4 papers
DiffuSearch: How Hybrid Trajectory Planning Benefits from Aligned Objectives in Diffusion and Action Space
Steffen Hagedorn, Aron Distelzweig, Alexandru P. Condurache
In trajectory planning for autonomous driving, hybrid planning architectures are often realized as a collection of disparate modules, each with its own objectives. This lack of a u…
When Planners Meet Reality: How Learned, Reactive Traffic Agents Shift nuPlan Benchmarks
Steffen Hagedorn, Luka Donkov, Aron Distelzweig +1
Planner evaluation in closed-loop simulation often uses rule-based traffic agents, whose simplistic and passive behavior can hide planner deficiencies and bias rankings. Widely use…
Learning Through Retrospection: Improving Trajectory Prediction for Automated Driving with Error Feedback
Steffen Hagedorn, Aron Distelzweig, Marcel Hallgarten +1
In automated driving, predicting trajectories of surrounding vehicles supports reasoning about scene dynamics and enables safe planning for the ego vehicle. However, existing model…
Pioneering SE(2)-Equivariant Trajectory Planning for Automated Driving
Steffen Hagedorn, Marcel Milich, Alexandru P. Condurache
Planning the trajectory of the controlled ego vehicle is a key challenge in automated driving. As for human drivers, predicting the motions of surrounding vehicles is important to…