Building Intelligent Transport Systems of the Eurasian Economic Union Based on Optimal Management and Forecasting

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. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Авторы
Chupin A. , Afonin P. , Morkovkin D.
Сборник материалов конференции
Издательство
Springer Science and Business Media Deutschland GmbH
Язык
Английский
Страницы
253-263
Статус
Опубликовано
Том
61 LNISO
Год
2023
Организации
  • 1 RUDN University, 6 Miklukho-Maklaya Str., Moscow, Russian Federation
  • 2 Saint Petersburg Electrotechnical University LETI, 5 Professora Popova Str., St. Petersburg, Russian Federation
  • 3 Financial University Under the Government of the Russian Federation, 49 Leningradsky Prospekt, Moscow, Russian Federation
Ключевые слова
EAEU; Economic and mathematical modeling; Forecast; Intelligent transport systems; Management
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