## 1 Introduction  
As autonomous vehicles (AVs) become an integral part of modern transportation, ensuring the safety and reliability of vehicle communication systems is of paramount importance. Autonomous vehicles rely on interconnected networks for data exchange between vehicles and urban infrastructure, which poses significant risks, including cyberattacks, data tampering, and impersonation. These vulnerabilities can undermine the security of AVs and their ability to make accurate decisions in real-time traffic scenarios. Blockchain technology offers a promising solution [1; 2; 3] to these challenges by providing a decentralized, immutable ledger that increases data integrity [4] and security. By integrating blockchain with AI-driven predictive algorithms, AVs can communicate securely in vehicular ad hoc networks (VANETs) [5; 6; 7], which are critical for reducing traffic congestion, improving decision-making, and increasing overall road safety. The cryptographic functions of the blockchain ensure that the data exchanged between vehicles are tamper-proof and that private user information remains secure. Recent research shows the potential of combining AI and blockchain in AV systems to increase security, decentralize data access, and protect against common attacks such as data tampering and Sybil attacks [2; 3; 8; 9]. This paper examines the role of blockchain technology in improving the security of autonomous vehicle networks. It analyzes the extent to which it is able to secure communication systems and improve the trustworthiness of AI-based decision-making processes. By addressing these key challenges, blockchain can serve as an important component in building a safe and efficient future for autonomous transportation. In this paper, we propose an architecture that combines blockchain technology with AI-based predictive models, especially reinforcement learning, to improve the security of autonomous vehicle communication systems. Our implementation not only secures the data exchanged between vehicles but also improves decision-making processes by protecting against data manipulation. We have designed and implemented this architecture as a proof of concept to demonstrate its practicality in real vehicle networks. This implementation shows the potential of the blockchain to revolutionize the safety of autonomous vehicles and pave the way for more secure and trustworthy AV systems. By enabling secure data sharing and decentralized decision making, our solution lays the foundation for the integration of autonomous vehicles into broader urban infrastructures and advances the vision of smart and connected cities of the future. In this work, we have implemented an architecture that addresses these challenges based on previous research. Our architecture allows vehicles to communicate either directly or through a master node. Road data and sensor information are collected from the nearest roadside units (RSUs) and forwarded to a blockchain ledger infrastructure deployed at the edge layer. These data are then processed and validated before being sent to a cloud layer where predictive AI models are stored and continuously trained with real-time inputs. These models are fed back to the vehicles and infrastructure to reduce congestion and improve road safety. We have integrated the Byzantine Fault Tolerance protocol to ensure a robust consensus across the blockchain network, and smart contracts [10] manage participant authentication, data storage, and AI model sharing between entities. Implemented as a proof of concept, this architecture demonstrates the potential of the blockchain for securing AV systems and paves the way for its integration into advanced smart cities. It can be further customized to support more advanced autonomous driving simulators such as CARLA [11], and it can also be deployed in various cloud environments that support blockchain-as-a-service.