Publication Detail
Midas: A Travel Demand Forecasting Tool Based on a Dynamic Model System of Household Demographics and Mobility
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UCD-ITS-RP-91-22 Research Report Download PDF |
Suggested Citation:
Kitamura, Ryuichi and Konstadinos G. Goulias (1991) Midas: A Travel Demand Forecasting Tool Based on a Dynamic Model System of Household Demographics and Mobility. Institute of Transportation Studies, University of California, Davis, Research Report UCD-ITS-RP-91-22
The Dutch National Mobility Panel has contributed tremendously to the development of dynamic travel behavior research by offering a unique and rich data set that has made possible the examination of many aspects of travel behavior that could not have been studied with cross-sectional data. This panel data set has been applied to the more traditional subject areas of mode use, car ownership, trip generation, and trip chaining, and to more novel subject areas such as habitual behavior, response lags, and adaptation behavior.
A new approach to travel demand forecasting is proposed in this study in which the following two concepts are integrated to form a simulation model of household travel. The first is the dynamic model of travel behavior. Panel data enable us observe changes, thus making possible the development of models that relate behavioral changes to changes in contributing factors. Using such dynamic models, future behavior can be predicted by extending longitudinally observed changes. It is in this respect that the use of dynamic models in forecasting is critically different from the use of cross-sectional models which, unfortunately, involves the untested assumption that future behavior can be depicted by longitudinally extrapolating cross-sectional variations.
The development of dynamic models in this study is a continuation of earlier work by one of the authors. That study, which used the Dutch National Mobility Panel data and was funded by Dienst Verkeerskunde (DVK), formulated a dynamic model system of car ownership and mobility, and discussed its application to forecasting. This present study adopts the model system, refines it, and uses it as a component of the forecasting model system developed in the study.
A new approach to travel demand forecasting is proposed in this study in which the following two concepts are integrated to form a simulation model of household travel. The first is the dynamic model of travel behavior. Panel data enable us observe changes, thus making possible the development of models that relate behavioral changes to changes in contributing factors. Using such dynamic models, future behavior can be predicted by extending longitudinally observed changes. It is in this respect that the use of dynamic models in forecasting is critically different from the use of cross-sectional models which, unfortunately, involves the untested assumption that future behavior can be depicted by longitudinally extrapolating cross-sectional variations.
The development of dynamic models in this study is a continuation of earlier work by one of the authors. That study, which used the Dutch National Mobility Panel data and was funded by Dienst Verkeerskunde (DVK), formulated a dynamic model system of car ownership and mobility, and discussed its application to forecasting. This present study adopts the model system, refines it, and uses it as a component of the forecasting model system developed in the study.
Final report for Project Bureau Integrale Verkeer: en Vervoe Studies, the Dutch Ministry of Transport and Public Works, The Hague, The Netherlands.