Explainable AI with EDA for V2I path loss prediction. [PDF]
Sci RepAmeur MB +5 more
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A cooperative ECC-based authentication protocol for VANETs. [PDF]
Sci RepLiu Z, Yao N, Bai S, Mai T.
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State-Aware Resource Allocation for V2X Communications. [PDF]
Sensors (Basel)Sun M, Xu J, Wang J.
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, 2019 La localisation précise des véhicules et la sécurité des échanges sont deux grands axes qui font la fiabilité des services fournis dans les systèmes de transport intelligent. Ces dernières années, elles font l’objet de nombreux projets de recherche pour des champs d’application divers. Dans cette thèse, le contexte d’application est la réalisation d’un
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Cooperative Eco-Driving at Signalized Intersections in a Partially Connected and Automated Vehicle Environment [PDF]
, 2019 Barth, Matthew J +2 more
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DRLO-VANET: a deep reinforcement learning-based offloading framework for low-latency and energy-efficient task execution in VANETs. [PDF]
Sci RepNeelima S, Sree SR, Ramakrishnaiah N.
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Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning. [PDF]
Sci RepLiu Q, Ma Y.
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Reinforcement learning for dynamic speed control in connected and autonomous vehicles: A review of applications and challenges. [PDF]
iScienceAlhmiedat T +6 more
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Machine learning for improved path loss prediction in urban vehicle-to-infrastructure communication systems. [PDF]
Front Artif IntellBen Ameur M +3 more
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Design and analysis of optically transparent high gain grid array antenna for vehicular communications. [PDF]
Sci RepJoy J A +4 more
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