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Evaluation of Cooperative Intelligent Transportation System scenarios for resilience in transportation using type-2 neutrosophic fuzzy VIKOR

Author

Listed:
  • Deveci, Muhammet
  • Gokasar, Ilgin
  • Pamucar, Dragan
  • Zaidan, Aws Alaa
  • Wen, Xin
  • Gupta, Brij B.

Abstract

There is a critical need for research in proactive and predictive management of the resilience of transportation systems implementing new technologies. Cooperative Intelligent Transportation System (C-ITS) uses wireless technology to allow vehicles and infrastructure to talk to each other in real-time. This makes it easier for people to work together on the road and makes it possible to make safer and more efficient traffic flows. Significant progress may be made in the transportation industry as a result of the incorporation of self-powered sensors into C-ITS providing resilience in transportation operation. One advantageous feature is that these sensors, which generate their power, could be deployed in a variety of C-ITS implementation scenarios. To assist decision-makers in making the most informed choice possible concerning investments and implementations, a type-2 neutrosophic number (T2NN) based VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method is used to perform advantage prioritization. To accomplish this goal, a case study is carried out to determine which of the three alternatives is the most suitable based on a set of twelve criteria that is divided into four aspects. According to the findings, the applicability and short-term benefits are the most crucial factors in determining which option is the most advantageous for the use of self-powered sensors in C-ITS. This is because both of these factors have an immediate impact on the system.

Suggested Citation

  • Deveci, Muhammet & Gokasar, Ilgin & Pamucar, Dragan & Zaidan, Aws Alaa & Wen, Xin & Gupta, Brij B., 2023. "Evaluation of Cooperative Intelligent Transportation System scenarios for resilience in transportation using type-2 neutrosophic fuzzy VIKOR," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:transa:v:172:y:2023:i:c:s0965856423000861
    DOI: 10.1016/j.tra.2023.103666
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    References listed on IDEAS

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    Cited by:

    1. Song, Zhao-Yu & Lin, Cheng-Wei & Feng, Xuehao & Lee, Paul Tae-Woo, 2024. "An empirical study of the performance of the sixth generation ports model with smart ports with reference to major container ports in mainland China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    2. Cheng, Xusen & Zhang, Shuang & Ran, Yanyue & Ma, Baojun, 2024. "Enhancing the perceived resilience of the road transportation system: Utilizing cues from ridesharing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).
    3. Anas A. Makki & Reda M. S. Abdulaal, 2023. "A Hybrid MCDM Approach Based on Fuzzy MEREC-G and Fuzzy RATMI," Mathematics, MDPI, vol. 11(17), pages 1-19, September.
    4. Amoozad Mahdiraji, Hannan & Yaftiyan, Fatemeh & Abbasi-Kamardi, Aliasghar & Vrontis, Demetris & Gong, Yu, 2024. "Disentangling the resiliency of international transportation systems under uncertainty by a novel multi-layer spherical fuzzy decision-making framework: Evidence from an emerging economy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).

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