| Survey of deep reinforcement learning for motion planning of autonomous vehicles S Aradi IEEE Transactions on Intelligent Transportation Systems, 2020 | 101 | 2020 |
| Security issues and vulnerabilities in connected car systems T Bécsi, S Aradi, P Gáspár 2015 International Conference on Models and Technologies for Intelligent …, 2015 | 75 | 2015 |
| Design of lane keeping algorithm of autonomous vehicle O Törő, T Becsi, S Aradi Periodica Polytechnica Transportation Engineering 44 (1), 60-68, 2016 | 49 | 2016 |
| Highly automated vehicle systems P Gáspár, Z Szalay, S Aradi BME MOGI, 2014 | 32 | 2014 |
| Model based trajectory planning for highly automated road vehicles F Hegedüs, T Bécsi, S Aradi, P Gápár IFAC-PapersOnLine 50 (1), 6958-6964, 2017 | 27 | 2017 |
| Design of predictive optimization method for energy-efficient operation of trains S Aradi, T Bécsi, P Gáspár 2014 European Control Conference (ECC), 2490-2495, 2014 | 20 | 2014 |
| A predictive optimization method for energy-optimal speed profile generation for trains S Aradi, T Bécsi, P Gáspár 2013 IEEE 14th International Symposium on Computational Intelligence and …, 2013 | 19 | 2013 |
| Policy gradient based reinforcement learning approach for autonomous highway driving S Aradi, T Becsi, P Gaspar 2018 IEEE Conference on Control Technology and Applications (CCTA), 670-675, 2018 | 18 | 2018 |
| Motion planning for highly automated road vehicles with a hybrid approach using nonlinear optimization and artificial neural networks F Hegedüs, T Bécsi, S Aradi, P Gáspár Strojniski vestnik-Journal of Mechanical Engineering 65 (3), 148-160, 2019 | 15 | 2019 |
| Lane change prediction using Gaussian classification, support vector classification and neural network classifiers O Rákos, S Aradi, T Bécsi Periodica Polytechnica Transportation Engineering 48 (4), 327-333, 2020 | 13 | 2020 |
| Hybrid DDPG approach for vehicle motion planning Á Fehér, S Aradi, F Hegedüs, T Bécsi, P Gáspár SciTePress, 2019 | 13 | 2019 |
| Control oriented modeling of an electro-pneumatic gearbox actuator A Szabo, T Becsi, P Gaspar, S Aradi 2018 European Control Conference (ECC), 2623-2628, 2018 | 13 | 2018 |
| Highly automated vehicle systems G Péter, S Zsolt, A Szilárd BME MOGI, 2014 | 12 | 2014 |
| Sensitivity and performance evaluation of multiple-model state estimation algorithms for autonomous vehicle functions O Törő, T Bécsi, S Aradi, P Gáspár Journal of Advanced Transportation 2019, 2019 | 10 | 2019 |
| Highway environment model for reinforcement learning T Bécsi, S Aradi, Á Fehér, J Szalay, P Gáspár IFAC-PapersOnLine 51 (22), 429-434, 2018 | 10 | 2018 |
| Autonomous vehicle function experiments with low-cost environment sensors T Bécsi, S Aradi, Á Fehér, G Gáldi Transportation Research Procedia 27, 333-340, 2017 | 10 | 2017 |
| 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 | 9 | 2018 |
| Guaranteed peaks of spacing errors in an experimental vehicle string G Rödönyi, P Gáspár, J Bokor, S Aradi, Z Hankovszki, R Kovács, ... IFAC Proceedings Volumes 45 (13), 759-764, 2012 | 9 | 2012 |
| Hierarchical evasive path planning using reinforcement learning and model predictive control Á Fehér, S Aradi, T Bécsi IEEE Access 8, 187470-187482, 2020 | 8 | 2020 |
| Analysis and experimental verification of faulty network modes in an autonomous vehicle string G Rödönyi, P Gáspár, J Bokor, S Aradi, Z Hankovszki, R Kovács, ... 2012 20th Mediterranean Conference on Control & Automation (MED), 884-889, 2012 | 8 | 2012 |
