Abstract
One of the factors limiting the increase in quality of traffic with the increasing complexity of the freight traffic in Russia is the lack of interaction consistency of the main modes of transport and transport uncommon in areas of direct transport service production and transport units. Lack of practical operating experience of intelligent transport systems in Russian enterprises, poor prevalence of well-known methods of accumulation and analysis of knowledge in transport, decision-making (genetic algorithms, neural networks, knowledge bases, Big Data methods, etc.) require improvement of the existing interaction methodology between industry and transport, in particular transport and technological systems providing direct cargo transport services. This methodology should be based not only on modern progress in technology and organization of rail transport, but also taken into account the economic and informational factors and constraints that arise in the interaction of industrial and mainline rail. This article proposes an approach to the formation and composition of intelligent transport systems in industry. This approach is based on the original combination of analytical and simulation models of transport and technological system realizing the complex of transport and logistic methods of functioning organization of rail transport and technological systems. Intelligent transport system of proposed functional composition is focused on improving the efficiency of interaction between production and transport in terms of complicating the structure of freight traffic and the increasing quality requirements for freight.
| Original language | English |
|---|---|
| Title of host publication | Studies in Systems, Decision and Control |
| Publisher | Springer International Publishing |
| Pages | 161-215 |
| Number of pages | 55 |
| DOIs | |
| Publication status | Published - 2016 |
Publication series
| Name | Studies in Systems, Decision and Control |
|---|---|
| Volume | 32 |
| ISSN (Print) | 2198-4182 |
| ISSN (Electronic) | 2198-4190 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Control and Systems Engineering
- Automotive Engineering
- Social Sciences (miscellaneous)
- Economics, Econometrics and Finance (miscellaneous)
- Control and Optimization
- Decision Sciences (miscellaneous)
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