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Artificial Intelligence-Enabled Vehicle-to-Vehicle (V2V) Communication: Working Principles, Current Research Advances, and Future Directions for Intelligent Transportation Systems

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The development of cutting-edge vehicle communication technology targeted at enhancing road safety, traffic efficiency, and autonomous mobility has been expedited by the emergence of intelligent transportation systems. Direct wireless connection between vehicles is made possible via vehicle-to-vehicle (V2V) communication, which speeds up the exchange of vital safety data like speed, trajectory, braking status, and road conditions. By incorporating Artificial Intelligence (AI) into V2V networks, predictive skills are improved, enabling cars to foresee possible risks and react proactively as opposed to reactively.With an emphasis on its operational architecture, supporting technologies, recent research advancements, and future network paradigms, this study provides a thorough scientific overview of V2V communication. The report demonstrates how next-generation wireless technologies, edge computing, and AI-driven analytics are converting vehicle networks into intelligent safety ecosystems. Important issues are also looked at, such as interoperability, scalability, cyber security hazards, and latency limitations. The study comes to the conclusion that AI-enabled V2V communication will be a key component of completely autonomous and accident-free transportation systems.
Title: Artificial Intelligence-Enabled Vehicle-to-Vehicle (V2V) Communication: Working Principles, Current Research Advances, and Future Directions for Intelligent Transportation Systems
Description:
The development of cutting-edge vehicle communication technology targeted at enhancing road safety, traffic efficiency, and autonomous mobility has been expedited by the emergence of intelligent transportation systems.
Direct wireless connection between vehicles is made possible via vehicle-to-vehicle (V2V) communication, which speeds up the exchange of vital safety data like speed, trajectory, braking status, and road conditions.
By incorporating Artificial Intelligence (AI) into V2V networks, predictive skills are improved, enabling cars to foresee possible risks and react proactively as opposed to reactively.
With an emphasis on its operational architecture, supporting technologies, recent research advancements, and future network paradigms, this study provides a thorough scientific overview of V2V communication.
The report demonstrates how next-generation wireless technologies, edge computing, and AI-driven analytics are converting vehicle networks into intelligent safety ecosystems.
Important issues are also looked at, such as interoperability, scalability, cyber security hazards, and latency limitations.
The study comes to the conclusion that AI-enabled V2V communication will be a key component of completely autonomous and accident-free transportation systems.

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