A novel multi-criteria group decision-making technique in traffic flow and safety assessment using interval-valued complex spherical fuzzy soft set
5 affiliations
- 1School of Business, Xian International University
- 2Department of Mathematics, Faculty of Science, Thonburi (KMUTT), King Mongkut′s University of Technology
- 3Department of Electrical Engineering, Faculty of Engineering, Hormuud University
- 4Department of Mathematics, Faculty of Science, Islamic University of Madinah
- 5Department of Mathematics, Saveetha School of Engineering, SIMATS Thandalam
Abstract
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.
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BibTeX
@article{zulqarnain2026novel,
title = {{A novel multi-criteria group decision-making technique in traffic flow and safety assessment using interval-valued complex spherical fuzzy soft set}},
author = {Rana Muhammad Zulqarnain and Saalam Ali and Hamza Naveed and Mohamed Abubakar Fiidow and Imran Siddique and Sohaib Abdal},
journal = {Scientific Reports},
year = {2026},
month = jul,
doi = {10.1038/s41598-026-43050-5},
url = {https://doi.org/10.1038/s41598-026-43050-5},
note = {CC BY},
}
RIS
TY - JOUR
TI - A novel multi-criteria group decision-making technique in traffic flow and safety assessment using interval-valued complex spherical fuzzy soft set
AU - Rana Muhammad Zulqarnain
AU - Saalam Ali
AU - Hamza Naveed
AU - Mohamed Abubakar Fiidow
AU - Imran Siddique
AU - Sohaib Abdal
PY - 2026
DA - 2026/07/01
JO - Scientific Reports
DO - 10.1038/s41598-026-43050-5
UR - https://doi.org/10.1038/s41598-026-43050-5
AB - 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.
SN - 2045-2322
ER -