Driving Task

The driving task in autonomous vehicles focuses on enabling safe, efficient, and comfortable navigation in diverse environments. Current research emphasizes developing robust decision-making algorithms, often employing deep reinforcement learning, generative pre-trained transformers, and game-theoretic approaches, to handle complex scenarios like lane changes and unsignalized intersections. These advancements leverage various sensor modalities (cameras, LiDAR, etc.) and large-scale datasets for training and evaluation, aiming to improve both the safety and reliability of autonomous driving systems. The ultimate goal is to create vehicles capable of navigating real-world traffic with human-like capabilities and superior safety performance.