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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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We consider a dynamic game in which multiple ride-hailing companies, each comprised of a large number of drivers, are competing over a shared traffic infrastructure to minimize individual teams’ total travel time. In realistic scenarios where the underlying traffic systems are described by nonlinear, stochastic, and high-dimensional dynamical systems, analyzing such a game is a challenging task. In this talk, we discuss two novel mathematical frameworks that offer powerful tools for such an analysis. As the first framework, we introduce the class of linearly-solvable mean-field games (MFGs). This is a special class of the MFGs where an equilibrium can be found simply by solving a linear system. This is in contrast to the conventional MFG framework where coupled Hamilton-Jacobi-Bellman and Fokker-Planck-Kolmogorov equations must be analyzed. Traffic congestion mitigation mechanism based on linearly-solvable MFG is discussed. In the second framework, we discuss Kappen’s path-integral control and its generalization to dynamic games. We demonstrate that a Nash equilibrium among multiple ride-hailing companies in a stochastic game with nonlinear dynamics can found numerically by forward-in-time Monte-Carlo sampling.
