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Financial Technology and Innovation
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Title

WASPAS Multi-Criteria Decision-Making Method for Assessment Effectiveness and Performance Intelligent Transportation Systems Alternatives

  Abedallah Z. Abualkishik 1 * ,   Rasha Almajed 2

1  American University in the Emirates, Dubai, UAE
    (abedallah.abualkishik@aue.ae)

2  American University in the Emirates, Dubai, UAE
    (rasha.almajed@aue.ae)


Doi   :   https://doi.org/10.54216/FinTech-I.030105

Received: May 17, 2023 Accepted: December 22, 2023

Abstract :

The assessment of Intelligent Transportation Systems (ITS) plays a vital role in understanding their effectiveness, efficiency, and impact on transportation networks. This abstract provides an overview of the criteria for assessing ITS and highlights the importance of a comprehensive and multidimensional approach. The requirements discussed include safety, efficiency, mobility, environmental impact, user satisfaction, cost-effectiveness, scalability and interoperability, data security and privacy, technological reliability and resilience, regulatory and policy compliance, equity and accessibility, system integration, innovation and future-readiness, stakeholder engagement, performance monitoring and evaluation, resilience and disaster preparedness, social and economic impact, and continuous improvement and adaptation. By considering these criteria, stakeholders can gain valuable insights into the performance and benefits of ITS, aiding in decision-making, policy development, and future planning for transportation systems. This study uses multi-criteria decision-making (MCDM) methodologies, such as the assessing attractiveness method and the weighted aggregated sum product assessment (WASPAS) method. The WASPAS method is used to rank the alternatives. We used 18 criteria and 8 alternatives to be organised. The sensitivity analysis is conducted to check the stability of the results.

Keywords :

Transportation System; Multi-Criteria Decision Making; WASPAS; Assessment. 

References :

[1]        J. N. Njoku, C. I. Nwakanma, G. C. Amaizu, and D. Kim, “Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems,” IET Intelligent Transport Systems, vol. 17, no. 1, pp. 1–21, 2023.

[2]        Z. Lv and W. Shang, “Impacts of intelligent transportation systems on energy conservation and emission reduction of transport systems: A comprehensive review,” Green Technologies and Sustainability, vol. 1, no. 1, p. 100002, 2023.

[3]        R. Jabbar et al., “Blockchain technology for intelligent transportation systems: A systematic literature review,” IEEE Access, vol. 10, pp. 20995–21031, 2022.

[4]        B. B. Gupta, A. Gaurav, E. C. Marín, and W. Alhalabi, “Novel graph-based machine learning technique to secure smart vehicles in intelligent transportation systems,” IEEE transactions on intelligent transportation systems, 2022.

[5]        C. Zhao, Y. Lv, J. Jin, Y. Tian, J. Wang, and F.-Y. Wang, “DeCAST in TransVerse for parallel intelligent transportation systems and smart cities: Three decades and beyond,” IEEE Intelligent Transportation Systems Magazine, vol. 14, no. 6, pp. 6–17, 2022.

[6]        S. Yang, H. Lu, and J. Li, “Multifeature fusion-based object detection for intelligent transportation systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 1, pp. 1126–1133, 2022.

[7]        T. R. Ramesh, M. Vijayaragavan, M. Poongodi, M. Hamdi, H. Wang, and S. Bourouis, “Peer-to-peer trust management in intelligent transportation system: An Aumann’s agreement theorem based approach,” ICT Express, vol. 8, no. 3, pp. 340–346, 2022.

[8]        R. W. Liu, Y. Guo, Y. Lu, K. T. Chui, and B. B. Gupta, “Deep network-enabled haze visibility enhancement for visual IoT-driven intelligent transportation systems,” IEEE Transactions on Industrial Informatics, vol. 19, no. 2, pp. 1581–1591, 2022.

[9]        N. Yuvaraj, K. Praghash, R. A. Raja, and T. Karthikeyan, “An investigation of garbage disposal electric vehicles (GDEVs) integrated with deep neural networking (DNN) and intelligent transportation system (ITS) in smart city management system (SCMS),” Wireless personal communications, vol. 123, no. 2, pp. 1733–1752, 2022.

[10]      J. Liu, L. Zhang, C. Li, J. Bai, H. Lv, and Z. Lv, “Blockchain-based secure communication of intelligent transportation digital twins system,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 11, pp. 22630–22640, 2022.

[11]      C. Liu and L. Ke, “Cloud assisted Internet of things intelligent transportation system and the traffic control system in the smart city,” Journal of Control and Decision, vol. 10, no. 2, pp. 174–187, 2023.

[12]      T. Yuan, W. Da Rocha Neto, C. E. Rothenberg, K. Obraczka, C. Barakat, and T. Turletti, “Machine learning for next‐generation intelligent transportation systems: A survey,” Transactions on emerging telecommunications technologies, vol. 33, no. 4, p. e4427, 2022.

[13]      R. Rajamoorthy et al., “A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms,” Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 44, no. 2, pp. 3555–3575, 2022.

[14]      K. Rudnik, G. Bocewicz, A. Kucińska-Landwójtowicz, and I. D. Czabak-Górska, “Ordered fuzzy WASPAS method for selection of improvement projects,” Expert Systems with Applications, vol. 169, p. 114471, 2021.

[15]      D. Karabašević, D. Stanujkić, S. Urošević, and M. Maksimović, “An approach to personnel selection based on SWARA and WASPAS methods,” Bizinfo (Blace), vol. 7, no. 1, pp. 1–11, 2016.

[16]      M. Badalpur and E. Nurbakhsh, “An application of WASPAS method in risk qualitative analysis: a case study of a road construction project in Iran,” International Journal of Construction Management, vol. 21, no. 9, pp. 910–918, 2021.

[17]      R. Lukić, D. V. Kljenak, S. Anđelić, and M. Gavrlilović, “Application of WASPAS method in the evaluation of efficiency of agricultural enterprises in Serbia,” Економика пољопривреде, vol. 68, no. 2, pp. 375–388, 2021.

[18]      E. K. Zavadskas, Z. Turskis, and J. Antucheviciene, “Selecting a contractor by using a novel method for multiple attribute analysis: Weighted Aggregated Sum Product Assessment with grey values (WASPAS-G),” Studies in Informatics and Control, vol. 24, no. 2, pp. 141–150, 2015.

[19]      S. Chakraborty, O. Bhattacharyya, E. K. Zavadskas, and J. Antucheviciene, “Application of WASPAS method as an optimization tool in non-traditional machining processes,” Information Technology and Control, vol. 44, no. 1, pp. 77–88, 2015.

[20]      M. K. Ghorabaee, E. K. Zavadskas, M. Amiri, and A. Esmaeili, “Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets,” Journal of Cleaner Production, vol. 137, pp. 213–229, 2016.

[21]      S. Chakraborty and E. K. Zavadskas, “Applications of WASPAS method in manufacturing decision making,” 2014.

[22]      S. Chakraborty, E. K. Zavadskas, and J. Antuchevičienė, “Applications of WASPAS method as a multi-criteria decision-making tool,” 2015.

[23]      A. Mardani et al., “A systematic review and meta-Analysis of SWARA and WASPAS methods: Theory and applications with recent fuzzy developments,” Applied soft computing, vol. 57, pp. 265–292, 2017.

[24]      A. Alinezhad, J. Khalili, A. Alinezhad, and J. Khalili, “WASPAS method,” New Methods and Applications in Multiple Attribute Decision Making (MADM), pp. 93–98, 2019.

[25]      S. Xia, Z. Yao, G. Wu, and Y. Li, “Distributed offloading for cooperative intelligent transportation under heterogeneous networks,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 9, pp. 16701–16714, 2022.

[26]      V. Shepelev et al., “Forecasting the passage time of the queue of highly automated vehicles based on neural networks in the services of cooperative intelligent transport systems,” Mathematics, vol. 10, no. 2, p. 282, 2022.

[27]      Y. Lin, Q. Li, D. Lyu, and X. Wang, “A Review of Wi-Fi-Based Traffic Detection Technology in the Field of Intelligent Transportation Systems,” Buildings, vol. 12, no. 4, p. 428, 2022.

[28]      A. R. Khan et al., “DSRC technology in Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) IoT system for Intelligent Transportation System (ITS): A review,” Recent Trends in Mechatronics Towards Industry 4.0: Selected Articles from iM3F 2020, Malaysia, pp. 97–106, 2022.

[29]      Q. Ren, O. Abbasi, G. K. Kurt, H. Yanikomeroglu, and J. Chen, “Caching and computation offloading in high altitude platform station (HAPS) assisted intelligent transportation systems,” IEEE Transactions on Wireless Communications, vol. 21, no. 11, pp. 9010–9024, 2022.

[30]      F. A. Omonov, “The important role of intellectual transport systems in increasing the economic efficiency of public transport services,” Academic research in educational sciences, vol. 3, no. 3, pp. 36–40, 2022.

[31]      H. Gao, W. Huang, T. Liu, Y. Yin, and Y. Li, “Ppo2: Location privacy-oriented task offloading to edge computing using reinforcement learning for intelligent autonomous transport systems,” IEEE transactions on intelligent transportation systems, 2022.

 


Cite this Article as :
Style #
MLA Abedallah Z. Abualkishik, Rasha Almajed. "WASPAS Multi-Criteria Decision-Making Method for Assessment Effectiveness and Performance Intelligent Transportation Systems Alternatives." Financial Technology and Innovation, Vol. 3, No. 1, 2023 ,PP. 45-56 (Doi   :  https://doi.org/10.54216/FinTech-I.030105)
APA Abedallah Z. Abualkishik, Rasha Almajed. (2023). WASPAS Multi-Criteria Decision-Making Method for Assessment Effectiveness and Performance Intelligent Transportation Systems Alternatives. Journal of Financial Technology and Innovation, 3 ( 1 ), 45-56 (Doi   :  https://doi.org/10.54216/FinTech-I.030105)
Chicago Abedallah Z. Abualkishik, Rasha Almajed. "WASPAS Multi-Criteria Decision-Making Method for Assessment Effectiveness and Performance Intelligent Transportation Systems Alternatives." Journal of Financial Technology and Innovation, 3 no. 1 (2023): 45-56 (Doi   :  https://doi.org/10.54216/FinTech-I.030105)
Harvard Abedallah Z. Abualkishik, Rasha Almajed. (2023). WASPAS Multi-Criteria Decision-Making Method for Assessment Effectiveness and Performance Intelligent Transportation Systems Alternatives. Journal of Financial Technology and Innovation, 3 ( 1 ), 45-56 (Doi   :  https://doi.org/10.54216/FinTech-I.030105)
Vancouver Abedallah Z. Abualkishik, Rasha Almajed. WASPAS Multi-Criteria Decision-Making Method for Assessment Effectiveness and Performance Intelligent Transportation Systems Alternatives. Journal of Financial Technology and Innovation, (2023); 3 ( 1 ): 45-56 (Doi   :  https://doi.org/10.54216/FinTech-I.030105)
IEEE Abedallah Z. Abualkishik, Rasha Almajed, WASPAS Multi-Criteria Decision-Making Method for Assessment Effectiveness and Performance Intelligent Transportation Systems Alternatives, Journal of Financial Technology and Innovation, Vol. 3 , No. 1 , (2023) : 45-56 (Doi   :  https://doi.org/10.54216/FinTech-I.030105)