The current paradigm for advancing autonomous driving functionalities on public roads predominantly operates within the tangible realm. Autonomous vehicles (AVs) are equipped with an array of sensors, including Lidar, cameras, radar, GPS, and on-board-unit (OBU) modems, each actively collecting data about the surrounding environment. This data is then processed through sophisticated algorithms, enhancing the vehicle's situational awareness. In our pursuit of refining autonomous driving capabilities, we leverage the AVTSC Simulator as our chosen Autonomous Vehicle (AV) simulation environment. Notably, this simulator stands out for its ability to replicate realistic urban settings and seamlessly integrate with widely used platforms such as Apollo and ROS. By harnessing the capabilities of this simulation environment, we aim to bridge the gap between real-world testing and simulated scenarios. This abstract encapsulates the essence of our strategy, emphasizing the integration of advanced sensor technologies and simulation environments for the development of autonomous driving features. Preliminary results indicate a promising 94% success rate for the proposed methodology, showcasing the efficacy of our approach in enhancing the robustness and reliability of autonomous systems.
Beyond Reality: Crafting Logical Systems for Autonomous Vehicles through Virtual Reality
2024-07-12
793146 byte
Conference paper
Electronic Resource
English
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