For the most part, the bulk of freight transportation modelling applications are nothing more than adaptations of modelling methodologies originally designed for passenger transportation, that tend to overlook the fundamental differences between freight movements and passenger transportation. One of the unique features of freight transportation is that there are a number of different dimensions to be taken into account, most notably: weight, volume, number of vehicle-trips, and value of the commodities being transported. Each of these dimensions represents a different way to define and measure freight transportation demand, with important implications for freight demand modelling. The existence of these different dimensions has resulted in two major modelling platforms: commodity-based and vehicle-trip based modelling. These approaches represent, in essence, uni-dimensional views of a multi-dimensional problem with tonnage, vehicle-trips, and value as the most relevant dimensions. A recent formulation attempts to bridge the gap between commodity based and vehicle-trip based models by formulating the urban goods problem as a market in economic equilibrium. Vehicle-trip based modelling focuses on depicting the flows of commercial vehicles, e.g., truck trips. The focus on vehicle trips enables this type of models to consider both loaded and empty trips. The limitations of such models are described. One way of overcoming the limitation of the consideration of empty trips in commodity based models is to develop complementary models to depict empty trips as a function of the routing choices that the commercial vehicle operators make, which are based on the commodity flows in the study area. This paper uses probability principles to formulate a model of empty trips as a part of a commercial vehicle trip chain. Three different destination choice probability functions were hypothesized based on different assumptions about the destination choice process. An example, based on data from an origin-destination study in Guatemala City, is included. The numerical results indicated a slight superiority of the formulation that takes into account the length of the previous trip. In all cases, this model outperformed the previous models. The paper also provided empirical evidence of the importance of modelling empty trips. Holguin-Veras and Thorson (2002) developed a new set of models of commercial vehicle empty trips based on a first order model of trip chains. An example, based on data from an origin-destination study in Guatemala City, is included in this paper. The paper focuses on the assessment of the practical implications of the models developed by Holguin-Veras and Thorson. For the covering abstract see ITRD E124693.
Samenvatting