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Descripción
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| To reduce the effects generated by extremely high levels of mobility and by an indiscriminate use of private cars many cities have started implementing various types of policies. To avoid the costly effects of taking wrong decisions it is vital to identify users¿ necessities and their possible responses under the implementation of new policies. Thus, demand estimation is a key component of any appropriate urban transport planning framework. Most travel demand models to date have been based on cross-sectional data. This data structure fails to correctly ascertain how choices evolve over time (both short and long-term variability). Models that fail to account for temporal effect (such as habit and inertia) might severely overestimate demand as well as user benefits due to new policies, leading the administration to take wrong decisions about their implementation. The objective of this research is to develop advanced disaggregate models that explicitly account for temporal effects in mode choice. Dynamic discrete choice models will be developed to study the true structural dependence among choices made in different periods. We expect our analyses and modelling results will provide a methodological contribution to the state of the art in this field for the international scientific community. The second objective is to speriment a new methodology to gathered panel data that represent the most appropriate data to develop models incorporating temporal effects. Advanced technology, such as GPS and smartphone, will be used to provide data of high quality and precision reducing the burden of the survey. This panel will represent a source of reference not only in Spain but also for the international research community in the field. | |
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Internacional
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No |
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Tipo de proyecto
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Proyectos y convenios en convocatorias públicas competitivas |
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Entidad financiadora
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Ministerio de Ciencia e Innovación |
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Nacionalidad Entidad
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ESPAÑA |
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Tamaño de la entidad
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Desconocido |
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Fecha concesión
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01/01/2011 |