Evaluation of two-lane road sections in terms of traffic risk using an integrated MCDM model
Abstract
The impact of geometric characteristics on traffic risk is reflected through identifying conflict points on roads,traffic accidents, and any other unforeseen situation that is inherently hazardous for traffic participants. In order to identify the road sections with the highest risk, it is necessary to consider a number of criteria that affect risk, and conduct extensive empirical research, analysis and data synthesis. This paper evaluates 9 sections of two-lane roads in the territory of Bosnia and Herzegovina (the Republic of Srpska) using an integrated Multi-Criteria Decision-Making (MCDM) model.To determine the significance of 8 criteria for the evaluation of the sections, it was applied a subjective–objective model consisting of 3 methods: (1) CRiteria Importance Through Inter-criteria Correlation (CRITIC), (2) FUll COnsistency Method (FUCOM) and (3) fuzzy PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA). The aggregation of the criterion values obtained using the methods yielded the final criterion values. Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS) method was used to evaluate the sections and determine their objective diversity. The obtained results identified one location as extremely hazardous by most of analysed input parameters. The section with the highest risk is the Rudanka – Doboj section (A4), which represents a section of the road infrastructure of the 105 road. The validation of the results obtained by applying the integrated MCDM model was performed through an extensive sensitivity analysis. The weights of criteria were observed through initially individual methods implemented in the MARCOS method. Then, a comparative analysis was performed with 6 other MCDM methods and Spearman’s Correlation Coefficient (SCC) was calculated as a statistical indicator of rank correlation in a sensitivity analysis. In addition,the Standard Deviation (STDEV) of the obtained results was determined.
Keyword : traffic risk, road sections, MARCOS, FUCOM, CRITIC, fuzzy PIPRECIA
How to Cite
Stević, Željko, Subotić, M., Tanackov, I., Sremac, S., Ristić, B., & Simić, S. (2022). Evaluation of two-lane road sections in terms of traffic risk using an integrated MCDM model. Transport, 37(5), 318–329. https://doi.org/10.3846/transport.2022.18243
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Hatefi, M. A. 2018. A multi-criteria decision analysis model on the fuels for public transport, with the use of hybrid ROC-ARAS method, Petroleum Business Review 2(1): 45–55.
Hwang, C.-L.; Yoon, K. 1981. Multiple Attribute Decision Making: Methods and Applications a State-of-the-Art Survey. Springer. 269 p. https://doi.org/10.1007/978-3-642-48318-9
Kanuganti, S.; Agarwala, R.; Dutta, B.; Bhanegaonkar, P. N.; Singh, A. P.; Sarkar, A. K. 2017. Road safety analysis using multi criteria approach: a case study in India, Transportation Research Procedia 25: 4649–4661. https://doi.org/10.1016/j.trpro.2017.05.299
Karabašević, D.; Popović, G.; Stanujkić, D.; Maksimović, M.; Sava, C. 2019. An approach for hotel type selection based on the single-valued intuitionistic fuzzy numbers, International Review (1–2): 7–14. https://doi.org/10.5937/intrev1901007K
Karlaftis, M. G.; Golias, I. 2002. Effects of road geometry and traffic volumes on rural roadway accident rates, Accident Analysis & Prevention 34(3): 357–365. https://doi.org/10.1016/s0001-4575(01)00033-1
Keshavarz Ghorabaee, M.; Amiri, M.; Zavadskas, E. K.; Antuchevičienė, J. 2017. Assessment of third-party logistics providers using a CRITIC–WASPAS approach with interval type-2 fuzzy sets, Transport 32(1): 66–78. https://doi.org/10.3846/16484142.2017.1282381
Keshavarz Ghorabaee, M.; Zavadskas, E. K.; Olfat, L.; Turskis, Z. 2015. Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS), Informatica 26(3): 435–451. https://doi.org/10.15388/Informatica.2015.57
Khan, S.; Haleem, A.; Khan, M. I. 2020. Analysing challenges towards development of smart city using WASPAS, Lecture Notes in Civil Engineering 58: 463–474. https://doi.org/10.1007/978-981-15-2545-2_39
Kulmala, R. 1994. Measuring the safety effect of road measures at junctions, Accident Analysis & Prevention 26(6): 781–794. https://doi.org/10.1016/0001-4575(94)90054-x
Liu, Z.; He, J.; Zhang, C.; Xing, L.; Zhou, B. 2020. The impact of road alignment characteristics on different types of traffic accidents, Journal of Transportation Safety & Security 12(5): 697–726. https://doi.org/10.1080/19439962.2018.1538173
Marković, V.; Stajić, L.; Stević, Ž.; Mitrović, G.; Novarlić, B.; Radojičić, Z. 2020. A novel integrated subjective-objective MCDM model for alternative ranking in order to achieve business excellence and sustainability, Symmetry 12(1): 164. https://doi.org/10.3390/sym12010164
Mayora, J. M. P.; Rubio, R. L. 2003. Relevant variables for crash rate prediction in Spain’s two lane rural roads, in Transportation Research Board 82nd Annual Meeting Compendium of Papers CD-ROM, 12–16 January 2003, Washington, DC, US. 24 p.
Morency, P.; Gauvin, L.; Plante, C.; Fournier, M.; Morency, C. 2012. Neighborhood social inequalities in road traffic injuries: the influence of traffic volume and road design, American Journal of Public Health 102(6): 1112–1119. https://doi.org/10.2105/ajph.2011.300528
Mountain, L.; Fawaz, B.; Jarrett, D. 1996. Accident prediction models for roads with minor junctions, Accident Analysis & Prevention 28(6): 695–707. https://doi.org/10.1016/S0001-4575(96)00042-5
Naeini, A. B.; Mosayebi, A.; Mohajerani, N. 2019. A hybrid model of competitive advantage based on Bourdieu capital theory and competitive intelligence using fuzzy Delphi and ISM-Gray DEMATEL (study of Iranian food industry), International Review (1–2): 21–35. https://doi.org/10.5937/intrev1901021N
Noureddine, M.; Ristic, M. 2019. Route planning for hazardous materials transportation: multicriteria decision making approach, Decision Making: Applications in Management and Engineering 2(1): 66–85.
Othman, S.; Thomson, R. 2007. Influence of road characteristics on traffic safety, in Proceedings of the 20th International Technical Conference on the Enhanced Safety of Vehicles (ESV), 18–21 June 2007, Lyon, France, Paper 07-0064, 1–10. Available from Internet: https://www-esv.nhtsa.dot.gov/Proceedings/20/07-0064-O.pdf
Pamučar, D.; Ćirović, G. 2015. The selection of transport and handling resources in logistics centers using multi-attributive border approximation area comparison (MABAC), Expert Systems with Applications 42(6): 3016–3028. https://doi.org/10.1016/j.eswa.2014.11.057
Pamučar, D.; Stević, Ž.; Sremac, S. 2018. A new model for determining weight coefficients of criteria in MCDM models: full consistency method (FUCOM), Symmetry 10(9): 393. https://doi.org/10.3390/sym10090393
Porter, R. J.; Donnell, E. T.; Mason, J. M. 2012. Geometric design, speed, and safety, Transportation Research Record: Journal of the Transportation Research Board 2309: 39–47. https://doi.org/10.3141/2309-05
Puška, A.; Stojanović, I.; Maksimović, A.; Osmanović, N. 2020. Evaluation software of project management by using measurement of alternatives and ranking according to compromise solution (MARCOS) method, Operational Research in Engineering Sciences: Theory and Applications 3(1): 89–102.
Räsänen, M. 2005. Effects of a rumble strip barrier line on lane keeping in a curve, Accident Analysis & Prevention 37(3): 575–581. https://doi.org/10.1016/j.aap.2005.02.001
Rostamzadeh, R.; Keshavarz-Ghorabaee, M.; Govindan, K.; Esmaeili, A.; Nobar, H. B. K. 2018. Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS-CRITIC approach, Journal of Cleaner Production 175: 651–669. https://doi.org/10.1016/j.jclepro.2017.12.071
Ruiz-Padillo, A.; Ruiz, D. P.; Torija, A. J.; Ramos-Ridao, Á. 2016. Selection of suitable alternatives to reduce the environmental impact of road traffic noise using a fuzzy multi-criteria decision model, Environmental Impact Assessment Review 61: 8–18. https://doi.org/10.1016/j.eiar.2016.06.003
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