An interlocking system determining the configuration of rail traffic control elements to ensure safety

Antonio Hernando; Gabriel Aguilera-Venegas; José Luis Galán-García; Sheida Nazary; Antonio Hernando; Gabriel Aguilera-Venegas; José Luis Galán-García; Sheida Nazary

doi:10.3934/math.20241043

AIMS Mathematics

2024, Volume 9, Issue 8: 21471-21495. doi: 10.3934/math.20241043

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An interlocking system determining the configuration of rail traffic control elements to ensure safety

1.
Depto. de Sistemas Informáticos, E.T.S.I. de Sistemas Informáticos, Universidad Politécnica de Madrid, Madrid, Spain
2.
Departamento de Matemática Aplicada, Escuela de Ingenierías Industriales, Universidad de Málaga, Málaga, Spain

Received: 29 March 2024 Revised: 25 June 2024 Accepted: 01 July 2024 Published: 04 July 2024
MSC : 13P05

Railway interlocking systems are essential safety components in rail transportation, designed to prevent train collisions. They regulate the transitions between sections of a railway station using rail traffic control elements. An interlocking system can assess whether the configuration of these control elements poses a collision risk. Over the years, researchers have developed various algebraic models to tackle this issue, highlighting the potential use of computer algebra systems in implementing interlocking systems. In this work, we aim to enhance these systems' capabilities. Not only will they indicate whether a situation is dangerous, but if it is, they will also provide guidance on how to configure certain rail traffic control elements to ensure safety. In this paper, we introduce an algebraic model that represents the railway station through polynomials. This approach transforms the task of identifying dangerous situations into calculating the residue of a polynomial over a set of polynomials. The monomials contained in this residue polynomial encode all possible configurations that would render the situation safe.
- railway interlocking system,
- computer algebra,
- decision making,
- commutative algebra
Citation: Antonio Hernando, Gabriel Aguilera-Venegas, José Luis Galán-García, Sheida Nazary. An interlocking system determining the configuration of rail traffic control elements to ensure safety[J]. AIMS Mathematics, 2024, 9(8): 21471-21495. doi: 10.3934/math.20241043

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Abstract

Railway interlocking systems are essential safety components in rail transportation, designed to prevent train collisions. They regulate the transitions between sections of a railway station using rail traffic control elements. An interlocking system can assess whether the configuration of these control elements poses a collision risk. Over the years, researchers have developed various algebraic models to tackle this issue, highlighting the potential use of computer algebra systems in implementing interlocking systems. In this work, we aim to enhance these systems' capabilities. Not only will they indicate whether a situation is dangerous, but if it is, they will also provide guidance on how to configure certain rail traffic control elements to ensure safety. In this paper, we introduce an algebraic model that represents the railway station through polynomials. This approach transforms the task of identifying dangerous situations into calculating the residue of a polynomial over a set of polynomials. The monomials contained in this residue polynomial encode all possible configurations that would render the situation safe.

References

[1]	N. Bešinović, Resilience in railway transport systems: A literature review and research agenda, Transport Rev., 40 (2020), 457–478. https://doi.org/10.1080/01441647.2020.1728419 doi: 10.1080/01441647.2020.1728419
[2]	Y. Zhou, J. Wang, H. Yang, Resilience of transportation systems: concepts and comprehensive review, IEEE T. Intell. Transp. Syst., 20 (2019), 4262–4276. https://doi.org/10.1109/TITS.2018.2883766 doi: 10.1109/TITS.2018.2883766
[3]	J. Pachl, Railway signalling principles, 2021. Available from: http://www.joernpachl.de/rsp.htm.
[4]	K. Winter, W. Johnston, P. Robinson, P. Strooper, L. van den Berg, Tool support for checking railway interlocking designs, in 10th Australian Workshop on Safety Re-lated Programmable Systems (SCS'05), Australian Computer Society, Sydney, 55 (2006), 101–107. Available from: https://crpit.scem.westernsydney.edu.au/confpapers/CRPITV55Winter.pdf.
[5]	A. Borälv, Case study: formal verification of a computerized railway interlocking, Formal Aspects Comput., 10 (1998), 338–360. https://doi.org/10.1007/s001650050021 doi: 10.1007/s001650050021
[6]	Anonymous, Proyecto y obra del enclavamiento electrónico de la estación de Madrid-Atocha, Proyecto Técnico, Siemens, Madrid, 1988.
[7]	Anonymous, Microcomputer interlocking hilversum, Siemens, Munich, 1986.
[8]	Anonymous, Microcomputer interlocking rotterdam, Siemens, Munich, 1989.
[9]	Anonymous, Puesto de enclavamiento con microcomputadoras de la estación de Chiasso de los SBB, Siemens, Munich, 1989.
[10]	L. Villamandos, Sistema informático concebido por Renfe para diseñar los enclavamientos, Vía Libre, 348 (1993), 65.
[11]	J. Peleska, N. Krafczyk, A. E. Haxthausen, R. Pinger, Efficient data validation for geographical interlocking systems, Formal Aspects Comput., 33 (2021), 925–955. https://doi.org/10.1007/s00165-021-00551-6 doi: 10.1007/s00165-021-00551-6
[12]	A. Fantechi, A. E. Haxthausen, M. B. R. Nielsen, Model checking geographically distributed interlocking systems using UMC, in 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), (2017), 278–286. https://doi.org/10.1109/PDP.2017.66
[13]	D. Bjørner, The FMERail/TRain Annotated Rail Bibliography, 1999. Available from: http://www2.imm.dtu.dk/db/fmerail/fmerail/
[14]	H. Lian, X. Wang, A. Sharma, M. A. Shah, Application and study of artificial intelligence in railway signal interlocking fault, Informatica, 46 (2022), 343–354. https://doi.org/10.31449/inf.v46i3.3961 doi: 10.31449/inf.v46i3.3961
[15]	A. Fantechi, G. Gori, A. E. Haxthausen, C. Limbrée, Compositional verification of railway interlockings: comparison of two methods, in Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification, (2022), 3–19. https://doi.org/10.1007/978-3-031-05814-1_1
[16]	G. Lukács, T. Bartha, Conception of a formal model-based methodology to support railway engineers in the specification and verification of interlocking systems, in 2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI), (2022), 000283–000288. https://doi.org/10.1109/SACI55618.2022.9919532
[17]	M. J. Morley, Modelling British Rail's Interlocking Logic: Geographic Data Correctness, LFCS, Department of Computer Science, University of Edinburgh, 1991.
[18]	K. Nakamatsu, Y. Kiuchi, A. Suzuki, EVALPSN based railway interlocking simulator, in Knowledge-Based Intelligent Information and Engineering Systems, Berlin - Heidelberg, (2004), 961–967. https://doi.org/10.1007/978-3-540-30133-2_127
[19]	A. Janota, Using Z specification for railway interlocking safety, Period. Polytech. Transp. Eng., 28 (2000), 39–53. Available from: https://pp.bme.hu/tr/article/view/1963.
[20]	K. M. Hansen, Formalising railway interlocking systems, in Nordic Seminar on Dependable Computing Systems, Lyngby, (1994), 83–94.
[21]	M. Montigel, Modellierung und Gewährleistung von Abhängigkeiten in Eisenbahnsicherungsanlagen, Ph.D. Thesis, ETH Zurich, Zurich, 1994. Available from: http://www.inf.ethz.ch/research/disstechreps/theses.
[22]	X. Chen, H. Huang, Y. He, Automatic generation of relay logic for interlocking system based on statecharts, in 2010 Second World Congress on Software Engineering, (2010), 183–188. https://doi.org/10.1109/WCSE.2010.31
[23]	X. Chen, Y. He, H. Huang, An approach to automatic development of interlocking logic based on Statechart, Enterp. Inf. Syst., 5 (2011), 273–286. https://doi.org/10.1080/17517575.2011.575475 doi: 10.1080/17517575.2011.575475
[24]	X. Chen, Y. He, H. Huang, A component-based topology model for railway interlocking systems, Math. Comput. Simul., 81 (2011), 1892–1900. https://doi.org/10.1016/j.matcom.2011.02.007 doi: 10.1016/j.matcom.2011.02.007
[25]	B. Luteberget, C. Johansen, Efficient verification of railway infrastructure designs against standard regulations, Form. Method. Syst. Des., 52 (2018), 1–32. https://doi.org/10.1007/s10703-017-0281-z doi: 10.1007/s10703-017-0281-z
[26]	M. Bosschaart, E. Quaglietta, B. Janssen, R. M. P. Goverde, Efficient formalization of railway interlocking data in RailML, Inf. Syst., 49 (2015), 126–141. https://doi.org/10.1016/j.is.2014.11.007 doi: 10.1016/j.is.2014.11.007
[27]	E. Roanes-Lozano, L. M. Laita, An applicable topology-independent model for railway interlocking systems, Math. Comput. Simul., 45 (1998), 175–183. https://doi.org/10.1016/S0378-4754(97)00093-1 doi: 10.1016/S0378-4754(97)00093-1
[28]	E. Roanes-Lozano, E. Roanes-Macías, L. Laita, Railway interlocking systems and Gröbner bases, Math. Comput. Simul., 51 (2000), 473–481. https://doi.org/10.1016/S0378-4754(99)00137-8 doi: 10.1016/S0378-4754(99)00137-8
[29]	E. Roanes-Lozano, A. Hernando, J. A. Alonso, L. M. Laita, A logic approach to decision taking in a railway interlocking system using Maple, Math. Comput. Simul., 82 (2011), 15–28. https://doi.org/10.1016/j.matcom.2010.05.024 doi: 10.1016/j.matcom.2010.05.024
[30]	A. Hernando, E. Roanes-Lozano, R. Maestre-Martínez, J. Tejedor, A logic-algebraic approach to decision taking in a railway interlocking system, Ann. Math. Artif. Intell., 65 (2012), 317–328. https://doi.org/10.1007/s10472-012-9321-y doi: 10.1007/s10472-012-9321-y
[31]	E. Roanes-Lozano, J. A. Alonso, A. Hernando, An approach from answer set programming to decision making in a railway interlocking system, Rev. R. Acad. Cienc. Exactas, Fis. Nat. Ser. A Mat., 108 (2014), 973–987. https://doi.org/10.1007/s13398-013-0155-1 doi: 10.1007/s13398-013-0155-1
[32]	A. Hernando, R. Maestre, E. Roanes-Lozano, A new algebraic approach to decision making in a railway interlocking system based on preprocess, Math. Probl. Eng., 2018 (2018), 4982974. https://doi.org/10.1155/2018/4982974 doi: 10.1155/2018/4982974
[33]	D. Cox, J. Little, D. O'Shea, Ideals, Varieties and Algorithms, Springer, 2015. Available from: https://link.springer.com/book/10.1007/978-3-319-16721-3.
[34]	A. Hernando, E. Roanes-Lozano, An algebraic model for implementing expert systems based on the knowledge of different experts, Math. Comput. Simul., 107 (2015), 92–107. https://doi.org/10.1016/j.matcom.2014.05.003 doi: 10.1016/j.matcom.2014.05.003
[35]	A. Hernando, E. Roanes-Lozano, J. L. Galán-García, G. Aguilera-Venegas, Decision making in railway interlocking systems based on calculating the remainder of dividing a polynomial by a set of polynomials, Electron. Res. Arch., 31 (2023), 6160–6196. https://doi.org/10.3934/era.2023313 doi: 10.3934/era.2023313
[36]	J. Abbott, A. M. Bigatti, CoCoALib: a C++ library for doing Computations in Commutative Algebra, 2019. Available from: http://cocoa.dima.unige.it/cocoalib

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