Travelers and goods that move in a given area constitute the demand for transportation service offered by the system on examination. Demand forecast is extremely important for the analysis and the modeling of transportation systems because the planning of infrastructures and services of transports results from the necessity to satisfy the needs of mobility and its characteristics. The scientific literature about freight transportation provides fewer studies than the literature about passenger transportation. A state of art of freight demand models has been proposed by Regan and Garrido [20]. Urban freight demand models could be classified into gravity models (Hutchinson [10]; List and Turnquist [12]; Taylor [28]; Fridstrom [3]; Russo and Comi [21, 22, 23]), input-output models (Harris and Liu [5]; Marzano and Papola [13]), models of spatial equilibrium of the prices (Oppenheim [19]; Nagurney [15]). In this paper the results of an experimental survey conducted in a medium-sized city are introduced. Generation and distribution models have been specified and calibrated for shopping trips in terms of passenger trips (trip-based approach), for perishables and household products in terms of quantity movements (quantity-based approach) and for durable goods in terms of purchase movements (purchase-based approach). Furthermore, regarding generation models, more disaggregated categories have been used and family regression models have been specified, calibrated and validated for the trip-based approach, the quantity-based approach and the purchase approach taking into account the number of components of the familiar nucleus, the level of annual net income and the family car availability. Logit models simulating the choices of the size of purchased goods allow to convert, in the trip-based approach, the trips in quantities and, in the purchase-based approach, the units purchased in quantities.
Freight transport in urban areas: an integrated system of models to simulate freight demand and passengers demand for purchase trips
IAQUINTA, Pietro;
2010-01-01
Abstract
Travelers and goods that move in a given area constitute the demand for transportation service offered by the system on examination. Demand forecast is extremely important for the analysis and the modeling of transportation systems because the planning of infrastructures and services of transports results from the necessity to satisfy the needs of mobility and its characteristics. The scientific literature about freight transportation provides fewer studies than the literature about passenger transportation. A state of art of freight demand models has been proposed by Regan and Garrido [20]. Urban freight demand models could be classified into gravity models (Hutchinson [10]; List and Turnquist [12]; Taylor [28]; Fridstrom [3]; Russo and Comi [21, 22, 23]), input-output models (Harris and Liu [5]; Marzano and Papola [13]), models of spatial equilibrium of the prices (Oppenheim [19]; Nagurney [15]). In this paper the results of an experimental survey conducted in a medium-sized city are introduced. Generation and distribution models have been specified and calibrated for shopping trips in terms of passenger trips (trip-based approach), for perishables and household products in terms of quantity movements (quantity-based approach) and for durable goods in terms of purchase movements (purchase-based approach). Furthermore, regarding generation models, more disaggregated categories have been used and family regression models have been specified, calibrated and validated for the trip-based approach, the quantity-based approach and the purchase approach taking into account the number of components of the familiar nucleus, the level of annual net income and the family car availability. Logit models simulating the choices of the size of purchased goods allow to convert, in the trip-based approach, the trips in quantities and, in the purchase-based approach, the units purchased in quantities.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
