A New Fuzzy MARCOS Method for Road Traffic Risk Analysis
Miomir Stanković,
Željko Stević,
Dillip Kumar Das,
Marko Subotić and
Dragan Pamučar
Additional contact information
Miomir Stanković: Mathematical Institute of the Serbian Academy of Sciences and Arts, 11001 Belgrade, Serbia
Željko Stević: Faculty of Transport and Traffic Engineering, University of East Sarajevo, 74000 Doboj, Bosnia and Herzegovina
Dillip Kumar Das: Civil Engineering, School of Engineering, University of Kwazulu Natal, Durban 4041, South Africa
Marko Subotić: Faculty of Transport and Traffic Engineering, University of East Sarajevo, 74000 Doboj, Bosnia and Herzegovina
Dragan Pamučar: Department of Logistics, University of Defence in Belgrade, 11000 Belgrade, Serbia
Mathematics, 2020, vol. 8, issue 3, 1-18
Abstract:
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.
Keywords: Fuzzy MARCOS; Fuzzy PIPRECIA; traffic risk; TFN; MCDM (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)
Downloads: (external link)
https://www.mdpi.com/2227-7390/8/3/457/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/3/457/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:8:y:2020:i:3:p:457-:d:336588
Access Statistics for this article
Mathematics is currently edited by Ms. Emma He
More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().