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Tamas Hegedus
Tamas Hegedus
Institute for Computer Science and Control
Verified email at mail.bme.hu
Title
Cited by
Cited by
Year
Optimal control of overtaking maneuver for intelligent vehicles
B Németh, P Gáspár, T Hegedűs
Journal of Advanced Transportation 2018, 1-11, 2018
292018
Graph-based multi-vehicle overtaking strategy for autonomous vehicles
T Hegedűs, B Németh, P Gáspár
IFAC-PapersOnLine 52 (5), 372-377, 2019
152019
Design of a low-complexity graph-based motion-planning algorithm for autonomous vehicles
T Hegedűs, B Németh, P Gáspár
Applied Sciences 10 (21), 7716, 2020
142020
Model predictive control design for overtaking maneuvers for multi-vehicle scenarios
B Németh, T Hegedűs, P Gáspár
2019 18th European Control Conference (ECC), 744-749, 2019
132019
Design of Model Free Control with tuning method on ultra-local model for lateral vehicle control purposes
T Hegedűs, D Fényes, B Németh, Z Szabó, P Gáspár
2022 American Control Conference (ACC), 4101-4106, 2022
102022
Handling of tire pressure variation in autonomous vehicles: an integrated estimation and control design approach
T Hegedűs, D Fényes, B Németh, P Gáspár
2020 American Control Conference (ACC), 2244-2249, 2020
92020
Robust control design for autonomous vehicles using neural network-based model-matching approach
D Fényes, T Hegedus, B Németh, P Gáspár
Energies 14 (21), 7438, 2021
82021
Challenges and possibilities of overtaking strategies for autonomous vehicles
T Hegedűs, B Németh, P Gáspár
Periodica Polytechnica Transportation Engineering 48 (4), 320-326, 2020
82020
Improving sustainable safe transport via automated vehicle control with closed-loop matching
T Hegedűs, D Fényes, B Németh, P Gáspár
Sustainability 13 (20), 11264, 2021
72021
Design framework for achieving guarantees with learning-based observers
B Németh, T Hegedűs, P Gáspár
Energies 14 (8), 2039, 2021
62021
Robust control design using ultra-local model-based approach for vehicle-oriented control problems
D Fényes, T Hegedűs, B Németh, Z Szabó, P Gáspár
2022 European Control Conference (ECC), 1746-1751, 2022
52022
Performance guarantees on machine-learning-based overtaking strategies for autonomous vehicles
B Németh, T Hegedűs, P Gáspár
2020 European Control Conference (ECC), 136-141, 2020
42020
Observer design with performance guarantees for vehicle control purposes via the integration of learning-based and LPV approaches
D Fényes, T Hegedűs, B Németh, P Gáspár
2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 122-127, 2021
32021
Mpc based semi-active suspension control for overtaking maneuvers
T Hegedűs, B Németh, P Gáspár
Periodica Polytechnica Transportation Engineering 49 (3), 224-230, 2021
22021
Multi-objective trajectory design for overtaking maneuvers of automated vehicles
T Hegedüs, B Németh, P Gáspár
IFAC-PapersOnLine 53 (2), 15566-15571, 2020
22020
Implementation and design of ultra-local model-based control strategy for autonomous vehicles
T Hegedűs, D Fényes, Z Szabó, B Németh, L Lukács, R Csikja, P Gáspár
Vehicle System Dynamics, 1-24, 2023
12023
Combined LPV and ultra-local model-based control design approach for autonomous vehicles
D Fényes, T Hegedűs, B Németh, Z Szabó, P Gáspár
2022 IEEE 61st Conference on Decision and Control (CDC), 3303-3308, 2022
12022
Combined observer design for road vehicles using LPV-based and learning-based methods
D Fényes, T Hegedűs, B Németh
2022 30th Mediterranean Conference on Control and Automation (MED), 1074-1079, 2022
12022
LPV control for autonomous vehicles using a machine learning-based tire pressure estimation
D Fényes, T Hegedűs, B Németh, P Gáspár, D Koenig, O Sename
2020 28th Mediterranean Conference on Control and Automation (MED), 212-217, 2020
12020
Cooperation Strategy for Optimal Motion of Aerial and Ground Vehicles
T Hegedűs, D Fényes, B Németh, P Gáspár
2023 31st Mediterranean Conference on Control and Automation (MED), 19-24, 2023
2023
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