Towards Next-Generation Autonomous Vehicle Communication in Smart Cities: A Blockchain and AI Perspective
DOI:
https://doi.org/10.29194/NJES.29020301Keywords:
Blockchain, Federated Learning, Reinforcement Learning, AVs, Smart Cities, Secure Data Transmission, Intelligent Transportation SystemsAbstract
Autonomous vehicles (AVs) rely on continuous vehicle-to-vehicle (V2V) and vehicle-to-everything (V2E) communication to support shared perception, traffic direction, and decision making. Integrating real-time data, connectivity, and precise navigation will revolutionize urban mobility by facilitating sustainable, secure, and highly efficient transportation options. The rapid evolution of AVs within smart cities necessitates robust and secure data transmission methods to ensure efficient and safe operations. This paper proposes a next-generation communication framework that integrates blockchain with artificial intelligence (AI) to enable secure, decentralized, and adaptive AVs network. Blockchain is employed as a distributed trust layer to ensure data immutability, decentralized identity management, and transparent transaction validation among vehicles and roadside infrastructure. AI techniques are incorporated to support intelligent threat detection, dynamic resource allocation, anomaly identification, and context-aware decision making. The integration between blockchain and AI enhances trust establishment while maintaining system scalability and real-time responsiveness. The proposed architecture introduces a layered design that separates communication, consensus, and intelligence components, allowing efficient integration with edge computing and 5G-enabled vehicular environments. This research contributes a unified conceptual framework for secure and intelligent autonomous vehicle communication, highlighting how blockchain and AI can jointly address critical limitations in next-generation vehicular networks and support the evolution of trustworthy, resilient, and scalable smart mobility ecosystems.
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