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.
Effects of Less-Equilibrated Data on Travel Choice Model Estimation
Transportation Research Record
Transportation Research Record: Journal of the Transportation Research Board ; 1831 , 1 ; 131-140
2003-01-01
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Effects of Less-Equilibrated Data on Travel Choice Model Estimation
Online Contents | 2003
|Effects of Less-Equilibrated Data on Travel Choice Model Estimation
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