Personal Mobility in Metaverse With Autonomous Vehicles Using Q-Rung Orthopair Fuzzy Sets Based OPA-RAFSI Model

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题名:	Personal Mobility in Metaverse With Autonomous Vehicles Using Q-Rung Orthopair Fuzzy Sets Based OPA-RAFSI Model
作者:	Dev, Muhammet;Deveci, Muhammet;Pamuc, Dragan;Pamucar, Dragan;Gokas, Ilgin;Gokasar, Ilgin;Koppen, Mario;Koppen, Mario;Bhoosha, Brij;Gupta, Brij Bhooshan
贡献者:	資訊電機學院資訊工程學系
关键词:	Metaverse , Autonomous vehicles , Decision making , Costs , Avatars , Safety , Fuzzy sets
日期:	2022-07-01
上传时间:	2023-03-29 02:49:36 (UTC+0)
出版者:	亞洲大學
摘要:	The term metaverse, which shows a 3D-designed virtual medium where people can connect through their avatars to spend time, telecommute, and socialize, has entered our lives fast. There are limitless implementations that can take place in the metaverse. Integration of another technological innovation, which is autonomous vehicles to the metaverse, is at hand. There are numerous alternative uses of autonomous vehicles in the metaverse. In this study, three alternative implementation options for autonomous vehicles in the metaverse are investigated. These alternatives are evaluated using the proposed multi-criteria decision-making (MCDM) method under twelve different criteria, which are grouped under four main aspects, namely technological, societal, legal and ethical, and transportation. A novel hybrid model based on q-rung orthopair fuzzy sets (q-ROFSs) which consists of three stages is presented to express the framework definition, calculate the weight coefficients of the criteria, and rank various alternatives. In the first stage, the structure of the problem is created. In the second stage, q-ROFSs based OPA algorithm is used to calculate the weights of the criteria. In the last stage, q-ROFSs based RAFSI (Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval) is applied to choose the best alternative among the three alternatives. Finally, we present a case study to verify our proposed method. The results of this study have the potential to be used as a guide by decision-makers of the metaverse while integrating autonomous vehicles into the transportation system.
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