3 accepted papers
"Accurate 3D object detection is vital for automated driving. While lidar sensors are well suited for this task, they are expensive and have limitations in adverse weather conditions. 3+1D imaging radar sensors offer a cost-effective, robust alternative but face challenges due to their low resolutio…
Offline reinforcement learning (RL) provides a framework for learning decision-making from offline data and therefore constitutes a promising approach for real-world applications such as automated driving (AD). Especially in safety-critical applications, interpretability and transferability are cruc
It is widely assumed that considering vehicle interactions for trajectory prediction can significantly improve accuracy. All environmental sensors of an automated vehicle (AV) suffer from occlusion. Therefore, relevant vehicles can be occluded by others, especially in dense traffic situations, and r