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Multicriteria train running model and simulator for railway capacity assessment

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Railway line capacity is growing in importance as a criterion for the assessment of railroad infrastructure performance. This problem is becoming more and more relevant as the demand for rail transport increases, especially considering the transport policy related to the promotion of climate-neutral means of transport. Insufficient capacity affects the stability and reliability of railway traffic operations. The analytical methods used for capacity estimation are typically insufficient to solve problems of a multicriteria nature (i.e. problems which take traffic heterogeneity and human factors into account). Optimisation methods, on the other hand, usually yield the best results if the current timetable for a given line is known. Additionally, they do not strongly consider the impact of the running characteristics of a specific train type and of the system or several systems in operation on the line (e.g. national Class B system and ERTMS/ETCS system). Therefore, this paper proposes a model and a simulation program developed in the Matlab and Simulink environment to be used to simulate on-route train movement, to study railroad capacity with different control systems, as well as for predictive train control to minimise energy losses. The authors described the assumptions adopted for the simulation program and the input parameters configurable against a specific line segment. They also discussed selected results derived from simulations of controlling the departure of trains to a railway line with the purpose of energy loss reduction.
Czasopismo
Rocznik
Strony
199--212
Opis fizyczny
Bibliogr. 27 poz.
Twórcy
  • Silesian University of Technology, Faculty of Transport and Aviation Engineering; Krasińskiego 8, Katowice, 40-019, Poland
autor
  • Alstom ZWUS Polska Sp. z o.o.; Modelarska 12, Katowice, 40-142, Poland
Bibliografia
  • 1. Burchart-Korol, D. & Folega, P. Impact of road transport means on climate change and human health in Poland. Promet-traffic & transportation. 2019. Vol. 31. No. 2. P. 195-204.
  • 2. Folega, P. & Burchart-Korol, D. Environmental assessment of road transport in a passenger car using the life cycle approach. Transport Problems. 2017. Vol. 12. No. 2. P. 147-153.
  • 3. Riboni, A. & et al. Design for testability of ERTMS Applications. In: 2019 IEEE International Symposium on Software Reliability Engineering Workshops. Berlin, Germany. 27-30.10.2019.
  • 4. Abril, M. & Barber, F. & Ingolotti, L. & et al. An assessment of railway capacity. Transportation Research Part Logistics and Transportation Review. 2008. Vol. 44. P. 774-806.
  • 5. Lai Yung-Cheng & Liu Yun-Hsuan & Lin Yi-Ju. Standardization of capacity unit for headway -based rail capacity analysis. Transportation Research. 2015. Vol. C57. P. 68-84.
  • 6. Dąbrowa-Bajon, M. Podstawy sterowania ruchem kolejowym. Vol. 3. Publishing House of the Warsaw University of Technology. Warsaw, 2014. ISBN: 978-83-7814-320-8. [In Polish: Basics of Rail Traffic Control].
  • 7. Jacyna, M. & Gołębiowski, P. & Krześniak, M. & Szkopiński, J. Organizacja ruchu kolejowego. Vol. I. Warsaw: PWN. 2019. ISBN: 978-83-01-20689-5. [In Polish: Organization of railway traffic].
  • 8. UIC leaflet 406, Capacity. UIC International Union of Railways, France 2004.
  • 9. Borodin, A. & Panin, V. The distribution of marshalling work of industrial and mainline rail transport. Transport Problems. 2018. Vol. 13. No. 4. P. 37-46.
  • 10. Pouryousef, H. & Lautala, P. & White, T. Railroad capacity tools and methodologies in the U.S. and Europe. J. Mod. Transport. 2015. Vol. 23. P. 30-42.
  • 11. Rosberg, T. & Thorslund, B. Simulated and real train driving in a lineside automatic train protection (ATP) system environment. Journal of Rail Transport Planning & Management. 2020. Vol. 16. Article ID: 100205.
  • 12. Rosell, F. & Codina, E. A model that assesses proposals for infrastructure improvement and capacity expansion on a mixed railway network. Transportation Research Procedia. 2020. Vol. 47. P. 441-448.
  • 13. Gao, H. & Zhang, Y. & Guo, J. Calculation and optimization of minimum headway in moving block system. In: 2020 IEEE 5th International Conference on Intelligent Transportation Engineering, ICITE. September, 2020. Beijing; China. No. 9231437. P. 482-486.
  • 14. Landex, A. & Jensen, L.W. Infrastructure capacity in the ERTMS signaling system. In: 8th International Conference on Railway Operations Modelling and Analysis – Rail. 2019. Norrkoping, Sweden.
  • 15. Estil-les, C. & Sacile R. & et al. High-speed train scheduling and rescheduling models. In: 2020 IEEE 15th International Conference of System of Systems Engineering (SoSE). 2020. P. 331-336.
  • 16. Ljubaj, I. & et al. Possibility of increasing the railway capacity of the R106 regional liny by using a simulation tool. Transportation Research Procedia. 2020. Vol. 44. P. 137-144.
  • 17. Li Ch. & et al. Robust cooperative control of networked train platoons: a negative-imaginary systems’ perspective. IEEE Transactions on Control of Network Systems. 2021. Vol. 8. No. 4.
  • 18. Gao, M. & Zhou, L. & Chen, Y. An alternative approach for high speed railway carrying capacity calculation based on multiagent simulation. Discrete Dynamics in Nature and Society. 2016. Vol. 2016. Article ID 4278073.
  • 19. Shakhar, S. & Singh, A. & et al. Development of a railway junction simulator for evaluation of control strategies and capacity utilization optimization. In: 2019 Fifth Indian Control Conference (ICC). 9-11 Jan. 2019. Delhi, India.
  • 20. Dunbar, R. & Roberts, C. & Zhao, N. A tool for the rapid selection of a railway signalling strategy to implement train control optimization for energy saving. Journal of Rail Transport Planning & Management. 2017. Vol. 7. P. 224-244.
  • 21. Shakibayifar, M. & Sheikholeslami, A. & Corman, F. A simulation-based optimization approach to rescheduling train traffic in uncertain conditions during disruptions. Scientia Iranica Transactions A: Civil Engineering. 2018. Vol. 25. P. 646-662.
  • 22. Shakibayifar, M. & Hassannayebi, E. & et al. An intelligent simulation platform for train traffic control under disturbance. International Journal of Modelling and Simulation. 2019. Vol. 38. No. 3. P. 135-156.
  • 23. Hassan, A.H. & Nicholson, G.L. & Roberts C. Impact of train positioning inaccuracies on railway traffic management systems: framework development and impacts on TMS functions. IET Intell. Transp. Syst. 2020. Vol. 14. No. 6. P. 534-544.
  • 24. Zappacosta, C. & Vetruccio, S. & Mancini, G. A simulation environment for railway dynamics and signalling, aimed to European certification of safe vital computers. In: 2018 AEIT International Annual Conference. 3-5 Oct. 2018. Bari, Italy.
  • 25. Onischenko, A.A. & Chenykh, I.V. Development a simulation model of automatic locomotive signaling continuous type of action. In: 2019 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon). 1-4 Oct. 2019. Vladivostok, Russia.
  • 26. Abate, C. & Campanile L. & Marrone, S. A flexible simulation-based framework for modelbased/data-driven dependability evaluation. In: 2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW). 12-15 Oct. 2020. Coimbra, Portugal.
  • 27. Szpytko, J. & Salgado Duearte, Y. Robust simulation method of complex technical transport systems. Transport Problems. 2021. Vol. 16. No. 2. P. 101-112.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fe25d5d7-d8ff-4aa1-a861-a6b3a494aa52
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