Giacomo Como

Department of Mathematical Sciences, Politecnico di Torino, Italy

Talk: Dynamic Pricing and Information Design in Transportation Networks

Transportation systems are essential for the smooth operation of modern societies. Ever-growing loads and limited infrastructure capacity lead to congestion and create significant challenges. To mitigate these issues, it is important to understand the interplay between the network and the user behavior and to influence the latter. In this talk, we discuss two fundamental mechanisms to induce socially desired behaviors in transportation networks: tolls and information design. 

First, we study transportation networks controlled by dynamic feedback tolls. We focus on a multiscale model, whereby the dynamics of the traffic flows are intertwined with those of the routing choices. The latter are influenced by the current traffic state of the network as well as by dynamic tolls controlled in feedback by the system planner. We prove that a class of decentralized monotone flow-dependent tolls allows for globally stabilizing the transportation network around a generalized Wardrop equilibrium. In particular, our results imply that using de-centralized marginal cost tolls, stability of the dynamic transportation network is guaranteed around the social optimum traffic assignment. This is particularly remarkable as such dynamic feedback tolls can be computed in a fully local way without the need for any global information about the network structure, its state, or the exogenous network loads.

Second, we study optimal information provision in transportation networks when users are strategic and the delay functions of the links of the network are affected by an uncertain network state. An omniscient planner observes the network state and discloses information to the users, with the goal of minimizing the expected travel time at the user equilibrium. Since public signal policies are known to be inefficient in Bayesian routing games, we focus on private signals sent to the users' personal devices. We formulate the general information design problem, and then provide sufficient conditions on the network topology and on the moments of the random network state under which optimality may be achieved by information provision. In particular, our results imply that optimality is more easily achieved when the uncertainty of the random network state is large.

Bio: Giacomo Como is a Professor at the Department of Mathematical Sciences, Politecnico di Torino, Italy, and a Senior Lecturer at the Automatic Control Department of Lund University, Sweden. He received the B.Sc., M.S., and Ph.D. degrees in Applied Mathematics from Politecnico di Torino, in 2002, 2004, and 2008, respectively. He was a Visiting Assistant in Research at Yale University in 2006–2007 and a Postdoctoral Associate at the Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, from 2008 to 2011. He currently serves as Senior Editor of the IEEE Transactions on Control of Network Systems and Associate Editor of Automatica. He has been serving as Associate Editor of the IEEE Transactions on Network Science and Engineering and of the IEEE Transactions on Control of Network Systems and as the chair of the IEEE-CSS Technical Committee on Networks and Communications. He was the IPC chair of the IFAC Workshop NecSys’15 and a semi-plenary speaker at the International Symposium MTNS’16. He is the recipient of the 2015 George S. Axelby Outstanding Paper Award. His research interests are in dynamics, information, and control in network systems with applications to cyber-physical systems, infrastructure networks, and social and economic networks.