Key points are not available for this paper at this time.
The investigation of road safety issues has long posed a formidable challenge because of the intricate and unpredictable practice of human behavior. To address this complexity, experts in the field have turned to linguistic terms for evaluation, capitalizing on recent advancements in ordinary fuzzy sets. A promising way in Multi-criteria decision-making (MCDM) is the utilization of Pythagorean fuzzy sets (PFSs), which provide an extra flexible representation of membership tasks. This study introduces an innovative approach, the Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP), to measure and rank essential driver behavior criteria in a hierarchical model tailored for diverse driver groups in Budapest city. Our method effectively ranks the model criteria and sub-criteria based on their weighted scores. Consequently, we determine that criteria 'lapses' and 'errors' are the most pivotal factors based on the aggregated weights as compared to all other considerations. In contrast, the criterion 'disobeying speed limits' emerges as the least critical one, followed by 'disobeying overtaking rules' as the second least criterion. Our research highlights that the proposed approach yields robust and useful outcomes, well accommodating the inherent ambiguity in decision-making processes. The resilience of our findings is further affirmed through one-at-a-time sensitivity analysis.
Danish Farooq (Mon,) studied this question.