AI-Powered Vehicular Activity Optimization Network
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Dr T.Parimalam
Dr. Anusha B
Dr. P Ramya
Abstract
Smart traffic control management systems that use AI incorporate continuous improvements to meet emerging challenges and utilize emerging technologies. Further refinement of AI algorithms, improving real-time adaptability and responsiveness, is critical to ensuring optimal traffic flow and security. Integration with emerging technologies such as connected and autonomous vehicles play a key role for a seamless and integrated transportation ecosystem. On-going research and development focus on addressing potential biases, improving data accuracy, and refining decision-making processes. Additionally, exploring the scalability of these systems to accommodate the growing complexity of urban environments and global urbanization trends will be a priority. Collaboration between researchers, policymakers and industry stakeholders will be essential to shape the future path of AI-powered traffic control, and create better and more sustainable urban mobility solutions. Briefly introduce the importance of network traffic management and the challenges it poses. Briefly introduce the importance of network traffic management and the challenges it poses. Discuss the role of AI, particularly machine learning (ML) and deep learning (DL), in addressing these challenges. Clearly state the aim of your paper—to propose a new AI-based approach that improves network traffic management. Discuss the role of AI, particularly machine learning (ML) and deep learning (DL), in addressing these challenges. Clearly state the aim of our paper to propose a new AI-based approach that improves network traffic management. We present experimental results on a simulated network to demonstrate the effectiveness of our proposed method. A simulation is conducted to compare the performance of the proposed method with traditional network traffic handling methods, and the results show that the proposed method outperforms traditional methods in terms of network utilization and packet loss.
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