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@article{185869,
        author = {Mukesh Reddy Madadi and Kotla Harika and Muddasani Harshith and Anthireddy Mounika},
        title = {Comprehensive Autonomous Vehicle Systems: The Future of Self Driving Cars},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {3559-3564},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185869},
        abstract = {As cities grow and traffic increases, the need for smarter, safer transportation becomes more urgent. This project explores the development of an intelligent self-driving car system designed to address these modern challenges. By combining camera-based navigation with dynamic braking angle adjust- ment, the system aims to improve vehicle safety and responsive- ness in real time. Leveraging computer vision and machine learn- ing, the car can detect road elements, obstacles, and lane markers through live video processing using OpenCV and NumPy. Deep learning models built with TensorFlow and Keras enhance object recognition and decision-making capabilities. Real-time communication between system components is enabled through Python SocketIO and Flask, with Eventlet ensuring efficient, non- blocking data transfer. Altogether, this setup creates a respon- sive, reliable autonomous driving framework. Beyond personal transport, such systems have the potential to revolutionize public transit, logistics, and emergency services, making transportation safer, more accessible, and environmentally conscious.},
        keywords = {Self-Driving Cars, Autonomous Vehicles, Brak- ing Angle Control, Computer Vision, Machine Learning, Real- Time Navigation, Obstacle Detection, Deep Learning Models, Front-View Camera, Python-SocketIO, Flask, Smart Transporta- tion Systems.},
        month = {October},
        }