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@article{174432,
        author = {Shraman Sandip Patil and Atharv Pandurang Lokare and Abhay Prashant Hanchate and Anannya Sanjay Powar and Mrs. Amruta M Kate and Mr. Sushil B Magdum},
        title = {A Review Paper On The Rise of Autonomous Vehicles},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {3942-3946},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174432},
        abstract = {The development of autonomous vehicles (AVs) has propelled the need for sophisticated simulation environments that replicate real-world driving conditions for training, testing, and validating self-driving algorithms. The CARLA (Car Learning to Act) simulator offers an open-source, high-fidelity environment that supports a variety of sensors and dynamic traffic scenarios, making it a valuable tool for advancing AV research. This paper explores CARLA’s capabilities, focusing on its integration with machine learning (ML), reinforcement learning (RL), and classical control techniques to enhance the decision-making processes of autonomous agents. We analyze CARLA’s sensor fidelity, dataset features, and its integration with frameworks like ROS and OpenAI Gym. Additionally, the paper addresses the challenges and ethical considerations in using such simulators, particularly regarding the generalizability of algorithms and the safety of deploying AVs in real-world settings. The findings underscore CARLA’s significance in bridging the gap between simulation and real-world deployment while also highlighting areas for further research and improvement.},
        keywords = {Artificial Intelligence, Autonomous Vehicle, Machine Learning, Deep Learning, Predictive Analytics, Incident Response, Automation.},
        month = {March},
        }