E3S Web Conf.
Volume 157, 2020Key Trends in Transportation Innovation (KTTI-2019)
|Number of page(s)||10|
|Section||Digitalisation of Transport and Logistics|
|Published online||20 March 2020|
Modeling of the virtual system of control of contrailer transportation in the information-economic space
Federal Freight Company, Kuibysheva Street, 44, letter D, Yekaterinburg, 620026, Russia
2 Ural State University of Railway Transport (USURT), Kolmogorova Street, 66, 620034, Yekaterinburg, Russia
* Corresponding author: email@example.com
In the present work, the main attention is focused on research and search for the most rational, economically justified way of developing the potential of the railway industry in the field of interaction of several modes of transport in the organization and management of correspondence of piggyback traffic. The concept, which is based on the evaluation of possibilities of future subjects of the transport and logistics process to integrate into a single information field of the transport system. The information model of the system for the management of contrailer traffic in the information and economic space is considered. The stratum of cognitive subsystem in the presented virtual system allows transforming and structuring the processes of monitoring, analysis, accounting and storage of correspondence of transport infrastructure of supposed production facilities, railway stations and loading and unloading sites for their compliance with the requirements for the organization of contrailer transportation correspondence. The information subsystem’s stratum reflects the functions of accounting and recording the impact of the subjects of transportation on the compliance with the technological process in all its life cycles. The application subsystem stratum reflects the process of making optimal decisions, formation of management teams. The difference of virtual control system consists in intellectual architecture, namely cognitive subsystem, which forms knowledge about unified information system and operational and technological management on the basis of above mentioned information data. Knowledge generation is based on the results of processing of system state data coming from system agents and integrators.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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