Sustainability in mobility for autonomous vehicles over smart city evaluation; using interval-valued fermatean fuzzy rough set-based decision-making model

Abstract

The simulation tools geared towards promoting sustainability in Mobility as a Service (MaaS) evaluation is inherently a multi-criteria decision-making (MCDM) challenge due to three primary concerns: the criteria significance, data variability, and the expert opinions' uncertainty. Despite efforts in recent years, no current developed MaaS has fully addressed all evaluation criteria. Moreover, no research has evaluated the sustainability of MaaS in the context of determining its optimality. As such, this research's pivotal contribution is to present an evaluation of simulation tools for sustainable MaaS in autonomous vehicles operating in smart cities. This evaluation leans on the advanced extension of a newly proposed an interval-valued Fermatean fuzzy rough set (IVFFRS) incorporated within integrated MCDM methodologies. The IVFFRS is designed to capture intricate and uncertain evaluative data. The initial phase of the evaluation methodology involves formulating the evaluation criteria using an interval-valued Fermatean fuzzy rough set, fuzzily weighted for zero inconsistency. The subsequent phase adopts the interval-valued Fermatean fuzzy rough decision via the opinion score method to prioritize alternatives in light of data variations. This study evaluates ten distinct simulation tools for MaaS in autonomous vehicles based on seven criteria. The methodology's robustness is further ascertained through sensitivity and comparative analyses.