MODELING THE INTERDISTRICT CORRESPONDENCE MATRIX

Аннотация

This article analyzes theoretical and practical approaches to modeling the interregional correspondence matrix in the transport sector. The concept of transport demand, the factors that form it, and ways to use it as a means of managing the demand for the transport system in modern urban planning are highlighted. The essence, differences, advantages, and disadvantages of aggregate and disaggregate models used in determining matrix values are considered. Optimized flows from the user and system perspectives are also analyzed based on Wardrop's principles. The need for doset models aimed at identifying potential transport needs, regardless ofthe network configuration, issubstantiated. Keywords: transport demand, correspondence matrix, aggregate model, disaggregate model, Wardrop principles, user optimization, system optimization, transport flows, transport modeling, doset model. Introduction. Management and forecasting of traffic flows in urban planning and transport planning is one of the most pressing issues today. Especially for the stable functioning of the transport system in large cities, it is important to analyze data on population movement, to model this movement through interaction in an interregional context. From this point of view, the compilation and modeling of the interregional correspondence matrix is one of the main stages in determining demand in the transport sector and ensuring the effective functioning of the network. In this chapter, the essence of the interregional correspondence matrix, the factors of transport demand formation, the significance of aggregate and disaggregate models used in determining thisdemand, and thecases of theirapplication are widely covered. Main Part. Transport demand is a quantitatively determined need for transportation and additional transport services. It can be measured in the number of vehicles, passengers, or cargo per unit of time. The demand for the services of a specific type of transport is determined, in particular, by the development of various types of transport in the region, the degree of their integration, the level of transport tariffs, and the quality of service provided to consumers by various types of transport enterprises and organizations. The demand for freight transportation is largely determined by two factors: the dynamics and structure of changes in production volumes, as well as the solvency of enterprises and organizations in all sectors of the economy [1]. As in the market situation, so-called market equilibrium (balance of supply and demand) operates in the transport services sector. The flow distribution in the transport network is an analogue of the market equilibrium situation, in which traffic participants create a demand for the use of transport system elements, the capabilities of these elements act as a supply, and the price is the costs (time, cost, comfort level) of traffic participants arising from the use of these page121 INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE ISSN:2692-5206,ImpactFactor:12,23 AmericanAcademicpublishers,volume05,issue06,2025 Journal: https://www.academicpublishers.org/journals/index.php/ijai elements. In the case when demand exceeds the possibilities of supply, a deterioration in the conditions of movement occurs, which leads to an increase in such costs. The total increase in such costs can be used as one of the indicators of the total overload of the transport system. For individual network sections, such growth can serve as an indicator of their insufficient capacity (carrying capacity). In addition, it is known that improved traffic conditions provoke increased traffic -so-called induced demand manifests itself. It should be noted that in recent years, in the practice of urban planning, transport demand has often been considered not as a predetermined value determining the flow distribution structure, but as a tool for managing the city's transport system. In particular, over the past decades, experience has been accumulated in using a whole range of regulatory measures aimed at reducing the demand for the use of individual transport ports, especially in areas with dense urban development [1]. Modeling the inter-district correspondence matrix is the main stage in calculating transport demand parameters. The problem of distributing movements (correspondences) between pairs of transport areas with known "departure" and "arrival" values, determined at the trip generation stage, has an infinite set of solutions. Figure 1 shows a tabular form of the correspondence matrix, each element of which represents the number of movements between pairs oftransport areas -from area i to area j. Arrivals Shipments 1 2 … n sum 1 P1 2 ? P2 m Pm sum Q1 Q2 … Qn Fig. 1.Correspondence matrix tableform Correspondence matrix values cannot be directly measured, therefore various indirect approaches are used to determine them, such as sociological research or the method of restoring matrix values based on known flo