An advanced multi-criteria decision-making model based on elliptic pythagorean fuzzy sets: A case study on autonomous vehicle technologies

Abstract

The development of autonomous vehicles (AVs) has become a pivotal element of modern transportation, aiming to alleviate persistent challenges such as driver errors, congestion hotspots, limited roadway capacity, and excessive fuel consumption. To address the inherent uncertainty in evaluating AV technologies, we propose the concept of elliptic Pythagorean fuzzy sets (E-PFSs). E-PFSs extend and generalize existing models, including the classical Pythagorean fuzzy sets (PFSs), the circular Pythagorean fuzzy sets (C-PFSs), and the elliptic intuitionistic fuzzy sets (E-IFSs). By expanding the feasible domain of membership and non-membership degrees from circular to elliptical regions, E-PFSs offer a more flexible and comprehensive representation of uncertainty. Some basic operations are established in the framework of E-PFNs, and their interrelations are discussed analytically. Further, we present aggregation operators under the E-PFS framework, such as the weighted arithmetic aggregation operator and the weighted geometric aggregation operator. A cosine similarity measure (CSM) is also proposed to calculate the similarity between elliptic Pythagorean fuzzy numbers (E-PFNs). Building upon these tools, we propose a novel multi-criteria group decision-making (MCGDM) method for practical applications such as AV technology selection, supplemented by comparative analysis with existing fuzzy models.