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A Dynamic Microsimulator for Travel Demand Forecasting
Abstract
The use of cross-sectional models in travel demand forecasting involves some fundamental problems. First, it is based on the untested assumption that cross-sectionally observed variations in travel behavior can be used as valid indicators of behavioral changes over time. Second, future values of socioeconomic and demographic input variables are obtained using inaccurate allocation and post-processing methods to transform aggregate forecasts into "pseudo-dissaggregate" data. And third, it does not properly represent response lages involved in long-term mobility decisions (e.g., residence location and car ownership). The result is a questionable basis on which travel demand forecasts are made.
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