceptions of satisfaction and comfort," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 134-143.
    3. John Pucher & Ralph Buehler, 2007. "Making Cycling Irresistible: Lessons from The Netherlands, Denmark and Germany," Transport Reviews, Taylor & Francis Journals, vol. 28(4), pages 495-528, November.
    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. Joo, Shinhye & Oh, Cheol, 2013. "A novel method to monitor bicycling environments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 1-13.
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    Cited by:

    1. Martín López-Molina & David Llopis-Castelló & Ana María Pérez-Zuriaga & Carlos Alonso-Troyano & Alfredo García, 2022. "Skid Resistance Analysis of Urban Bike Lane Pavements for Safe Micromobility," Sustainability, MDPI, vol. 15(1), pages 1-14, December.
    2. Tufail Ahmed & Ali Pirdavani & Davy Janssens & Geert Wets, 2023. "Utilizing Intelligent Portable Bicycle Lights to Assess Urban Bicycle Infrastructure Surfaces," Sustainability, MDPI, vol. 15(5), pages 1-22, March.

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