Details

Autor(en) / Beteiligte

• Anjum, Mohd
• Simic, Vladimir
• Alrasheedi, Melfi A.
• Shahab, Sana

Titel

T-Spherical Fuzzy-CRITIC-WASPAS Model for the Evaluation of Cooperative Intelligent Transportation System Scenarios

Ist Teil von

• IEEE access, 2024, Vol.12, p.61137-61151

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2024

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• In response to the transportation industry's immediate need for more proactive and foresighted management, cooperative intelligent transportation systems (C-ITS) use wireless technology to foster real-time communication between vehicles and infrastructure, with the goal of increasing road safety and streamlining traffic flow. The introduction of self-powered sensors, which have the clever capacity to produce their own electricity, is critical for the reliability of transport operations across a wide range of C-ITS applications. Our analytical technique, which employs the criteria importance through intercriteria correlation (CRITIC) methodology and the weighted aggregated sum product assessment (WASPAS) approach, does not end there. We have taken it a step further by using the T-spherical fuzzy (T-SF) form of CRITIC-WASPAS, which adds a more subtle layer to our evaluation. We embark on an in-depth case study, methodically evaluating five choices against eight criteria. In the context of the CRITIC-WASPAS framework, the application of the T-SF logic enhances analytical precision by taking into account uncertainty throughout the decision-making process. This is particularly beneficial in the context of complex systems like C-ITS. The incorporation of CRITIC also makes it possible to evaluate the correlations between different criteria, which ultimately results in decision outcomes that are more nuanced and robust. This is accomplished by aggregating all of the criteria and options. This rigorous and intelligent strategy goes beyond simply meeting urgent system needs. It tactically impacts decision-making, moving the transport industry forward significantly.