A model of informational nudging in transportation networks

Building on an existing model of coupled traffic/ driver decision-making in transportation networks, this paper investigates a mechanism for influencing drivers' en route choices. We consider dynamical transportation networks in a framework where drivers' route choices are affected by their response to an announced global information, as well as by a myopic observation of the surrounding congestion levels. Such a behavior is modeled by a system of ordinary differential equations. Furthermore, a traffic recommender is introduced to provide possibly misleading global information to drivers so as to influence their route choices in a way consistent with Thaler and Sunstein's concept of (informational) nudge. Our main result shows that the traffic recommender can create and stabilize any desired equilibrium on transportation networks by assuming that drivers always tend to minimize their expected travel cost, conditional on their past experience and the announced global information.