Parting with misconceptions about learning-based vehicle motion planning D Dauner, M Hallgarten, A Geiger, K Chitta Conference on Robot Learning, 1268-1281, 2023 | 34 | 2023 |
Rethinking integration of prediction and planning in deep learning-based automated driving systems: a review S Hagedorn, M Hallgarten, M Stoll, A Condurache arXiv preprint arXiv:2308.05731, 2023 | 9 | 2023 |
From prediction to planning with goal conditioned lane graph traversals M Hallgarten, M Stoll, A Zell 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 7 | 2023 |
Stay on Track: A Frenet Wrapper to Overcome Off-road Trajectories in Vehicle Motion Prediction M Hallgarten, I Kisa, M Stoll, A Zell arXiv preprint arXiv:2306.00605, 2023 | 3 | 2023 |
Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios? M Hallgarten, J Zapata, M Stoll, K Renz, A Zell arXiv preprint arXiv:2404.07569, 2024 | | 2024 |
Conditional Unscented Autoencoders for Trajectory Prediction F Janjoš, M Hallgarten, A Knittel, M Dolgov, A Zell, JM Zöllner arXiv preprint arXiv:2310.19944, 2023 | | 2023 |
Conditional Unscented Autoencoders for Trajectory Prediction A Zell, JM Zöllner, M Dolgov, A Knittel, M Hallgarten, F Janjoš arXiv, 2023 | | 2023 |
From Prediction to Planning With Goal Conditioned Lane Graph Traversals A Zell, M Stoll, M Hallgarten arXiv, 2023 | | 2023 |
Stay on Track: A Frenet Wrapper to Overcome Off-road Trajectories in Vehicle Motion Prediction A Zell, M Stoll, I Kisa, M Hallgarten arXiv, 2023 | | 2023 |
Supplementary Material for Stay on Track: A Frenet Wrapper to Overcome Off-road Trajectories in Vehicle Motion Prediction M Hallgarten, I Kisa, M Stoll, A Zell | | |
Predictive Driver Model: A Technical Report D Dauner, M Hallgarten, A Geiger, K Chitta | | |
Supplementary Material for Parting with Misconceptions about Learning-based Vehicle Motion Planning D Dauner, M Hallgarten, A Geiger, K Chitta | | |