Safety-Centric Vehicle Classification Using Vehicular Networks

This paper investigates the vehicle classification (VC) based on vehicular ad-hoc networks (VANETs). Using VANETs, one can extract the physical and mobility characteristics of the vehicles globally and in a real-time manner. In this paper, the authors propose an in-depth novel safety-driven VC method for heterogeneous connected vehicles. In this innovative approach, road vehicles are classified into a broad range of classes according to their distinctive behaviors and safety measures. The proposed method can play a vital role in reducing collisions and can be used as a safety standard reference in VANETs-based VC systems. Furthermore, advance driver assistance systems (ADAS) can integrate this method and extend road safety by notifying vehicles of dangerous situations on the road using V2X communication.

• Record URL:
  https://doi.org/10.1016/j.procs.2021.07.030
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1877050921014253
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/18770509
• Supplemental Notes:
  • © 2021 Ashkan Gholamhosseinian and Jochen Seitz. Published by Elsevier B.V. Abstract reprinted with permission of Elsevier. The 16th International Conference on Future Networks and Communications (FNC) August 9-12, 2021, Leuven, Belgium
• Authors:
  • Gholamhosseinian, Ashkan
  • Seitz, Jochen
• Publication Date: 2021

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 238-245
• Serial:
  • Procedia Computer Science
  • Volume: 191
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1877-0509
  • Serial URL: http://www.sciencedirect.com/science/journal/18770509
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Connected vehicles; Driver support systems; Intelligent transportation systems; Traffic safety; Vehicle to infrastructure communications; Vehicle to vehicle communications
• Identifier Terms: VANET (Traffic simulator)
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01783259
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 27 2021 9:59AM