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@article{171266,
        author = {Rohit Singh and Dr. Nidhi Saxena},
        title = {Autonomous Vehicle Navigation System using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {3126-3130},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171266},
        abstract = {Autonomous vehicles (AVs) are rapidly evolving technologies that promise to reshape the transportation landscape by removing the need for human intervention in driving. The core challenge in autonomous driving lies in enabling the vehicle to safely navigate complex environments while processing a vast array of sensory inputs. This paper explores the use of machine learning (ML) for autonomous vehicle navigation, focusing on sensor data fusion, reinforcement learning algorithms, and neural network models for real-time decision-making. By integrating these technologies, we aim to develop a robust navigation system capable of responding to dynamic road conditions. Key experimental results demonstrate significant advancements in autonomous navigation, accuracy, and safety, presenting a potential framework for the next generation of self-driving vehicles.},
        keywords = {Autonomous vehicles, machine learning, reinforcement learning, neural networks, navigation system, sensor fusion, real-time decision-making, deep learning.},
        month = {December},
        }