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

Metaverse comes from the meta-universe, and it is the integration of physical and digital space into a virtual universe. Metaverse technologies will change the transportation system as we know it. Preparations for the transition of the transportation systems into the world of metaverse are underway. This study considers four alternative metaverses: auto-driving algorithm testing for training autonomous driving artificial intelligence, public transportation operation and safety, traffic operation, and sharing economy applications to obtain sus-tainable transportation. These alternatives are evaluated on thirteen sub-criteria, grouped under four main aspects: efficiency, operation, social and health, and legislation and regulation. A novel Rough Aczel-Alsa (RAA) function and the Ordinal Priority Approach (OPA) method are used in the assessment model. We also present a case study to demonstrate the applicability and exhibit the efficacy of the assessment framework in prioritizing the metaverse implementation alternatives.