A practical policy-sensitive, activity-based, travel-demand model

The development of activity-based models as a tool to analyse travel behaviour and forecast transport demand has been motivated by the growing complexity in activity patterns resulting from socio-economic changes, growing congestion, and negative externalities, as well as the need to estimate changes in travel behaviour in response to innovative policies designed to achieve sustainability. This paper reviews how the trade-off between behavioural realism and complexity, one of the main challenges facing the travel-demand modeler, is made in the best practical activity-based models. It proposes an approach that captures key behavioural aspects and policy sensitivities, while remaining practical with reasonable requirements of computational resources. The three main model elements in this trade-off-model structure, data, and application method-are analysed. Drawing on examples from a model developed for Tel Aviv and from existing US models, this paper shows that behavioural realism and policy sensitivity can be achieved with a reasonable level of model complexity.