Transportation Systems Lab
We are looking for under- and post-graduate students for the following research topics:
Connected and autonomous vehicular systems
Personal mobility
Adaptive traffic control systems
Cooperative adaptive cruise control
Physics-guided artificial intelligence
Digital Twin in Transportation Engineering
Traffic data science
Transit system optimization
If you are interested in these topics, please do not hesitate to contact Dr. Seunghyeon Lee (seunghyeon.lee at uos.ac.kr)
Dr. Seunghyeon Lee, an Associate Professor in the Department of Transportation Engineering, has founded the Transportation Systems Lab in 2023 to advance research in data-oriented multimodal transportation systems. The lab's work encompasses several key focus areas:
Artificial Intelligence in Transportation Engineering
The lab is exploring the application of artificial intelligence techniques to transportation engineering challenges, such as developing smart mobility solutions and enhancing traffic safety.
Emerging Mobility and Connected/Autonomous Vehicles
The lab's research agenda includes optimizing transit systems and investigating the integration of personal mobility devices in low-carbon, heterogeneous transportation environments.
Traffic Management and Control
The lab is working on developing digital twin models, cooperative intelligent transportation systems, and advanced traffic management and control strategies.
The Transportation Systems Lab's overarching philosophy aligns with the University of Seoul's vision of "Defining global excellence in higher education." By leveraging data-driven approaches and embracing multimodal transportation solutions, the lab aims to contribute to the advancement of transportation systems and infrastructure, ultimately enhancing mobility, sustainability, and safety for communities.
Key insights
To consider Stochastic characteristics of human behavior
To develop Uncomplicated models for succeeding studies
To provide Precise estimates and predictions
To be Elastic against drastic changes in transportation systems
To be Robust against uncertainty in transportation systems
Research visions
To consider Multi -sourced data sets and -modal transportation systems
To develop Associated urban transportation systems under a connected environment
To enhance the prevailing models to understand human behavior along with a signalized Network