Human-Social Information Sciences

Road Transportation and Traffic C13

  • Prof. Takashi Akamatsu
  • Assoc. Prof. Shunsuke Hayashi
Keywordstransportation planning, spatial economic systems, infrastructure, system optimization, mathematical programming, equilibrium problems

Planning and management of spatial economic systems / Theory and applications of optimization

This group consists of Akamatsu laboratory and Hayashi laboratory.

(i) Akamatsu Labo

Akamatsu Labo studies mathematical and computational methodologies for planning/managing urban/transportation systems in the following three fields.

Transportation Science & Transportation Planning

We develop novel transportation demand management schemes to solve road congestion problems by exploiting recent advances in information technologies and computational mechanism design theory.

Regional Science & Spatial Economics

Most of the world's population is strikingly concentrated in a limited number of areas. We study mathematical models to explain the economic mechanisms of such agglomeration patterns in geographical space.

Investment Science & Mathematical Finance

Urban infrastructures are exposed to various risks due to changes in economic environment. We develop control-theoretic methods to achieve better decisions for investment / management of infrastructure systems under uncertainty.

(ii) Hayashi Labo

Our research interest is to study theory and applications of optimization. The mathematical optimization is one of typical methodologies for solving real problems appearing in the various fields such as traffic engineering, communication engineering, urban planning, game theory, financial engineering, operations research, etc. In our laboratory, we not only study how to make an optimization model from the real problem, but also analyze its mathematical property or develop an algorithm to solve it.

  • Evolutionary process of agglomeration patterns in the course of decreasing transportation cost (Spatial Period Doubling Bifurcation)

  • Graphical expression of optimization problem