5 papers · 1 filter
FlowCalib: LiDAR-to-Vehicle Miscalibration Detection using Scene Flows
Ilir Tahiraj, Peter Wittal, Markus Lienkamp
Accurate sensor-to-vehicle calibration is essential for safe autonomous driving. Angular misalignments of LiDAR sensors can lead to safety-critical issues during autonomous operati…
Cal or No Cal? -- Real-Time Miscalibration Detection of LiDAR and Camera Sensors
Ilir Tahiraj, Jeremialie Swadiryus, Felix Fent +1
The goal of extrinsic calibration is the alignment of sensor data to ensure an accurate representation of the surroundings and enable sensor fusion applications. From a safety pers…
Scenario Understanding of Traffic Scenes Through Large Visual Language Models
Esteban Rivera, Jannik Lübberstedt, Nico Uhlemann +1
Deep learning models for autonomous driving, encompassing perception, planning, and control, depend on vast datasets to achieve their high performance. However, their generalizatio…
Snapshot: Towards Application-centered Models for Pedestrian Trajectory Prediction in Urban Traffic Environments
Nico Uhlemann, Yipeng Zhou, Tobias Simeon Mohr +1
This paper explores pedestrian trajectory prediction in urban traffic while focusing on both model accuracy and real-world applicability. While promising approaches exist, they oft…
MAN TruckScenes: A multimodal dataset for autonomous trucking in diverse conditions
Felix Fent, Fabian Kuttenreich, Florian Ruch +8
Autonomous trucking is a promising technology that can greatly impact modern logistics and the environment. Ensuring its safety on public roads is one of the main duties that requi…