International Journal of Engineering
Trends and Technology

Research Article | Open Access | Download PDF
Volume 74 | Issue 10 | Year 2026 | Article Id. IJETT-V74I10P133 | DOI : https://doi.org/10.14445/22315381/IJETT-V74I10P133

Intelligent VANETS: Neuro-Fuzzy Optimization for Traffic Management and Accident Prevention using Vehicle Cluster Routing-based Neuro-Fuzzy Logic

R. Syed Ali Fathima, R. Sumathi

Received Revised Accepted Published
24 Jun 2026 14 Sep 2026 18 Sep 2026 27 Oct 2026

Citation :

R. Syed Ali Fathima, R. Sumathi, "Intelligent VANETS: Neuro-Fuzzy Optimization for Traffic Management and Accident Prevention using Vehicle Cluster Routing-based Neuro-Fuzzy Logic," International Journal of Engineering Trends and Technology (IJETT), vol. 74, no. 10, pp. 470-478, 2026. Crossref, https://doi.org/10.14445/22315381/IJETT-V74I10P133

Abstract

In wireless communication between vehicles, the The Vehicular Ad Hoc Network (VANET) is a key component of optimizing efficient and secured traffic management. But it gives more complications due to its dynamic changing architecture associated with rapid vehicle mobility, inconsistent communication network, and restricted framework region. In this research, an innovative approach is introduced Vehicle Cluster Routing based Neuro-Fuzzy Logic (VCR-NFL) to achieve stable connectivity in VANET The main goal of this proposed VCR-NFL approach is to address the problem of over speed vehicles. The Cluster Head (CH) is elected with vehicles having slow speed, minimal distance, and high energy levels. This cluster concept is applied to monitor and control the vehicles effectively. The stability of the cluster is achieved by FUZZY logic which enables the automated succeeding CH selection process. Simulation results demonstrate that the proposed VCR-NFL approach outperforms the other methods currently in use. by providing reliable communication in VANET.

Keywords

VANET, CH, Fuzzy logic, Traffic, and Safety.

References

  1. Zahid Khan, and Pingzhi Fan, “A Novel Triple Cluster based Routing Protocol (TCRP) for VANETs,” 2016 IEEE 83rd Vehicular Technology Conference, Nanjing, China, pp. 1-5, 2016.
    [CrossRef] [Google Scholar] [Publisher Link]
  2. Ishtiaq Wahid et al., “State of the Art Routing Protocols in VANETs: A Review,” Procedia Computer Science, vol. 130, pp. 689-694, 2018.
    [CrossRef] [Google Scholar] [Publisher Link]
  3. Zahid Khan et al., “An Unsupervised Cluster-based VANET-Oriented Evolving Graph (CVoEG) Model and Associated Reliable Routing Scheme,” IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 10, pp. 3844-3859, 2019.
    [CrossRef] [Google Scholar] [Publisher Link]
  4. Zahid Khan, and Pingzhi Fan, “A Multi-Hop Moving Zone (MMZ) Clustering Scheme based on Cellular-V2X,” China Communications, vol. 15, no. 7, pp. 55-66, 2018.
    [CrossRef] [Google Scholar] [Publisher Link]
  5. Mahmoud Hashem Eiza, and Qiang Ni, “An Evolving Graph-based Reliable Routing Scheme for VANETs,” IEEE Transactions on Vehicular Technology, vol. 62, no. 4, pp. 1493-1504, 2013.
    [CrossRef] [Google Scholar] [Publisher Link]
  6. Zahid Khan et al., “Two-Level Cluster based Routing Scheme for 5G V2X Communication,” IEEE Access, vol. 7, pp. 16194-16205, 2019.
    [CrossRef] [Google Scholar] [Publisher Link]
  7. Dan Lin et al., “MoZo: A Moving Zone based Routing Protocol using Pure V2V Communication in VANETs,” IEEE Transactions on Mobile Computing, vol. 16, no. 5, pp. 1357-1370, 2017.
    [CrossRef] [Google Scholar] [Publisher Link]
  8. Zahid Khan et al., “Street-Centric Routing Scheme using Ant Colony Optimization-based Clustering for Bus-based Vehicular Ad-Hoc Network,” Computers and Electrical Engineering, vol. 86, no. 1-12, 2020.
    [CrossRef] [Google Scholar] [Publisher Link]
  9. Fakhar Abbas et al., “An Efficient Cluster based Resource Management Scheme and its Performance Analysis for V2X Networks,” IEEE Access, vol. 8, pp. 87071-87082, 2020.
    [CrossRef] [Google Scholar] [Publisher Link]
  10. Craig Cooper et al., “A Comparative Survey of VANET Clustering Techniques,” IEEE Communications Surveys and Tutorials, vol. 19, no. 1, pp. 657-681, 2017.
    [CrossRef] [Google Scholar] [Publisher Link]
  11. Xiaofeng Liu, Ben St. Amour, and Arunita Jaekel, “A Q-Learning based Adaptive Congestion Control for V2V Communication in VANET,” 2022 International Wireless Communications and Mobile Computing, Dubrovnik, Croatia, pp. 847-852, 2022.
    [CrossRef] [Google Scholar] [Publisher Link]
  12. Atul R. Deshmukh, Satyajeet A. Dhawale, and S.S. Dorle, “Analysis of Cluster based Routing Protocol (CBRP) for Vehicular Adhoc Network (VANET) in Real Geographic Scenario,” 2020 IEEE International Conference on Electronics, Computing and Communication Technologies, Bangalore, India, pp. 1-5, 2020.
    [CrossRef] [Google Scholar] [Publisher Link]
  13. Sumendra Yogarayan et al., “A Review of Routing Protocols for Vehicular Ad-Hoc Networks (VANETs),” 2020 8th International Conference on Information and Communication Technology, Yogyakarta, Indonesia, pp. 1-7, 2020.
    [CrossRef] [Google Scholar] [Publisher Link]
  14. Ankita Srivastava, Arun Prakash, and Rajeev Tripathi, “Location based Routing Protocols in VANET: Issues and Existing Solutions,” Vehicular Communications, vol. 23, pp. 1-30, 2020.
    [CrossRef] [Google Scholar] [Publisher Link]
  15. Sahil Khatri et al., “Machine Learning Models and Techniques for VANET based Traffic Management: Implementation Issues and Challenges,” Peer-to-Peer Networking and Applications, vol. 14, no. 3, pp. 1778-1805, 2021.
    [CrossRef] [Google Scholar] [Publisher Link]
  16. Bechir Alaya, and Lamaa Sellami, “Clustering Method and Symmetric/Asymmetric Cryptography Scheme Adapted to Securing Urban VANET Networks,” Journal of Information Security and Applications, vol. 58, pp. 1-12, 2021.
    [CrossRef] [Google Scholar] [Publisher Link]
  17. Fatemehsadat Mirsadeghi, Marjan Kuchaki Rafsanjani, and Brij B. Gupta, “A Trust Infrastructure based Authentication Method for Clustered Vehicular Ad Hoc Networks,” Peer-to-Peer Networking and Applications, vol. 14, no. 4, pp. 2537-2553, 2021.
    [CrossRef] [Google Scholar] [Publisher Link]
  18. Muhsen Alkhalidy et al., “A New Scheme for Detecting Malicious Nodes in Vehicular Ad Hoc Networks based on Monitoring Node Behavior,” Future Internet, vol. 14, no. 8, pp. 1-11, 2022.
    [CrossRef] [Google Scholar] [Publisher Link]
  19. Akhilesh Bijalwan et al., “A Self-Adaptable Angular based K-Medoid Clustering Scheme (SAACS) for Dynamic VANETs,” Electronics, vol. 11, no. 19, pp. 1-19, 2022.
    [CrossRef] [Google Scholar] [Publisher Link]
  20. Asma Ait Ouallane et al., “Fusion of Engineering Insights and Emerging Trends: Intelligent Urban Traffic Management System,” Information Fusion, vol. 88, pp. 218-248, 2022.
    [CrossRef] [Google Scholar] [Publisher Link]
  21. R.M. Rajeswari, and S. Rajesh, “Enhance Security and Privacy in VANET based Sensor Monitoring and Emergency Services,” Cybernetics and Systems, vol. 55, no. 4, pp. 872-893, 2024.
    [CrossRef] [Google Scholar] [Publisher Link]
  22. Jinbin Hu et al., “Motion Prediction based TDMA Protocol in VANETs,” Electronics, vol. 9, no. 11, pp. 1-14, 2020.
    [CrossRef] [Google Scholar] [Publisher Link]
  23. Hyung-Sin Kim et al., “PC-RPL: Joint Control of Routing Topology and Transmission Power in Real Low-Power and Lossy Networks,” ACM Transactions on Sensor Networks, vol. 16, no. 2, pp. 1-32, 2020.
    [CrossRef] [Google Scholar] [Publisher Link]
  24. Xin Yang et al., “Priority-based Hybrid MAC Protocol for VANET with UAV-Enabled Roadside Units,” Wireless Communications and Mobile Computing, vol. 2022, no. 1, pp. 1-13, 2022.
    [CrossRef] [Google Scholar] [Publisher Link]
  25. Rajeshwari Chiluveru, Nishu Gupta, and Ariel Soares Teles, “Distribution of Safety Messages using Mobility-Aware Multi-Hop Clustering in Vehicular Ad Hoc Network,” Future Internet, vol. 13, no. 7, pp. 1-17, 2021.
    [    CrossRef] [Google Scholar] [Publisher Link]