The Metaverse is a concept used to refer to a virtual world that exists in parallel to the physical world. It has grown from a conceptual level to having real applications in virtual reality games. The applicability of the Metaverse in numerous sectors like marketing, education, social, and even advertising exists. However, there exists little or no work on Metaverse applicability to the transportation industry. Data-driven intelligent transportation systems (DDITS) aim to provide more intelligent systems based on exploiting data. This paper reviews the concepts and features of the Metaverse. Also, the review goes over three dominant DDITS challenges: vehicle fault detection and repair, testing new technologies, and anti-theft systems. In addition, it highlights prospective Metaverse solutions that apply to the DDITS. Buttressing the utility of Metaverse in DDITS, this paper presents two major case studies: the invisible to visible (I2V) and the Metaverse on Wheels (MoW) technologies. Finally, the influence, limitations, and open issues of Metaverse applications to DDITS are discussed. 

Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems

Evaluation of Metaverse integration of freight fluidity measurement alternatives using fuzzy Dombi EDAS model

Blockchain technology and metaverse advancements allow people to create virtual personalities and spend time online. Integrating public transportation into the metaverse could improve services and collect user data. This article introduces a hybrid decision-making framework for prioritizing sustainable public transportation in Metaverse under q-rung orthopair fuzzy set (q-ROFS) context. In this regard, first, q-rung orthopair fuzzy (q-ROF) generalized Dombi weighted aggregation operators and their characteristics are developed to aggregate the q-ROF information. Second, a q-ROF information-based method using the removal effects of criteria and stepwise weight assessment ratio analysis models are proposed to find the objective and subjective weights of criteria, respectively. Then, a combined weighting model is taken to determine the final weights of the criteria. Third, the weighted sum product method is extended to q-ROFS context by considering the double normalization procedures, the proposed operators and integrated weighting model. This method has taken the advantages of two normalization processes and four utility measures that approve the effect of benefit and cost criteria by using weighted sum and weighted product models. Next, to demonstrate the practicality and effectiveness of the presented method, a case study of sustainable public transportation in metaverse is presented in the context of q-ROFSs. The findings of this article confirms that the proposed model can recommend more feasible performance while facing numerous influencing factors and input uncertainties, and thus, provides a wider range of applications.

https://nottingham-repository.worktribe.com/preview/8952675/Metaverse_TFS_v1.pdf

A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse

Blockchain technology and metaverse advancements allow people to create virtual personalities and spend time online. Integrating public transportation into the metaverse could improve services and collect user data. This article introduces a hybrid decision-making framework for prioritizing sustainable public transportation in Metaverse under q-rung orthopair fuzzy set (q-ROFS) context. In this regard, first, q-rung orthopair fuzzy (q-ROF) generalized Dombi weighted aggregation operators and their characteristics are developed to aggregate the q-ROF information. Second, a q-ROF information-based method using the removal effects of criteria and stepwise weight assessment ratio analysis models are proposed to find the objective and subjective weights of criteria, respectively. Then, a combined weighting model is taken to determine the final weights of the criteria. Third, the weighted sum product method is extended to q-ROFS context by considering the double normalization procedures, the proposed operators and integrated weighting model. This method has taken the advantages of two normalization processes and four utility measures that approve the effect of benefit and cost criteria by using weighted sum and weighted product models. Next, to demonstrate the practicality and effectiveness of the presented method, a case study of sustainable public transportation in metaverse is presented in the context of q-ROFSs. The findings of this article confirms that the proposed model can recommend more feasible performance while facing numerous influencing factors and input uncertainties, and thus, provides a wider range of applications. 

/pdf/a-decision-support-system-for-assessing-and-prioritizing-2xtw4nr2.pdf

Digital forest recreation in the metaverse: Opportunities and challenges

A metaverse assessment model for sustainable transportation using ordinal priority approach and Aczel-Alsina norms

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. 

Ilgin Gokasar

Papers

A metaverse assessment model for sustainable transportation using ordinal priority approach and Aczel-Alsina norms

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

Safe E-scooter operation alternative prioritization using a q-rung orthopair Fuzzy Einstein based WASPAS approach

Fuzzy Einstein WASPAS Approach for the Economic and Societal Dynamics of the Climate Change Mitigation Strategies in Urban Mobility Planning

A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse