A novel multi-criteria group decision-making technique in traffic flow and safety assessment using interval-valued complex spherical fuzzy soft set
摘要
The significant increase in vehicular traffic has grown into an enormous challenge for both the transportation system and public safety mechanisms. To address such issues effectively, experts must employ an integrated, competent decision-making strategy that objectively consolidates and interprets their arguments. The main objective of this research is to introduce the Einstein operational laws for interval-valued complex spherical fuzzy soft sets (IVCSFSS) and develop the interval-valued complex spherical fuzzy soft Einstein weighted average (IVCSFSEWA) and interval-valued complex spherical fuzzy soft Einstein weighted geometric (IVCSFSEWG) operators with their properties. Moreover, we introduce a novel multi-criteria group decision-making (MCGDM) technique that employs the proposed operators to evaluate traffic flow and safety in uncertain, dynamic environments. The proposed model is applied to four traffic scenarios: a smart-signal roundabout, a residential road, an expressway merge point, and a school-zone intersection. The assessment is executed by experts using criteria such as road conditions, public awareness, traffic density, and average travel time. The results demonstrate that the proposed framework effectively detects the most critical traffic scenario and offers an organized framework for analyzing traffic risk and uncertainty. This supports decision-makers in promoting safer, more flexible traffic management strategies.