Baidu Research

Simulations are also increasingly essential to training autonomous driving systems, but generating high-definition computer graphics within limited budgets remains a difficult challenge. In March, we presented our augmented autonomous driving simulation (AADS) in the journal Science Robotics. Our solution augmented real-world pictures with simulated traffic flow to create photorealistic simulation images and renderings. More specifically, we used LiDAR and cameras to scan street scenes and, from that acquired trajectory data, generated plausible traffic flows for cars and pedestrians and composed them into the background. These composite images can be resynthesized with different viewpoints and sensor models (camera or LiDAR) to simulate different use cases.