Evaluation of intelligent transportation system implementation alternatives in metaverse using a Fermatean fuzzy distance measure-based OCRA model

INFORMATION SCIENCES(2024)

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摘要
The concept of the Metaverse, an immersive simulated world with parallels to reality, has gained significant prominence in recent times. Initially popularized through gaming, the Metaverse is now poised to infiltrate various aspects of human life. Intelligent transportation systems represent a promising yet challenging domain for Metaverse integration. Alternative implementations can create challenges in different dimensions. A comprehensive evaluation that takes challenges and opportunities for the different dimensions into account is required in decision making process of choosing the best implementation method. This study presents the development of a novel evaluation model, the Fermatean Fuzzy Operational Competitiveness Rating (OCRA) model, which incorporates the Fermatean Fuzzy Distance Measure (FF-DM) and Relative Closeness Coefficient (FF-RCC) techniques. The model is tested in a case to rank three alternative approaches, considering criteria of four key dimensions: managerial, safety, user, and urban mobility. In the first stage, the FF-DM and FF-RCC-based tool is employed to determine the criteria weights. In the second stage, an enhanced version of the Fermatean Fuzzy OCRA model, utilizing FF-DM and FFRCC, is employed to rank the alternatives. The findings indicate that policymakers' decisions in traffic management hold the potential to shape the trajectory of the Metaverse movement, representing an unparalleled opportunity with implications that extend beyond our current comprehension.
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关键词
Intelligent transportation systems,Metaverse,Traffic management,Fermatean fuzzy sets,Multi-criteria decision-making,Operational competitiveness rating
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