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Martin Stoll
Martin Stoll
Research Engineer, Robert Bosch GmbH
Verified email at de.bosch.com
Title
Cited by
Cited by
Year
HERWIG++ 2.6 release note
K Arnold, L d'Errico, S Gieseke, D Grellscheid, K Hamilton, ...
arXiv preprint arXiv:1205.4902, 2012
932012
Collective intelligence recommender system for travel information and travel industry marketing platform
M Stoll
US Patent App. 11/625,157, 2007
882007
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
262023
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
262023
Tracking New Physics at the LHC and beyond
M Spannowsky, M Stoll
Physical Review D 92 (5), 054033, 2015
232015
Travel industry marketing platform
M Stoll
US Patent App. 12/710,753, 2010
192010
Reconstruction of vectorlike top partner from fully hadronic final states
M Endo, K Hamaguchi, K Ishikawa, M Stoll
Physical Review D 90 (5), 055027, 2014
172014
Vetoed jet clustering: The mass-jump algorithm
M Stoll
Journal of High Energy Physics 2015 (4), 1-15, 2015
162015
Stay on track: A frenet wrapper to overcome off-road trajectories in vehicle motion prediction
M Hallgarten, I Kisa, M Stoll, A Zell
2024 IEEE Intelligent Vehicles Symposium (IV), 795-802, 2024
112024
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
62024
How to decontaminate overlapping fat jets
K Hamaguchi, SP Liew, M Stoll
Physical Review D 92 (1), 015012, 2015
62015
The integration of prediction and planning in deep learning automated driving systems: A review
S Hagedorn, M Hallgarten, M Stoll, AP Condurache
IEEE Transactions on Intelligent Vehicles, 2024
52024
Scaling Planning for Automated Driving using Simplistic Synthetic Data
M Stoll, M Mazzola, M Dolgov, J Mathes, N Möser
arXiv preprint arXiv:2305.18942, 2023
32023
Computer-Implemented Method and System for Training a Planning Model
J Mathes, M Mazzola, M Stoll, M Dolgov
US Patent App. 18/767,605, 2025
2025
Method and Apparatus for Generating at Least One Training Travel Trajectory for Training a Driving Mode of a Self Driving Vehicle
M Stoll, M Mazzola, M Dolgov
US Patent App. 18/753,037, 2024
2024
SELECTING A RESPONSE TO A TRAFFIC SITUATION FOR DRIVING ASSISTANCE SYSTEMS AND AUTOMATED DRIVING SYSTEMS
A Desies, M Stoll
US Patent App. 18/579,067, 2024
2024
Method for Behavior Planning of an Ego Vehicle as Part of a Traffic Scene
J Mathes, M Mazzola, M Stoll, M Dolgov
US Patent App. 18/441,846, 2024
2024
Computer-implemented method for behavior planning of an at least partially automated ego vehicle with a specified navigation destination
M Hallgarten, M Stoll
US Patent App. 18/406,737, 2024
2024
Selection of Driving Maneuvers for at Least Semi-Autonomously Driving Vehicles
F Schmitt, M Stoll, J Goth, HA Banzhaf, JM Doellinger, M Hanselmann
US Patent App. 18/255,849, 2024
2024
Dynamics-Dependent Behavioral Planning for at least Partially Self-Driving Vehicles
SJ Etesami, M Stoll
US Patent App. 18/252,457, 2024
2024
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