There is a widespread belief that the available tools for predicting travel impacts of urban development are not as strong as they could be. The implications are that cities ( a) may be hindered in developing appropriate travel impact mitigations, ( b) lack good information to communicate to existing residents about potential travel impacts of proposed development, and ( c) with better tools would be able to make stronger policy on the basis of more reliable understanding of development impacts. The most frequently used tool for estimating travel impacts is the ITE informational report on vehicle trip generation. The ITE report contains information primarily on single-use suburban automobile-oriented environments. As travel characteristics are inherently different in urban areas, a wide body of research has sought to create additional data-driven tools to estimate multimodal trip impacts of developments on the basis of urban-context characteristics. This paper compares the estimated trip generation outputs of the ITE and other models to field counts and surveys conducted for the District Department of Transportation at 16 locations in Washington, D.C. The findings here support the widely held belief that existing tools are not well suited to trip generation estimation in urban contexts. The paper is part of a larger study effort that seeks to develop a robust data set of urban trip generation that will be a foundation in the creation of better models.


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    Titel :

    Predicting Travel Impacts of New Development in America's Major Cities


    Untertitel :

    Testing Alternative Trip Generation Models


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Weinberger, Rachel (Autor:in) / Dock, Stephanie (Autor:in) / Cohen, Liza (Autor:in) / Rogers, Jonathan D. (Autor:in) / Henson, Jamie (Autor:in)


    Erscheinungsdatum :

    04.04.2019




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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