Autonomous Driving

Autonomous driving research aims to develop vehicles capable of navigating and operating without human intervention, prioritizing safety and efficiency. Current efforts heavily focus on improving perception (using techniques like 3D Gaussian splatting and Bird's-Eye-View representations), prediction (leveraging diffusion models, transformers, and Bayesian games to handle uncertainty), and planning (employing reinforcement learning, large language models, and hierarchical approaches for decision-making). These advancements are crucial for enhancing the reliability and safety of autonomous vehicles, with significant implications for transportation systems and the broader AI community.