Autors: Andreev, D. J., Trifonov, R. I., Lazarova, M. K. Title: Challenges Regarding AI Integration in V2X Communication Keywords: artificial intelligence, intelligent transportation systems, machine learning, vehicle-to-everythingAbstract: 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. References - P. Arthurs, L. Gillam, P. Krause, N. Wang, K. Halder and A. Mouzakitis, "A Taxonomy and Survey of Edge Cloud Computing for Intelligent Transportation Systems and Connected Vehicles," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 7, pp. 6206-6221, July 2022.
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| 2024 12th International Scientific Conference on Computer Science, COMSCI 2024 - Proceedings, 2024, , https://doi.org/10.1109/COMSCI63166.2024.10778510 |
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