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

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. The authors present a comprehensive review of AI techniques that are currently being explored by various research efforts in the area of VANETs. The authors discuss the strengths and weaknesses of these proposed AI-based proposed approaches for the VANET environment. Finally, the authors identify future VANET research opportunities that can leverage the full potential of AI.

• Record URL:
  https://doi.org/10.1016/j.vehcom.2021.100403
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S2214209621000723
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/22142096
• Supplemental Notes:
  • © 2021 Elsevier Inc. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Mchergui, Abir
  • 0000-0003-0232-9136
  • Moulahi, Tarek
  • Zeadally, Sherali
• Publication Date: 2022-4

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Serial:
  • Vehicular Communications
  • Volume: 34
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2214-2096
  • Serial URL: http://www.sciencedirect.com/science/journal/22142096/1/2

Subject/Index Terms

• TRT Terms: Artificial intelligence; Machine learning; Vehicular ad hoc networks
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01785606
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 25 2021 9:16AM