Integration between activity-based demand models and multimodal assignment: Some empirical evidences

Abstract Aiming at supporting decision makers in transport policy choices, transport models used for decades the trip-based approach for travel demand forecasts. This approach, despite suited to peak hours modelling where systematic trips are predominant, suffers the limits of not being related to the sequence of activities usually undertaken in real day-life. Differently, in the Activity Based Models (ABM) the travel demand is explicitly modelled as the result of individuals’ involvement in different activities in different times and locations. The use of such models is recommended when complex trip chains connected to the multiple daily activities that characterise today's life have to be taken into account, even if the integration with other sub-models (particularly with the assignment) within the whole transport modelling procedure has to be carefully considered. For this reason, this paper focuses on the integration between ABM and transport assignment by investigating the multimodal demand-supply interaction. Specifically, the consistency between ABM and assignment models is studied proposing a methodology that can be applied to large real size networks. It is based on a multimodal static equilibrium assignment, which is easy-to-use and less time consuming with respect to a Dynamic Traffic Assignment (DTA), allowing a better estimation of the modal splits between alternative transport modes. Such a model also considers (road) congestion and (transit) crowding phenomena, as well as the multimodal network performances are estimated by taking into account the interaction between different modes sharing the same network facilities. The goodness of the proposed approach is investigated through the convergence analysis of both the entire integration procedure and its individual components (ABM and assignment) for a better transport simulation in urban areas. The application to an urban multimodal network of real-size dimensions (Rome) is presented to show the promising results of this research.

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