61 citations · 64 across the 9 of their papers we have counts for
4 papers · 1 filter
Semantic Map Learning of Traffic Light to Lane Assignment based on Motion Data
Thomas Monninger, Andreas Weber, Steffen Staab
Understanding which traffic light controls which lane is crucial to navigate intersections safely. Autonomous vehicles commonly rely on High Definition (HD) maps that contain infor…
LMR: Lane Distance-Based Metric for Trajectory Prediction
Julian Schmidt, Thomas Monninger, Julian Jordan +1
The development of approaches for trajectory prediction requires metrics to validate and compare their performance. Currently established metrics are based on Euclidean distance, w…
Exploring Navigation Maps for Learning-Based Motion Prediction
Julian Schmidt, Julian Jordan, Franz Gritschneder +2
The prediction of surrounding agents' motion is a key for safe autonomous driving. In this paper, we explore navigation maps as an alternative to the predominant High Definition (H…
SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
Thomas Monninger, Julian Schmidt, Jan Rupprecht +5
Understanding traffic scenes requires considering heterogeneous information about dynamic agents and the static infrastructure. In this work we propose SCENE, a methodology to enco…