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Open AccessArticle

A New Fuzzy MARCOS Method for Road Traffic Risk Analysis

1
Mathematical Institute of the Serbian Academy of Sciences and Arts, 11001 Belgrade, Serbia
2
Faculty of Transport and Traffic Engineering, University of East Sarajevo, 74000 Doboj, Bosnia and Herzegovina
3
Civil Engineering, School of Engineering, University of Kwazulu Natal, Durban 4041, South Africa
4
Department of Logistics, University of Defence in Belgrade, 11000 Belgrade, Serbia
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(3), 457; https://doi.org/10.3390/math8030457 (registering DOI)
Received: 20 February 2020 / Revised: 18 March 2020 / Accepted: 20 March 2020 / Published: 24 March 2020
(This article belongs to the Special Issue Dynamics under Uncertainty: Modeling Simulation and Complexity)
In this paper, a new fuzzy multi-criteria decision-making model for traffic risk assessment was developed. A part of a main road network of 7.4 km with a total of 38 Sections was analyzed with the aim of determining the degree of risk on them. For that purpose, a fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (fuzzy MARCOS) method was developed. In addition, a new fuzzy linguistic scale quantified into triangular fuzzy numbers (TFNs) was developed. The fuzzy PIvot Pairwise RElative Criteria Importance Assessment—fuzzy PIPRECIA method—was used to determine the criteria weights on the basis of which the road network sections were evaluated. The results clearly show that there is a dominant section with the highest risk for all road participants, which requires corrective actions. In order to validate the results, a comprehensive validity test was created consisting of variations in the significance of model input parameters, testing the influence of dynamic factors—of reverse rank, and applying the fuzzy Simple Additive Weighing (fuzzy SAW) method and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS). The validation test show the stability of the results obtained and the justification for the development of the proposed model. View Full-Text
Keywords: Fuzzy MARCOS; Fuzzy PIPRECIA; traffic risk; TFN; MCDM Fuzzy MARCOS; Fuzzy PIPRECIA; traffic risk; TFN; MCDM
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Stanković, M.; Stević, Ž.; Das, D.K.; Subotić, M.; Pamučar, D. A New Fuzzy MARCOS Method for Road Traffic Risk Analysis. Mathematics 2020, 8, 457.

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