A fermatean fuzzy SWARA-TOPSIS methodology based on SCOR model for autonomous vehicle parking lot selection

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dc.authoridAYYILDIZ, ERTUGRUL/0000-0002-6358-7860
dc.contributor.authorAyyildiz, Ertugrul
dc.contributor.authorErdogan, Melike
dc.date.accessioned2025-10-11T20:48:37Z
dc.date.available2025-10-11T20:48:37Z
dc.date.issued2024
dc.departmentDüzce Üniversitesien_US
dc.description.abstractPopulation growth in crowded cities and the resulting increase in vehicle use have led to the problem of insufficient parking. When public parking lots and urban growth are not in coordination, vehicles park on the street and close the crosswalks. In the coming years, this problem will become more complicated with the addition of autonomous vehicles (AVs) to urban traffic. This study addresses the research question of how to effectively select AV parking lots in urban areas experiencing population growth and increased vehicle usage. For this aim, a hybrid Multi-Criteria Decision Making (MCDM) methodology, combining SWARA (Step-wise Weight Assessment Ratio Analysis) and TOPSIS (Technique for Order Preference by Similarity) approaches in a Fermatean Fuzzy (FF) environment is proposed. The decision hierarchy based on the SCOR model has been developed to determine and construct the evaluation criteria. Then, a case study analysis has been applied to selected districts in Istanbul, which is Turkiye's most populous and developing city. Operating expenses, safety and security, and land costs are determined as the most important factors. As a result of the detailed fuzzy analysis, which districts should primarily be chosen for AV parking lots in Istanbul is determined and finally, the robustness and validity of the results obtained by the sensitivity analysis being questioned. The study contributes by providing insights into AV parking lot selection, demonstrating the efficacy of the proposed methodology, and highlighting the importance of addressing this issue in urban planning.en_US
dc.description.sponsorshipKaradeniz Technical University Scientific Research Projects Coordination Unit [FBA-2023-10771]en_US
dc.description.sponsorshipFunding This work is supported by Karadeniz Technical University Scientific Research Projects Coordination Unit. Project Number: FBA-2023-10771.en_US
dc.identifier.doi10.1016/j.asoc.2024.112198
dc.identifier.issn1568-4946
dc.identifier.issn1872-9681
dc.identifier.scopus2-s2.0-85204402618en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.asoc.2024.112198
dc.identifier.urihttps://hdl.handle.net/20.500.12684/22016
dc.identifier.volume166en_US
dc.identifier.wosWOS:001313505500001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofApplied Soft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_WOS_20250911
dc.subjectAutonomous vehiclesen_US
dc.subjectDecision analysisen_US
dc.subjectFermatean Fuzzy Setsen_US
dc.subjectParking lot selectionen_US
dc.titleA fermatean fuzzy SWARA-TOPSIS methodology based on SCOR model for autonomous vehicle parking lot selectionen_US
dc.typeArticleen_US

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