@revista_internacional{897, keywords = {Metaverse, Connected autonomous vehicles, Real-time traffic management, Fuzzy sets, multi-criteria decision making, Self-powered sensors}, author = {Ilgin Gokasar and Dragan Pamucar and Muhammet Deveci and Brij B. Gupta and Luis Martínez and Oscar Castillo}, title = {Metaverse integration alternatives of connected autonomous vehicles with self-powered sensors using fuzzy decision making model}, abstract = {Using self-powered sensors, traffic data may be collected continuously, efficiently, and sustainably once connected autonomous vehicles (CAVs) are a part of metaverse technology. Metaverse self-powered sensors can capture uninterrupted data that allow for activities such as the management of the traffic network, the optimization of transportation facilities, and the management of urban and intercity journeys to be performed. In addition, metaverse technology creates a new field of study. Evaluating the systems involved in current transportation activities together with the metaverse can increase the efficiency and sustainability of transportation. The main purpose of this study is to prioritize four alternatives of CAVs in metaverse with self-powered sensors using a novel decision making model. The proposed hybrid decision making framework includes two stages. In the first stage the fuzzy full consistency method (fuzzy FUCOM) is applied to find the weighting coefficients of criteria. In the second stage, a fuzzy non-linear model based on fuzzy Aczel-Alsina functions (fuzzy Aczel-Alsina weighted assessment - ALWAS method) is defined to rank the alternatives. Four alternatives are defined and evaluated using twelve different criteria under four headings, namely, technical advancement, environmental, implementation, and financial aspects. A case study has been created for the experts to evaluate the alternatives most effectively. The results of the study indicate that using self-powered sensors for integrating real-time traffic management in the metaverse is the most advantageous alternative.}, year = {2023}, journal = {Information Sciences}, volume = {642}, pages = {119192}, issn = {0020-0255}, url = {https://www.sciencedirect.com/science/article/pii/S0020025523007776}, doi = {https://doi.org/10.1016/j.ins.2023.119192}, }