Challenges Regarding AI Integration in V2X Communication

Advances in the field of computation, networking, communication and machine learning have allowed for their integration in vehicle-to-everything communication to form intelligent transportation systems. These systems aim to improve safety, mitigate traffic congestion, and enhance fuel efficiency. The main challenge this survey investigates is the integration of artificial intelligence within vehicle-to-everything systems, focusing on its contributions to improving vehicle communications and traffic management. We discuss the current state of artificial intelligence applications in vehicle-to-everything, explore key challenges, and propose future research directions.

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Publication Details

Published
2024-09-13
DOI
https://doi.org/10.1109/comsci63166.2024.10778510
Citations
5
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
1.74
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article

Challenges Regarding AI Integration in V2X Communication

Milena Lazarova, D. P. Andreev, Roumen Trifonov
5 citations
IoT and Edge/Fog Computing
1.74
article

Challenges Regarding AI Integration in V2X Communication

Milena Lazarova, D. P. Andreev, Roumen Trifonov
article en
5 citations

Abstract

Advances in the field of computation, networking, communication and machine learning have allowed for their integration in vehicle-to-everything communication to form intelligent transportation systems. These systems aim to improve safety, mitigate traffic congestion, and enhance fuel efficiency. The main challenge this survey investigates is the integration of artificial intelligence within vehicle-to-everything systems, focusing on its contributions to improving vehicle communications and traffic management. We discuss the current state of artificial intelligence applications in vehicle-to-everything, explore key challenges, and propose future research directions.

Technical University of Sofia (BG)
Reduced inequalities
Openalex Percentile: Top 14%
IoT and Edge/Fog Computing
1.74
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