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@article{174216,
        author = {Kakumani Lalitha and Gadelavarthi Sasi Kumar and Gorantla Narendra and Choppara Saketh and B.Lalitha Rajeswari},
        title = {AI Based Traffic Management System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {3211-3215},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174216},
        abstract = {Efficient traffic management is a crucial challenge in modern urban environments, where increasing vehicular congestion leads to delays, fuel wastage, and pollution. This research presents an AI-driven traffic management system that leverages machine learning techniques to predict traffic volume and optimize flow.
Regression algorithms are employed to analyze real-time traffic data, enabling dynamic signal adjustments to reduce congestion. By integrating AI-driven predictions, this system enhances traffic efficiency, minimizes travel time, and contributes to sustainable urban mobility. Experimental results demonstrate the effectiveness of the proposed approach in improving traffic flow and reducing bottlenecks.},
        keywords = {},
        month = {March},
        }