FE - DI | Dissertações de Mestrado e Teses de Doutoramento
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- Network Analytics for 5G DataPublication . Ferreira, Rui Pedro Passos; Proença, Hugo Pedro Martins Carriço; Araújo, MarcoOver the last decade, advances in network infrastructure and Artificial Intelligence have driven the development and integration of autonomous vehicles into society. The ultra-low latency and high bandwidth of Fifth Generation Mobile Networks (5G) enable real-time data exchange among vehicles, infrastructure and cloud-based Artificial Intelligence systems. This connectivity empowers the development of Intelligent Transportation Systems. Machine Learning algorithms onboard these vehicles and integrated into network infrastructures enable real-time data analysis, allowing for a more accurate decision-making process and improved road safety and sustainability. Within this scope, this research assesses various approaches to building intelligent systems capable of effectively predicting End-to-End latency values to ensure reliable communication in vehicular platooning scenarios. Traffic pattern delays are also analyzed to extract meaningful insights that promote efficient traffic management strategies. The work described in this document is part of the European project 5G/SDN Intelligent Systems For LOw latencY V2X communications in cross-Domain mobility applications (FLOYD), which aims to advance autonomous driving technologies for Vehicle-toEverything (V2X) platooning applications.