Methodology for modeling freight transportation based on statistical data of commodity groups
Keywords:
modeling, freight transport, transport infrastructure, modeling methodology, statistic dataAbstract
The article outlines the problem of generating freight traffic based on the available statistics for product groups in quantitative terms. The transport model is an important tool for planning and developing transport infrastructure. Its role is to identify bottlenecks in the simulated transport infrastructure. The presented methodology determines the procedure for processing the transport model depending on the goals, objectives and planned investment costs. It can be applied to new transport projects leading to a change in the quality, volume or reliability of the transport infrastructure. Modeling and analyzing intensity data is one of the ways to predict the demand for transportation and the behavior of the population in the area in question, as well as planning future route patterns. There are several possible alternative solutions for each transport problem, some of which are presented in the form of investment projects. However, testing multiple alternative designs in the field is nearly impossible due to the complexity and / or high cost. Transport modeling allows a variety of options to be tested. The financial costs and labor intensity when using simulation modeling are minimal. Transport models can be conditionally divided depending on: the length of the simulated territory, type (s) of transport, time costs; availability of the software package. Transport models used in practice are often a combination of model types. The different types of transport models are not strictly defined and may overlap. Thus, using the methodology for modeling freight traffic based on statistical data of commodity groups or a transport model, it becomes possible to increase the efficiency of the multimodal network by restoring the correspondence matrix.
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