Survey on Artificial Intelligence (AI) techniques for Vehicular Ad-hoc Networks (VANETs)

Abir Mchergui, Tarek Moulahi, Sherali Zeadally

Research output: Contribution to journalReview articlepeer-review

49 Scopus citations


Advances in communications, smart transportation systems, and computer systems have recently opened up vast possibilities of intelligent solutions for traffic safety, convenience, and effectiveness. Artificial Intelligence (AI) is currently being used in various application domains because of its strong potential to help enhance conventional data-driven methods. In the area of Vehicular Ad hoc NETworks (VANETs) data is frequently collected from various sources. This data is used for various purposes which include routing, broadening the awareness of the driver, predicting mobility to avoid hazardous situations, thereby improving passenger comfort, safety, and quality of road experience. We present a comprehensive review of AI techniques that are currently being explored by various research efforts in the area of VANETs. We discuss the strengths and weaknesses of these proposed AI-based proposed approaches for the VANET environment. Finally, we identify future VANET research opportunities that can leverage the full potential of AI.

Original languageEnglish
Article number100403
JournalVehicular Communications
StatePublished - Apr 2022

Bibliographical note

Funding Information:
We thank the anonymous reviewers for their valuable comments which helped us improve the quality, organization, content, and presentation of this paper.

Publisher Copyright:
© 2021 Elsevier Inc.


  • Artificial intelligence
  • Deep learning
  • Machine learning
  • Swarm intelligence
  • Vehicular networks

ASJC Scopus subject areas

  • Automotive Engineering
  • Electrical and Electronic Engineering


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