Most discrete choice models assume steady state conditions and a fully equilibrated system when estimating unknown coefficients from real-world data. However, the estimated model can be biased when the data set used for the model estimation was drawn from non- or less-equilibrated traveler behavior. The resulting biased model could lead to a misunderstanding of the system. Such effects on discrete choice model estimation were examined by performing Monte Carlo simulation experiments. A day-to-day dynamic evolutionary framework was used to observe changes in traveler’s choice and to compare the estimated results during the adjustment process with the true behavior parameters.


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    Titel :

    Effects of Less-Equilibrated Data on Travel Choice Model Estimation


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Oh, Jun-Seok (Autor:in) / Cortés, Cristián E. (Autor:in) / Recker, Will (Autor:in)


    Erscheinungsdatum :

    2003-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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