Seo Lab, Institute of Science Tokyo
Transportation Research with Data Science
Our research focuses on Transportation Research with Data Science, which involves investigating transportation systems and information and communication technology using theoretical and data-driven approaches to achieve a better society. We are particularly interested in emerging technologies such as automated driving, ridesharing, and connected vehicles. Our research topics include developing data-driven estimation methods for the state of transportation systems, building models to understand the behavior of these systems, and implementing control measures to optimize them for society.
Our research addresses questions such as: How can we use data to understand the actual state of the massive traffic flows moving through a large city? How can we reproduce these flows through large-scale simulation? How can we optimize transportation? And what should next-generation transportation systems built on emerging technologies look like?
Dear international students: if you are interested in applying to our lab for the graduate school admission exam, please read this application instruction and contact Prof. Seo accordingly.
Research topics
Traffic state estimation, data analysis, and control
Estimate traffic conditions of entire road networks from limited observation data; analyze and control them.
Traffic flow theory
Mathematical modeling and simulation of vehicle, pedestrian, and rail flow dynamics.
Next-gen transportation systems
Theoretical foundations for automated vehicles, ridesharing, MaaS, and urban transportation design.
Open-source software
UXsim / UNsim / FreeTSE — research outputs released as open-source software.