Autonomous Driving System

Autonomous driving systems aim to create vehicles capable of navigating and operating without human intervention, prioritizing safety and efficiency. Current research heavily focuses on improving perception (using multi-sensor fusion, advanced object detection, and robust mapping techniques, often incorporating bird's-eye-view representations and Kalman filtering), prediction (leveraging large language models and incorporating uncertainty), and planning (employing model predictive control and actor-critic algorithms, sometimes integrated with differentiable optimizers). These advancements are crucial for addressing challenges like data scarcity, environmental variability, and ensuring robustness against adversarial attacks, ultimately contributing to safer and more reliable autonomous vehicles.