70 / 100

Dr. Krešimir Kušić, Motorway traffic, Best Researcher Award

Ph.D at the University of Zagreb, Croatia

Dr. Krešimir Kušić, a Croatian expert in intelligent transport systems, holds a Ph.D. in Technical Sciences from the University of Zagreb. With a rich academic journey, including a Swiss Government Excellence Scholarship, he specializes in traffic flow optimization and microsimulation modeling. As a postdoctoral researcher at the Faculty of Transport and Traffic Sciences, he leads innovative projects such as DLASIUT and SSA@EDAL, advancing learning-based systems for urban traffic control. His impactful work spans international collaborations, numerous publications, and honors, showcasing his commitment to advancing intelligent mobility and his expertise in machine learning and control systems.

Professional Profiles:

Scopus Profile

Orcid Profile

GoogleScholar profile

Researchgate profile

LinkedIn profile

📚 Education:

PhD, Technical Sciences University of Zagreb, Faculty of Transport and Traffic Sciences Duration: 2017 – 2023 Location: Zagreb, Croatia.


Work Experience

Postdoctoral Researcher Faculty of Transport and Traffic Sciences, University of Zagreb Duration: 16/10/2023 – Current City: Zagreb, Country: Croatia Department of Intelligent Transport Systems.


Expert in: Traffic flow theory Microscopic traffic simulators (SUMO and PTV Vissim) Python and Matlab Operations research: reinforcement learning, linear programming, simplex method, dynamic programming Multi-agent systems.

Research Focus

Dr. Krešimir Kušić, an accomplished researcher, focuses on advancing transportation through his expertise in Intelligent Transport Systems (ITS). With a Ph.D. in Technical Sciences, he specializes in real-time simulation and the development of digital twins for motorway dynamics. His research spans various areas, including reinforcement learning for variable speed limit control, multi-agent systems, and the impact of deep reinforcement learning on connected vehicle environments. Dr. Kušić’s work, cited extensively, reflects his commitment to enhancing traffic flow optimization, particularly in urban motorways. His comprehensive contributions showcase a dedication to innovative approaches and methodologies, positioning him as a prominent figure in the field of ITS research.

Publications (TOP NOTES):


An overview of reinforcement learning methods for variable speed limit control, Cited by 31, Publication date: 2020/7/17.


Extended variable speed limit control using multi-agent reinforcement learning, Cited by 22, Publication date: 2020/9/20.


Impact of deep reinforcement learning on variable speed limit strategies in connected vehicles environments, Cited by 19, Publication date: 2022/6/1.


Spatial-temporal traffic flow control on motorways using distributed multi-agent reinforcement learning, Cited by 15, Publication date: 2021/11/30.


Traffic flow simulators with connected and autonomous vehicles: A short review, Cited by 11, Publication date: 2021.


Krešimir Kušić | Motorway traffic | Best Researcher Award

You May Also Like