In sharp contrast to passenger transport demand modelling macroscopic models are the state of the art for freight transport demand analysis and forecasting. These models deduce transport demand with statistical methods from socio-demographic and economical data for the regions under consideration. The idea behind microscopic modeling is the representation of the interacting subjects that produce transport demand in a computer simulation. The properties of the whole transport system emerge from the individual actions of these subjects. In this way microscopic models are able to consider broader information about influences, possible choices and constraints for transport decisions. Furthermore the temporal and spatial resolution is intrinsically higher when using microscopic modelling. In this light the Institute for Transport Research in the German Aerospace Center (DLR) is developing the commercial transport simulation model 'WiVSim'. The project's goal is the disaggregated analysis of commercial tranport under the influences of changes in manufacturing and logistics. At the same time the shift from macroscopic to microscopic models, which has been achieved for passenger travel demand modelling (e.g. TRANSIMS and activity-based models by Timmermans or Bowman, Ben-Akiva), is to be replicated for freight transport demand modelling. The simulation framework will be used for analysis and forecasting and for the evaluation of new concepts for efficient freight transport. In this paper the concept and setup of the simulation model is described. First results from a prototype implementation are presented as well. The framework centers around an agent-based, microscopic model of freight transport demand. In the model, agents represent business sites of enterprises in manufacturing industries. Decisions leading from the structural properties of the sites (e.g. location, industry, size) to their freight transport demand are modelled using rules. In this way, the step from a simulated virtual economy to freight shipment demand is taken. The resulting list of individual shipments forms the input of the next simulation module which represents logistics providers. The module groups shipments to trips utilising rules and an optimization mechanism. Transport mode choice is done at this stage as well incorporating possible constraints from shippers. In the next step the list of microscopic trips is fed into an existing microscopic traffic flow model on the underlying transport network of the area to be analysed. The flow model generates traffic loads for individual edges in the transport network, e.g. streets and railroads. From these traffic loads aggregated indicators for transportation and environmental effects can be computed, e.g. travel times or noise and pollution effects. The indicator values influence the agent's decisions in the next time step. Changes in production patterns, spatial effects (outsourcing), short-term and long-term logistics changes are considered. The microscopic model needs data of a new structure, revealing decision making mechanisms regarding freight transport in individual businesses and their influences. To gather these data a qualitative study has been performed. It is planned to gather relevant quantitave data in a further study to calibrate and validate the model. In the first project stage this concept was implemented in a prototype simulation which incorporates all modules to show the data flow from a virtual economic structure through shipments and trips to loads on edges of the transport network. Results for this prototype are to be presented together with the underlying model structure, next steps and planned applications. For the covering abstract please see ITRD E135207.
Abstract