Ultra-Low Latency V2X Systems with AI-Driven Resource Optimization
DOI:
https://doi.org/10.4108/eetsc.8366Keywords:
Autonomous Vehicles, V2X Communication, Ultra-Low Latency, Artificial Intelligence, Resource Optimization, Edge Computing, 5G Networks, Smart CitiesAbstract
Achieving ultra-low latency in Vehicle-to-Everything (V2X) communication is essential for ensuring the safety and effectiveness of autonomous vehicles (AVs). However, existing systems often struggle to meet the stringent latency demands, particularly in complex and rapidly changing urban environments. This study introduces an innovative framework that utilizes artificial intelligence (AI) for dynamic resource allocation in V2X networks. By integrating real-time data analysis, edge computing, and 5G capabilities, the proposed approach effectively minimizes latency. Simulation results indicate up to a 35% reduction in latency compared to conventional models, underscoring the potential of AI in enhancing the responsiveness and reliability of V2X systems. These findings offer a significant step toward making autonomous vehicle deployments more viable in smart cities.
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Copyright (c) 2025 Milad Rahmati
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