International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

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 Volume 8, Issue 11 (November 2021), Pages: 37-43

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 Original Research Paper

 Title: Organizational and economic mechanism of the automatic underground train operation system

 Author(s): Oleksii Yu. Palant 1, *, Vyacheslav V. Stamatin 2, Olena V. Dymchenko 1, Mykola V. Nesprava 3, Tykhon S. Yarovoi 4

 Affiliation(s):

 1Department of Entrepreneurship and Business Administration, O.M. Beketov National University of Urban Economy in Kharkiv, Kharkiv, Ukraine
 2Municipal Enterprise “Kharkiv Metro”, Kharkiv, Ukraine
 3Department of International Relations and Tourism, Dnipropetrovsk State University of Internal Affairs, Dnipro, Ukraine
 4Department of Public Administration, Interregional Academy of Personnel Management, Kyiv, Ukraine

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0001-8178-6874

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2021.11.005

 Abstract:

This work deals with the provision of underground, as one of the main modes of public transport, with automated control systems, in particular the provision of automated train management. It defines that the underground is one of the most progressive modes of transport, which is related to its environmental safety, comfort, and speed of movement, as this mode of transport does not intersect with other transport and pedestrian routes, which excludes traffic blocks. Underground is an important element of urbanized spaces, for it serves large passenger traffic. The article presents an algorithm for the creation of an automated control system for the underground train system. Based on this algorithm, a model of building an organizational and economic mechanism for automation of control systems has been developed. The diagram of organizational and technical implementation of the automated system of underground train management is presented. An economic analysis of the effectiveness of the application of the automated control system of underground trains was carried out. The recoupment on the acquisition and installation of automation systems is very high. The application of the automated system will increase the capacity of the underground by optimizing the traffic schedules, which will contribute to increasing its profitability. It is also useful to determine the reduction of electricity consumption due to the change in the dynamics of acceleration and braking systems, which is important, as the underground is a powerful enterprise. In the future, a promising direction is to streamline the coordination of train schedules and other modes of land public transport. 

 © 2021 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Automated control systems, Public transport, Metropolitan cities, Traffic system, Electric transport

 Article History: Received 24 June 2021, Received in revised form 28 August 2021, Accepted 30 August 2021

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Palant OY, Stamatin VV, and Dymchenko OV et al. (2021). Organizational and economic mechanism of the automatic underground train operation system. International Journal of Advanced and Applied Sciences, 8(11): 37-43

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 Figures

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 Tables

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 References (18)

  1. Abed SK (2010). European rail traffic management system-an overview. In the 1st International Conference on Energy, Power and Control, IEEE, Basrah, Iraq: 173-180.   [Google Scholar]
  2. Africa ADM, Bautista SJP, Lardizabal FJO, Patron JNC, and Santos AGN (2017). Minimizing passenger congestion in train stations through radio frequency identification (RFID) coupled with database monitoring system. ARPN Journal of Engineering and Applied Sciences, 12(9): 2863–2869.   [Google Scholar]
  3. Bakulina O, Lehan I, and Bakhov I (2019). Cluster associations as a factor of innovative and integrative development of the economy. International Journal of Innovative Technology and Exploring Engineering, 8(10): 2249–2255. https://doi.org/10.35940/ijitee.J1122.0881019   [Google Scholar]
  4. Berger U, James P, Lawrence A, Roggenbach M, and Seisenberger M (2018). Verification of the European rail traffic management system in real-time maude. Science of Computer Programming, 154: 61–88. https://doi.org/10.1016/j.scico.2017.10.011   [Google Scholar]
  5. Chernenko N, Korohodova O, Moiseienko T, and Hlushchenko Y (2020). Influence of industry 4.0 on the investment activities of transnational corporations. Scientific Horizons, 23(10): 68–77. https://doi.org/10.48077/scihor.23(10).2020.68-77   [Google Scholar]
  6. Cho I-H, Kim D-Y, and Lee B-H (2018). Research on technical characteristics of battery management system for railway systems. Journal of the Korean Society for Railway, 21(9): 882–891. https://doi.org/10.7782/JKSR.2018.21.9.882   [Google Scholar]
  7. Davis D (2010). Railway signaling and control systems legal issues and the engineer: Some notes on contract law and intellectual property rights. In the IET Professional Development Course on Railway Signaling and Control Systems, IET, Birmingham, UK: 41-46. https://doi.org/10.1049/ic.2010.0086   [Google Scholar]
  8. Faggini M and Parziale A (2012). The failure of economic theory: Lessons from chaos theory. Modern Economy, 3(1): 16802. https://doi.org/10.4236/me.2012.31001   [Google Scholar]
  9. Feng D, Lin S, He Z, and Sun X (2017). A technical framework of PHM and active maintenance for modern high-speed railway traction power supply systems. International Journal of Rail Transportation, 5(3): 145–169. https://doi.org/10.1080/23248378.2017.1286954   [Google Scholar]
  10. Gaspari P, Riccobene E, and Gargantini A (2019). A formal design of the hybrid European rail traffic management system. In the 13th European Conference on Software Architecture, Association for Computing Machinery, Paris, France, 2: 156-162. https://doi.org/10.1145/3344948.3344993   [Google Scholar]
  11. Liu J, Gui W, Huang Z, Liu Y, and Liu Y (2011). Modelling and model optimization of locomotive brake control system. In the 2011 International Conference on Transportation, Mechanical, and Electrical Engineering, IEEE, Changchun, China: 1256-1260. https://doi.org/10.1109/TMEE.2011.6199433   [Google Scholar]
  12. Lukasevych-Krutnyk IS (2020). The concept and methods of harmonisation of the private law legislation of Ukraine in the field of provision of transport services with the legislation of the European Union. Journal of the National Academy of Legal Sciences of Ukraine, 27(2): 91–106. https://doi.org/10.37635/jnalsu.27(2).2020.91-106   [Google Scholar]
  13. Naghiyev A, Sharples S, Ryan B, Coplestone A, and Carey M (2017). Expert knowledge elicitation to generate human factors guidance for future European rail traffic management system (ERTMS) train driving models. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 231(10): 1141–1149. https://doi.org/10.1177/0954409717695902   [Google Scholar]
  14. Navarro J, Segarra P, Sanchidrián JA, Castedo R, and Lopez LM (2019). Assessment of drilling deviations in underground operations. Tunnelling and Underground Space Technology, 83: 254-261. https://doi.org/10.1016/j.tust.2018.10.003   [Google Scholar]
  15. Sheludchenko B, Kukharets S, Biletskiy V, and Pluzhnikov O (2019). Background of collective movement synchronization motor transport flows serpentine sites (in hairpins) car roads. Scientific Horizons, 12(85): 60–66. https://doi.org/10.33249/2663-2144-2019-85-12-60-66   [Google Scholar]
  16. Skalozub VV and Osovik VN (2014). Individual intellectual models for the operation of a fleet of homogeneous railway technical systems based on current state parameters. Information and Control Systems for Railway Transport, 6: 8–12. Available online at: http://nbuv.gov.ua/UJRN/Ikszt_2014_6_3   [Google Scholar]
  17. You K, Yu M, and Yu Q (2019). Research and application on design of underground container logistics system based on autonomous container truck. In the IOP Conference Series: Earth and Environmental Science, IOP Publishing, 330(2): 022054. https://doi.org/10.1088/1755-1315/330/2/022054   [Google Scholar]
  18. Zhukovytskyy I (2017). Use of an automaton model for the designing of real-time information systems in the railway stations. Transport Problems, 12(4): 101–108. https://doi.org/10.20858/tp.2017.12.4.10   [Google Scholar]