Anna Rehr — accepted AI-conference papers

2026

ParkDiffusion++: Ego Intention Conditioned Joint Trajectory Prediction for Automated Parking Using Diffusion Models

Jiarong Wei, Anna Rehr, Christian Feist, Abhinav Valada

ICRA 2026poster

Automated parking is a challenging operational domain for advanced driver assistance systems, requiring robust scene understanding and interaction reasoning. The key challenge is twofold: (i)predict multiple plausible ego intentions according to context and (ii)for each intention, predict the joint …

Cited by 0 Scholar ↗

2025

ParkDiffusion: Heterogeneous Multi-Agent Multi-Modal Trajectory Prediction for Automated Parking using Diffusion Models

Jiarong Wei, Niclas Vödisch, Anna Rehr, Christian Feist, Abhinav Valada

IROS 2025

Automated parking is a critical feature of Advanced Driver Assistance Systems (ADAS), where accurate trajectory prediction is essential to bridge perception and planning modules. Despite its significance, research in this domain remains relatively limited, with most existing studies concentrating on

Cited by 5 Source ↗Scholar ↗