Information, rational expectations and network equilibria — an analytical perspective for route guidance systems

Abstract

This paper tries to provide with a unified framework for understanding how drivers act in response to exogenously provided route guidance information; and how they form subjective expectations on traffic conditions from repeated learning. The learning problems are placed in the context of iterative adjustment processes which achieve equilibrium if drivers have rational expectations. Route choice models with rational expectations find a new justification since the models appear as the limits of drivers' learning procedures. This paper is also devoted to the question of whether route guidance information can convey substantial information to drivers even if drivers behave with rational expectations of their environment. The author also tries to propose a framework for designing the optimal route guidance systems.