Within environments linked to intelligent transport, the efficiency and reliability of vehicular communication protocols are crucial, especially in dense urban environments. This work proposes an enhancement to the ITS-G5 protocol by integrating adaptive mechanisms based on real-time traffic analysis. The approach relies on intelligent adjustment of communication parameters to optimize data flow, reduce latency, and also avoid congestion-related losses. By continuously analyzing the network’s state, the system dynamically adapts to varying traffic conditions, thus improving the scalability and responsiveness of Its-G5. Experimental evaluations carried out in simulated urban scenarios have shown that the proposed solution significantly enhances communication quality and resource management. Compared to the standard protocol, notable improvements were observed in terms of data delivery rate, latency reduction and overall network performance. These results demonstrate the relevance of incorporating intelligent decision-making into existing communication architectures. The proposed method opens promising perspectives for the deployment of more resilient and efficient networks, contributing to safer and more coordinated autonomous vehicle navigation in complex traffic environments.