ArticleSensors (Basel, Switzerland)2026
Joint Optimization of Packet Survivability and Aerodynamic Energy for Dynamic UAV Activation in VANETs via Deep Q-Networks.
Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
UAV-assisted VANETs are a key component of the 6G vision, yet their practical deployment is hindered by the fundamental conflict between network Quality of Service (QoS) and the high aerodynamic power required for rotary-wing flight. This paper proposes SAVIOR (Survivable Aerial-Vehicular Intelligent Optimization and Routing), a Deep Reinforcement Learning (DRL) framework that jointly optimizes multi-UAV activation and packet routing. Unlike existing approaches that rely on oversimplified linear energy models, SAVIOR integrates a rigorous three-component aerodynamic power model and introduces an M/M/1 queuing-based Survivability Score (
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