| Hierarchical evasive path planning using reinforcement learning and model predictive control Á Fehér, S Aradi, T Bécsi IEEE Access 8, 187470-187482, 2020 | 37 | 2020 |
| Hybrid DDPG Approach for Vehicle Motion Planning PG Á. Fehér, Sz. Aradi, F. Hegedűs,T. Bécsi ICINCO 2019, July 29-31, 2019, in Prague, Czech Republic, P. 422 - 429, 2019 | 30* | 2019 |
| Q-learning based reinforcement learning approach for lane keeping A Feher, S Aradi, T Becsi 2018 IEEE 18th International Symposium on Computational Intelligence and …, 2018 | 19 | 2018 |
| Mixed-reality automotive testing with sensoris B Varga, M Szalai, Á Fehér, S Aradi, T Tettamanti Periodica Polytechnica Transportation Engineering 48 (4), 357-362, 2020 | 15 | 2020 |
| Autonomous vehicle function experiments with low-cost environment sensors T Bécsi, S Aradi, Á Fehér, G Gáldi Transportation Research Procedia 27, 333-340, 2017 | 12 | 2017 |
| Highway environment model for reinforcement learning T Bécsi, S Aradi, Á Fehér, J Szalay, P Gáspár IFAC-PapersOnLine 51 (22), 429-434, 2018 | 11 | 2018 |
| Fast prototype framework for deep reinforcement learning-based trajectory planner Á Fehér, S Aradi, T Bécsi Periodica Polytechnica Transportation Engineering 48 (4), 307-312, 2020 | 9 | 2020 |
| Proving ground test of a ddpg-based vehicle trajectory planner Á Fehér, S Aradi, T Bécsi, P Gáspár, Z Szalay 2020 European Control Conference (ECC), 332-337, 2020 | 9 | 2020 |
| Online trajectory planning with reinforcement learning for pedestrian avoidance Á Fehér, S Aradi, T Bécsi Electronics 11 (15), 2346, 2022 | 8 | 2022 |
| Highly automated electric vehicle platform for control education Á Fehér, S Aradi, T Bécs, P Gáspár IFAC-PapersOnLine 53 (2), 17296-17301, 2020 | 6 | 2020 |
| A gépi tanulás szerepe és hatásai a közlekedésben T Bécsi, S Aradi, Á Fehér Közlekedéstudományi Szemle 70 (1), 54-65, 2020 | 2 | 2020 |
| An Automated Valet Parking Experiment D Doba, A Feher, L Szoke 2022 IEEE 1st International Conference on Cognitive Mobility (CogMob …, 2022 | 1 | 2022 |
| Sávdetektáló algoritmus teljesítményének összehasonlítása C++ és Python nyelven D Dániel, F Árpád, A Szilárd IFFK 2019: XIII. Innováció és fenntartható felszíni közlekedés.(2019), 2019 | 1 | 2019 |
| Path planning via reinforcement learning with closed-loop motion control and field tests Á Fehér, Á Domina, Á Bárdos, S Aradi, T Bécsi Engineering Applications of Artificial Intelligence 142, 109870, 2025 | | 2025 |
| Modular Path-Following Control Architecture for Unmanned Ground Vehicles in ROS 2 Environment Á Szabó, DK Doba, Á Fehér, S Aradi 2025 IEEE 23rd World Symposium on Applied Machine Intelligence and …, 2025 | | 2025 |
| Mozgástervezés Előzési Manőverekhez Közúti Környezetben D Losonczi, Á Fehér Magyar Mérnökakadémia (MMA), 2024 | | 2024 |
| Reinforcement learning-based motion planning methods Á Fehér PQDT-Global, 2023 | | 2023 |
| Nagy pontosságú GNSS alapú mérőrendszer kifejlesztése nagysebességű járműves tesztek támogatásához K Gábor, F Árpád, S Ádám, A Szilárd | | 2021 |
| Local Motion Planning for Overtaking Maneuvers in a Rural Road Environment D Losonczi, A Fehér, S Aradi, L Palkovics | | |
| Double Lane Change Path Planning Using Reinforcement Learning with Field Tests Á Fehér, S Aradi1a, T Bécsi | | |