This study investigates how cycling speeds vary across infrastructure types using open data from Hamburg, Germany, collected between 2022 and 2024. By integrating bicycle network data, tracking app-based cycling speeds, land use, and topographic information, key determinants of cycling speed are identified through a gamma regression model. Results show that infrastructure type, surface conditions, and surrounding land use significantly affect speed. Dedicated cycling infrastructure promotes faster and more consistent speeds, especially on bituminous surfaces. Also, longer segments increase speeds. Urban or industrial areas tend to reduce speeds, while fields and forests lead to faster cycling speeds.


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    Titel :

    Cycling Speeds in Urban Traffic


    Beteiligte:
    Lucas Schuhmacher (Autor:in) / Gabriel Wilkes (Autor:in) / Martin Kagerbauer (Autor:in) / Peter Vortisch (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2025




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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