Abstract The persistence of environmental problems in urban areas and the prospect of increasing congestion have precipitated a variety of new policies in the USA, with concomitant analytical and modeling requirements for transportation planning. This paper introduces the Sequenced Activity-Mobility Simulator (SAMS), a dynamic and integrated microsimulation forecasting system for transportation, land use and air quality, designed to overcome the deficiencies of conventional four-step travel demand forecasting systems. The proposed SAMS framework represents a departure from many of the conventional paradigms in travel demand forecasting. In particular, it aims at replicating the adaptative dynamics underlying transportation phenomena; explicitly incorporates the time-of-day dimension; represents human behavior based on the satisficing, as opposed to optimizing, principle; and endogenously forecasts socio-demographic, land use, vehicle fleet mix, and other variables that have traditionally been projected externally to be input into the forecasting process.


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    Titel :

    The sequenced activity mobility simulator (SAMS): an integrated approach to modeling transportation, land use and air quality


    Beteiligte:
    Kitamura, Ryuichi (Autor:in) / Pas, Eric I. (Autor:in) / Lula, Clarisse V. (Autor:in) / Lawton, T. Keith (Autor:in) / Benson, Paul E. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    1996




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.80 Verkehrswesen, Transportwesen: Allgemeines / 74.75 Verkehrsplanung, Verkehrspolitik
    Lokalklassifikation TIB:    535/7000



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