Algorithm Theory for Mobility

In the mobility society of the near future, a flexible response to environmental changes will be required to realize a society wherein each individual can continue to be comfortable. Systems, services, and infrastructure related to mobility will be implemented, and automated vehicles will travel in an automatically controlled transportation system that is highly “safe, comfortable, convenient, and fair.” Automation eliminates traffic congestion and minimizes energy consumption. The most important factor in realizing such a society is quality assurance. Our group aims to construct an algorithmic theory that can mathematically guarantee the quality of automation, mobility, etc., which is the foundation of a mobility society.

Our group develops a basic algorithmic theory for mobility when there is more than one subject, using criteria such as equilibrium, stability, and no-envy. For example, a ride-sharing platform needs to match the most appropriate driver to each passenger request that comes in one after another. If matching takes too long, then dissatisfied passengers may cancel their requests. To perform online optimization and perform fair matching in such a dynamic situation, a multi-subjective algorithm is required. When considering mobility, it is also essential to develop algorithms for transportation networks and other networks. Our group will work on the development and integration of network algorithms, mechanism design for multi-agent systems, and online optimization.

Advisor