Information design for congestion minimization in transportation networks

We study an information design problem to reduce congestion in transportation networks. In presence of an uncertain network state, the central planner may sends private signals to the users, with the goal of steering the user equilibrium towards the system optimum flow. We consider private signals and provide sufficient conditions under which optimality may be achieved by information provision in networks with arbitrary number of parallel links and affine delay functions. Our results imply that optimality is more easily achieved in presence of large uncertainty of the random variables of the delay functions of the links of the network.