Autonomous driving paper index
A novel multi-criteria group decision-making technique in traffic flow and safety assessment using interval-valued complex spherical fuzzy soft set
One-line summary
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.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original 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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