IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i20p9101-d1771034.html
   My bibliography  Save this article

A New Methodology for Optimising Railway Line Capacity: Improving Infrastructure for Sustainable Transport

Author

Listed:
  • Jozef Gašparík

    (Department of Railway Transport, University of Žilina, Univerzitná 8215/1010 26, 010 26 Žilina, Slovakia)

  • Marek Vyhnanovský

    (Department of Transport Technology and Control, University of Pardubice, Studentská 95, 532 10 Pardubice, Czech Republic)

  • Martin Vojtek

    (Department of Transport Technology and Control, University of Pardubice, Studentská 95, 532 10 Pardubice, Czech Republic)

  • Petr Nachtigall

    (Department of Transport Technology and Control, University of Pardubice, Studentská 95, 532 10 Pardubice, Czech Republic)

  • Milan Dedík

    (Department of Railway Transport, University of Žilina, Univerzitná 8215/1010 26, 010 26 Žilina, Slovakia)

Abstract

The sufficient capacity of railway lines is a key prerequisite for stable and sustainable transport, not only on main or high-speed lines, but also on lines of regional importance that complement the network. Their indispensable role is manifested not only daily, but especially in the event of incidents on the backbone network. One of the main characteristics of these support lines is that they are largely single-track. Another important characteristic is that they alternate between sections with different traffic loads, which significantly changes the capacity requirements along the whole line. Existing modernisation approaches are frequently implemented in a non-differentiated manner, thereby lacking segment-specific prioritisation. The present paper introduces a novel methodology for systematic identification and the ranking of line sections for capacity upgrades. The approach is comprised of three distinct steps: first, the line is segmented using traffic homogeneity criteria; second, limiting journey times are determined through analytical capacity calculations based on the ninth decile of train volumes; and third, infrastructure measures are identified when the actual journey times exceed these thresholds. Potential interventions encompass the introduction of additional block sections, the implementation of passing loops, or the introduction of double-tracking. The methodology was applied to the Havlíčkův Brod–Jihlava–Znojmo line, thereby demonstrating its ability to detect bottlenecks and propose targeted measures. The findings indicate that there is considerable potential for enhancing capacity while concomitantly improving operational safety and cost efficiency. Consequently, this will serve to reinforce the role of diversionary lines within the broader context of the rail network. The proposed framework provides infrastructure managers with a generalisable tool with which to prioritise investments and support the long-term development of resilient and sustainable railway systems.

Suggested Citation

  • Jozef Gašparík & Marek Vyhnanovský & Martin Vojtek & Petr Nachtigall & Milan Dedík, 2025. "A New Methodology for Optimising Railway Line Capacity: Improving Infrastructure for Sustainable Transport," Sustainability, MDPI, vol. 17(20), pages 1-17, October.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:20:p:9101-:d:1771034
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/20/9101/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/20/9101/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eliasson, Jonas & Börjesson, Maria, 2014. "On timetable assumptions in railway investment appraisal," Transport Policy, Elsevier, vol. 36(C), pages 118-126.
    2. Marinella Giunta, 2023. "Trends and Challenges in Railway Sustainability: The State of the Art regarding Measures, Strategies, and Assessment Tools," Sustainability, MDPI, vol. 15(24), pages 1-19, December.
    3. Jaromír Široký & Petr Nachtigall & Erik Tischer & Jozef Gašparík, 2021. "Simulation of Railway Lines with a Simplified Interlocking System," Sustainability, MDPI, vol. 13(3), pages 1-16, January.
    4. Burdett, Robert L., 2015. "Multi-objective models and techniques for analysing the absolute capacity of railway networks," European Journal of Operational Research, Elsevier, vol. 245(2), pages 489-505.
    5. Mussone, Lorenzo & Wolfler Calvo, Roberto, 2013. "An analytical approach to calculate the capacity of a railway system," European Journal of Operational Research, Elsevier, vol. 228(1), pages 11-23.
    6. Burdett, RL, 2016. "Optimisation models for expanding a railway's theoretical capacity," European Journal of Operational Research, Elsevier, vol. 251(3), pages 783-797.
    7. Zdenko Kljaić & Danijel Pavković & Mihael Cipek & Maja Trstenjak & Tomislav Josip Mlinarić & Mladen Nikšić, 2023. "An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency, Safety, and Sustainability of Railway Transport," Future Internet, MDPI, vol. 15(11), pages 1-44, October.
    8. Abril, M. & Barber, F. & Ingolotti, L. & Salido, M.A. & Tormos, P. & Lova, A., 2008. "An assessment of railway capacity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 774-806, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Feng & Gao, Ziyou & Wang, David Z.W. & Liu, Ronghui & Tang, Tao & Wu, Jianjun & Yang, Lixing, 2017. "A subjective capacity evaluation model for single-track railway system with δ-balanced traffic and λ-tolerance level," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 43-66.
    2. Jovanović, Predrag & Pavlović, Norbert & Belošević, Ivan & Milinković, Sanjin, 2020. "Graph coloring-based approach for railway station design analysis and capacity determination," European Journal of Operational Research, Elsevier, vol. 287(1), pages 348-360.
    3. Burdett, RL, 2016. "Optimisation models for expanding a railway's theoretical capacity," European Journal of Operational Research, Elsevier, vol. 251(3), pages 783-797.
    4. Line Blander Reinhardt & David Pisinger & Richard Lusby, 2018. "Railway capacity and expansion analysis using time discretized paths," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 712-739, December.
    5. Bevrani, Bayan & Burdett, Robert L. & Bhaskar, Ashish & Yarlagadda, Prasad K.D.V., 2017. "A capacity assessment approach for multi-modal transportation systems," European Journal of Operational Research, Elsevier, vol. 263(3), pages 864-878.
    6. Francesco Rotoli & Elena Navajas Cawood & Antonio Soria, 2016. "Capacity assessment of railway infrastructure: Tools, methodologies and policy relevance in the EU context," JRC Research Reports JRC100509, Joint Research Centre.
    7. Masoud Yaghini & Mohammadreza Sarmadi & Nariman Nikoo & Mohsen Momeni, 2014. "Capacity Consumption Analysis Using Heuristic Solution Method for Under Construction Railway Routes," Networks and Spatial Economics, Springer, vol. 14(3), pages 317-333, December.
    8. Zdenka Bulková & Jozef Gašparík & Jaroslav Mašek & Vladislav Zitrický, 2022. "Analytical Procedures for the Evaluation of Infrastructural Measures for Increasing the Capacity of Railway Lines," Sustainability, MDPI, vol. 14(21), pages 1-28, November.
    9. Ait Ali, Abderrahman & Warg, Jennifer & Eliasson, Jonas, 2020. "Pricing commercial train path requests based on societal costs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 452-464.
    10. Bayan Bevrani & Robert L. Burdett & Ashish Bhaskar & Prasad K. D. V. Yarlagadda, 2020. "A multi commodity flow model incorporating flow reduction functions," Flexible Services and Manufacturing Journal, Springer, vol. 32(3), pages 693-723, September.
    11. Bevrani, Bayan & Burdett, Robert & Bhaskar, Ashish & Yarlagadda, Prasad K.D.V., 2020. "A multi-criteria multi-commodity flow model for analysing transportation networks," Operations Research Perspectives, Elsevier, vol. 7(C).
    12. Vytautas Grigonis & Mantas Kaušylas & Vytautas Palevičius, 2025. "Advancing Sustainable Interoperability Between Standard and Broad-Gauge Railway Systems," Sustainability, MDPI, vol. 17(18), pages 1-15, September.
    13. Ortega Riejos, Francisco A. & Barrena, Eva & Canca Ortiz, J. David & Laporte, Gilbert, 2016. "Analyzing the theoretical capacity of railway networks with a radial-backbone topology," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 83-92.
    14. Behiri, Walid & Belmokhtar-Berraf, Sana & Chu, Chengbin, 2018. "Urban freight transport using passenger rail network: Scientific issues and quantitative analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 227-245.
    15. Coviello, Nicola, 2015. "Modelling periodic operations on single track lines: Timetable design and stability evaluation," Research in Transportation Economics, Elsevier, vol. 54(C), pages 2-14.
    16. Xu, Xin-yue & Liu, Jun & Li, Hai-ying & Jiang, Man, 2016. "Capacity-oriented passenger flow control under uncertain demand: Algorithm development and real-world case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 130-148.
    17. Burdett, Robert & Kozan, Erhan, 2016. "A multi-criteria approach for hospital capacity analysis," European Journal of Operational Research, Elsevier, vol. 255(2), pages 505-521.
    18. Maosheng Li & Zhengqiu Liu & Yonghong Zhang & Weijun Liu & Feng Shi, 2017. "Distribution analysis of train interval journey time employing the censored model with shifting character," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(4), pages 715-733, March.
    19. Chen, Zebin & Li, Shukai & D’Ariano, Andrea & Yang, Lixing, 2022. "Real-time optimization for train regulation and stop-skipping adjustment strategy of urban rail transit lines," Omega, Elsevier, vol. 110(C).
    20. Börjesson, Maria, 2014. "Forecasting demand for high speed rail," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 81-92.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:20:p:9101-:d:1771034. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.