Risk Analysis of Level Crossing Element Failures in a Fuzzy Environment

Milivoje ILIĆ; Đorđe MAKSIMOVIĆ; Norbert PAVLOVIĆ; Ivan BELOŠEVIĆ

doi:10.7307/ptt.v36i5.560

Authors

Milivoje ILIĆ University of Belgrade, Faculty of Transport and Traffic Engineering
Đorđe MAKSIMOVIĆ Institute Mihailo Pupin
Norbert PAVLOVIĆ University of Belgrade, Faculty of Transport and Traffic Engineering
Ivan BELOŠEVIĆ University of Belgrade, Faculty of Transport and Traffic Engineering

DOI:

https://doi.org/10.7307/ptt.v36i5.560

Keywords:

level crossing, risk analysis, failure modes and effects analysis (FMEA), fuzzy approach, TOPSIS

Abstract

The concept of risk analysis is especially important because it examines and analyses in a detailed manner the factors that affect the normal functioning of a system. In this paper, the level crossing is considered as one system, composed of several elements. The failures of those elements were analysed with the aim of showing which are the most frequent and most critical failures. A multi-methodological approach was used in the analysis. The failure modes and effects analysis (FMEA) method was used to determine risk factors, after that a multi-criteria model was created in a fuzzy environment, and as output, it gave a ranking list of critical failures in the system. Through the discussion of the results, a comparison of the basic model with two other similar ones was made, and the comparative results were analysed. The main aim of this paper is to present one of the possible ways to analyse the risk of the system of level crossings with the aim of improving traffic safety at the crossing.

References

Tordai L, Olpinski W, Schafer W, Wegele S. D1 - report about statistics, database analysis and regulations for level crossing, SELCAT (Safer European Level Crossing Appraisal and Technology). Paris, France, 2008.

Starčević M, Barić D, Pilko H. Survey-based impact of influencing parameters on level crossings safety. Promet - Traffic&Transportation. 2016;28(6):639–649. DOI:10.7307/ptt.v28i6.2208.

Pavlović N, Starčević M, Belošević I, Nikšić M. Safety at level crossing comparative analysis between Serbia and Croatia. (In Serbian) Železnice. 2022,67(2):57-67. https://www.casopis-zeleznice.rs/index.php/zeleznice/article/view/106/98 [Accessed 14th May 2024].

Ouyang L, Che Y, Yan L, Park C. Multiple perspectives on analyzing risk factors in FMEA. Computers in Industry. 2022;141:1–13. DOI:10.1016/j.compind.2022.103712.

Fu S, et al. Towards a probabilistic approach for risk analysis of nuclear-powered icebreakers using FMEA and FRAM. Ocean Engineering. 2022;260. DOI:10.1016/j.oceaneng.2022.112041.

Ebrahimi S, Vachal K, Szmerekovsky J. A Delphi-FMEA model to assess county-level speeding crash risk in North Dakota. Transportation Research Interdisciplinary Perspectives. 2022;16(1):1-11. DOI:10.1016/j.trip.2022.100688.

Liang C, Ghazel M, Cazier O, El-Koursi E. Risk analysis on level crossings using a causal Bayesian network based approach. WCTR 2016. Shanghai, China, 10–15 July 2016. DOI:10.1016/j.trpro.2017.05.418.

Nedeliakova E, Hranicky M, Valla M. Risk identification methodology regarding the safety and quality of railway services. Production Engineering Archives. 2022;28(1):21–29. DOI:10.30657/pea.2022.28.03.

Žitnikova I, Schwarz M, Bernatik A. Assessment of the risk of level crossings in the Moravian-Silesian region and proposed safety measures. Transactions of the VŠB - Technical University of Ostrava-Safety Engineering Series. 2011;6(1):48–54. https://core.ac.uk/download/pdf/8992474.pdf [Accessed 14th May 2024].

Milosavljević M, Kasalica S, Jeremić D, Vil G. Application of fuzzy TOPSIS method for selection the additional protecting system on railway crossing. Proceedings of the XVIII International Scientific-Expert Conference on Railways- RAILCON 2018. October 2018, Niš, Serbia. p. 57-60. 2018.

Berrado A, El-Koursi E, Cherkaoui A, Khaddour M. A framework for risk management in railway sector: Application to road-rail level crossings. Open Transportation Journal. 2010;5(1):34–44. DOI:10.2174/1874447801105010034.

Fayyaz MAB, Johnson C. Object detection at level crossing using deep learning. Micromachines. 2020;11(12):1055. DOI:10.3390/mi11121055.

Pamučar D, Lukovac V, Božanić D, Komazec N. Multi-criteria FUCOM-MAIRCA model for the evaluation of level crossings: Case study in the Republic of Serbia. Operational Research in Engineering Sciences: Theory and Applications. 2018;1(1):108–129. DOI:10.31181/oresta190120101108p.

Ballay M, Sventekova E, Kubiatko T, Macurova L. The impact of critical elements on the formation and consequences of accidents at railway crossings. Proceedings of 23rd International Scientific Conference Transport Means. Kaunas, Lithuania. 2019. https://www.tf.lbtu.lv/conference/proceedings2022/Papers/TF271.pdf [Accessed 14th May 2024].

Stamatis DH. Failure mode and effect analysis: FMEA from theory to execution, 2nd edition, ASQ Quality Press, Milwaukee, Wisconsin, USA. 2003.

Zadeh LA. Fuzzy sets. Information and Control. 1965;8(3):338–353. DOI:10.1016/S0019-9958(65)90241-X.

Bellman RE, Zadeh LA. Decision-making in a fuzzy environment. Management Science. 1970;17(4):141–164. DOI: 10.1287/mnsc.17.4.B141.

Mardani A, Jusoh A, Zavadskas EK. Fuzzy multiple criteria decision-making techniques and applications – Two decades review from 1994 to 2014. Expert System with Applications. 2015;42(8):4126–4148. DOI:10.1016/j.eswa.2015.01.003.

Shafabakhsh G, Hadjihoseinlou M, Taghizadeh SA. Selecting the appropriate public transportation system to access the Sari International airport by fuzzy decision making. European Transport Research Review. 2014;6(3):277–285. DOI:10.1007/s12544-013-0128-7.

Gajzler M, Zima K. Evaluation of planned construction projects using fuzzy logic. International Journal of Civil Engineering. 2017;15(4):641–652. DOI:10.1007/s40999-017-0177-8.

Cheng CH, Lin Y. Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research. 2002;142(1):174–186. DOI:10.1016/S0377-2217(01)00280-6.

Chen LY, Wang TC. Optimizing partners’ choice in IS/IT outsourcing projects: the strategic decision of fuzzy VIKOR. International Journal of Production Economics. 2009;120(1):233–242. DOI:10.1016/j.ijpe.2008.07.022.

Chen CT. Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems. 2000;114(1):1–9. DOI:10.1016/S0165-0114(97)00377-1.

Olson DL. Comparison of Weights in TOPSIS Models. Mathematical and Computer Modelling. 2004;40(7):721–727. DOI:10.1016/j.mcm.2004.10.003.

Saaty TL. How to make a decision: The analytic hierarchy process. European Journal of Operational Research. 1990;48(1):9–26. DOI:10.1016/0377-2217(90)90057-I.

Saaty TL. Fundamentals of decision making and priority theory with AHP, RWS Publications, Pittsburgh, Pennsylvania, USA. 1994.