Future Autonomous

Future autonomous systems, primarily focusing on autonomous vehicles, aim to create self-driving vehicles capable of safe and efficient navigation in complex environments. Current research emphasizes improving perception through advanced computer vision techniques like Bird's-Eye View (BEV) representations and leveraging large language models (LLMs) for decision-making and human-vehicle interaction, often employing deep reinforcement learning and federated learning for data processing and model training. These advancements are crucial for enhancing safety, optimizing energy consumption, and enabling personalized driving experiences, with significant implications for transportation, logistics, and urban planning.