Author
Abstract
The article presents the results of the analysis of existing national intelligent transport systems in the member states of the Eurasian Economic Union (EAEU). Currently, the development of intelligent transport systems (ITSs) is significantly limited by the difficulty of creating the control part of the system, which, except for the simplest cases of linear second-order objects, requires the use of functional converters of many variables or complex computing devices that solve the boundary problem. The authors have developed a scheme illustrating the realization of ITS optimal control based on a number of principles. This scheme shows the principal possibility of constructing ITSs of optimal control of n-order objects in which a set of predictive devices is used as the optimal regulator. World experience shows that one of the most important elements of the economy of states is the transport infrastructure. It largely determines the scale of production and trade. Due to the increasing requirements for the quality of automatic control processes in the transport infrastructure, ITSs are increasingly being used. ITS is the transport management using the information infrastructure. In other words, it is the use of a control system and an extensive class of speed-optimal systems. The purpose of the study is the development of ITSs in the EAEU countries by using the method of optimal management and forecasting. The paper is structured as follows. In Sect. 1, we describe the state of ITSs in the EAEU countries. In Sect. 2, we present a block diagram of the optimal ITS control system with single-coordinate prediction. Section 3 provides a description of various studies. And in Sect. 4, we conclude on the application of the optimal control and forecasting method.
Suggested Citation
Alexander Chupin & Petr Afonin & Dmitry Morkovkin, 2023.
"Building Intelligent Transport Systems of the Eurasian Economic Union Based on Optimal Management and Forecasting,"
Lecture Notes in Information Systems and Organization, in: Vikas Kumar & Grigorios L. Kyriakopoulos & Victoria Akberdina & Evgeny Kuzmin (ed.), Digital Transformation in Industry, pages 253-263,
Springer.
Handle:
RePEc:spr:lnichp:978-3-031-30351-7_20
DOI: 10.1007/978-3-031-30351-7_20
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