Hendrik Berkemeyer — accepted AI-conference papers

2023

IPCC-TP: Utilizing Incremental Pearson Correlation Coefficient for Joint Multi-Agent Trajectory Prediction

Dekai Zhu, Guangyao Zhai, Yan Di, Fabian Manhardt, Hendrik Berkemeyer, Tuan Tran +3

CVPR 2023poster

Reliable multi-agent trajectory prediction is crucial for the safe planning and control of autonomous systems. Compared with single-agent cases, the major challenge in simultaneously processing multiple agents lies in modeling complex social interactions caused by various driving intentions and road…

Cited by 19 Source ↗PDF ↗Scholar ↗

2021

Feasible and Adaptive Multimodal Trajectory Prediction with Semantic Maneuver Fusion

Hendrik Berkemeyer, Riccardo Franceschini, Tuan Tran, Lin Che, Gordon Pipa

ICRA 2021poster

Predicting trajectories of participating vehicles is a crucial task towards full and safe autonomous driving. General unconstrained machine learning methods often report unrealistic predictions, and need to be combined with different motion constraints. Existing work either defines some shallow mane…

Cited by 12 Source ↗Scholar ↗