In the United States, planning and design efforts to generate bike-friendly environments through the greater provision of safe, low-stress bike infrastructure in our cities continue to advance. In Cambridge, Massachusetts, construction of the Grand Junction Pathway – an envisioned shared-use pathway – is at the heart of a citywide effort to enhance its active transportation system. However, a challenge – shared by many public agencies given that data on cycling activity are rarely frequently systematically gathered – is the creation of a baseline estimate of cycling demand for this planned network link. Using short-duration manual data supplemented with long-duration count data, this study employs a state-of-the-practice method for generating annual average daily bicycle trips for current bike network facilities. A statistical modelling strategy is then undertaken to forecast the volume of daily cyclists that the proposed off-street, shared-use path could expect to attract given its physical context and the socioeconomic attributes of nearby residents.


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    Titel :

    Direct demand modelling approach to forecast cycling activity for a proposed bike facility


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2021-01-02


    Format / Umfang :

    15 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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