Árpád Fehérمشاهده پروفایل
استادیار
Árpád Fehér is an Assistant Professor at the Department of Transport and Vehicle Control, Faculty of Transportation Engineering and Vehicle Engineering at Budapest University of Technology and Economics. He also maintains an affiliation with the Systems and Control Theory Research Laboratory at the Hungarian Academy of Sciences Research Institute for Experimental Computer Science (SZTAKI) since 2022. Having completed his PhD in 2023 with a dissertation on "Reinforcement learning-based motion planning methods," Dr. Fehér has established himself as a promising researcher in the field of autonomous vehicle technology. His educational background includes: PhD in Engineering from Budapest University of Technology and Economics (2023) Prior academic work at Budapest University of Technology and Economics since 2013 Dr. Fehér's research focuses on the intersection of artificial intelligence and vehicle control systems. His work primarily addresses motion planning, trajectory control, and reinforcement learning applications for autonomous vehicles. His research has evolved from foundational work on trajectory planning algorithms to more complex implementations involving real-world testing and mixed reality environments. He has made significant contributions to developing practical AI solutions that can be implemented in actual vehicle control systems, bridging the gap between theoretical AI approaches and automotive engineering requirements. His publication record demonstrates a consistent focus on advancing autonomous vehicle technology through innovative applications of machine learning. The trends in his work show progression from basic trajectory planning algorithms to more sophisticated implementations involving closed-loop control systems, real-world testing, and integration with simulation environments. His research spans both theoretical algorithm development and practical implementation challenges. Dr. Fehér has received recognition through citations of his work, with his 2020 paper "Hierarchical Evasive Path Planning using Reinforcement Learning and Model Predictive Control" in IEEE Access accumulating 24 citations, indicating significant impact in the field. His advising approach appears to be collaborative and hands-on, with numerous co-authored publications involving students and junior researchers. His work on educational platforms for control education suggests a commitment to developing practical teaching methods that connect theoretical concepts with real-world applications. Dr. Fehér is actively involved in the Systems and Control Theory Research Laboratory at SZTAKI, where his team works on advancing autonomous vehicle technologies through a combination of AI research and practical engineering solutions. His laboratory focuses on implementing and testing advanced control algorithms in both simulated and real-world environments.
