This paper proposes a Dynamic Demand Estimation (DODE) framework that explicitly accounts for activity scheduling and duration. By assuming a Utility-Based departure time choice model, the time-dependent OD flow becomes a function, whose parameters are those of the utility function(s) within the departure time choice model. In this way, the DODE is solved using a parametric approach, which, on one hand, has less variables to calibrate with respect to the classical bi-level formulation while, on the other hand, it accounts for different trip purposes. Properties of the model are analytically and numerically discussed, showing that the model is more suited for estimating the systematic component of the demand with respect to the standard GLS formulation. Differently from similar approaches in literature, which rely on agent-based microsimulators and require expensive survey data, the proposed framework is applicable with all those DTA models, which are based on OD matrix, and do not necessarily need any data at user level. This is illustrated by applying the proposed approach with a standard macroscopic realistic Dynamic Traffic Assignment (DTA).
Cantelmo, G., Viti, F., Cipriani, E., Nigro, M. (2017). A Utility-based Dynamic Demand Estimation Model that Explicitly Accounts for Activity Scheduling and Duration. In Transportation Research Procedia (pp.440-459). Elsevier B.V. [10.1016/j.trpro.2017.05.025].
A Utility-based Dynamic Demand Estimation Model that Explicitly Accounts for Activity Scheduling and Duration
Cantelmo, Guido;Viti, Francesco;Cipriani, Ernesto;Nigro, Marialisa
2017-01-01
Abstract
This paper proposes a Dynamic Demand Estimation (DODE) framework that explicitly accounts for activity scheduling and duration. By assuming a Utility-Based departure time choice model, the time-dependent OD flow becomes a function, whose parameters are those of the utility function(s) within the departure time choice model. In this way, the DODE is solved using a parametric approach, which, on one hand, has less variables to calibrate with respect to the classical bi-level formulation while, on the other hand, it accounts for different trip purposes. Properties of the model are analytically and numerically discussed, showing that the model is more suited for estimating the systematic component of the demand with respect to the standard GLS formulation. Differently from similar approaches in literature, which rely on agent-based microsimulators and require expensive survey data, the proposed framework is applicable with all those DTA models, which are based on OD matrix, and do not necessarily need any data at user level. This is illustrated by applying the proposed approach with a standard macroscopic realistic Dynamic Traffic Assignment (DTA).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.