András RÖVID, PhD.
Dr. András Rövid is a Senior Research Fellow at the Department of Automotive Technologies at the Budapest University of Technology and Economics. His research focuses on environment perception for automated vehicles and the real-time digital representation of transport environments. His work plays a key role in the development of cooperative perception solutions based on vehicle–infrastructure interaction, as well as the intelligent transportation systems built upon them.
Education and Professional Background
Dr. András Rövid obtained his MSc degree in Computer Engineering in 2001 from the Technical University of Košice, and earned his PhD in 2005 from the Budapest University of Technology and Economics in the fields of mechanical engineering and transportation sciences.
In 2006, he was awarded a postdoctoral research fellowship by the Suzuki Foundation, followed by the János Bolyai Research Scholarship in 2008. Between 2013 and 2014, he conducted research in Japan under the Invitation Fellowship Program of the Japan Society for the Promotion of Science (JSPS), focusing primarily on image processing and machine vision.
Since 2018, he has been a Senior Research Fellow at the Faculty of Transportation Engineering and Vehicle Engineering at BME, where he also serves as the professional head of the Cooperative Environment Perception Research Group.
His areas of expertise include environment perception for automated vehicles, real-time digital twin modeling of transport environments, and cooperative perception based on vehicle–infrastructure integration.
Professional Experience and Collaborations
Between 2009 and 2011, Dr. Rövid served as Deputy Head of the Institute at the John von Neumann Faculty of Informatics, Óbuda University.
From 2015 to 2018, he worked in Japan as an R&D engineer at Kyoto Robotics, where he was involved in the development of 3D robotic vision systems for industrial robots, focusing primarily on bin-picking automation. From 2017, he also led the professional work of the machine vision group. Kyoto Robotics is a recognized leader in 3D vision, robotic perception, and robot control technologies.
Between 2014 and 2015, he was an invited researcher and lecturer at Shizuoka University within the framework of the “Asia Bridge Program”. In 2012, he received the “Researcher of the Year” award from Óbuda University.
He has participated in numerous national and international research projects, often serving as research topic leader or professional coordinator, frequently managing multidisciplinary research teams.
Under his professional leadership, a smart road technology capable of generating a real-time digital twin of the transport environment—covering both static and dynamic elements—has been developed. The M1–M7 smart road section demonstrating this technology is considered a globally unique solution.
He regularly serves as a reviewer for international scientific journals, primarily in the fields of machine vision and environment perception for autonomous vehicles.
Selected Publications
Varkonyi-Koczy, A. Rovid and T. Hashimoto,
Gradient-Based Synthesized Multiple Exposure Time Color HDR Image
IEEE Transactions on Instrumentation and Measurement, vol. 57, no. 8, pp. 1779-1785, Aug. 2008, doi: 10.1109/TIM.2008.925715.
Rövid, A., Szeidl, L. and Várlaki, P. (2015)
Integral Operators in Relation to the HOSVD-Based Canonical Form.
Asian J. Control, 17: 459–466. doi: 10.1002/asjc.1017.
Csonthó and A. Rövid
Pillar-X: Integrating Self-Learned Image Features to Improve 3D Object Detection
IEEE Access, vol. 13, pp. 83071-83081, 2025, doi: 10.1109/ACCESS.2025.3567658.
Cserni and A. Rövid
Semantic Shape and Trajectory Reconstruction for Monocular Cooperative 3D Object Detection
IEEE Access, vol. 12, pp. 167153-167167, 2024, doi: 10.1109/ACCESS.2024.3484672.
Edit Tóth-Laufer, András Rövid, Márta Takács
Error calculation of the HOSVD-based rule base reduction in hierarchical fuzzy systems
Fuzzy Sets and Systems, Volume 307, 2017, Pages 67-82, ISSN 0165-0114
Rovid et al.
Digital Twin and Cloud Based Remote Control of Vehicles
2024 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST), Dallas, TX, USA, 2024, pp. 154-167, doi: 10.1109/MOST60774.2024.00024.
Zhao et al.
A Communication-Latency-Aware Co-Simulation Platform for Safety and Comfort Evaluation of Cloud-Controlled ICVs
IEEE Internet of Things Journal, vol. 13, no. 4, pp. 6217-6229, 15 Feb.15, 2026, doi: 10.1109/JIOT.2025.3634326.
