System optimum is usually referred to as a theoretical traffic assignment, whose main use is comparison to user equilibrium. In this paper, we investigate an advanced travel information service (ATIS) that provides the travelers system optimal routing signals, so that if all travelers comply with the signal, system optimum is achieved. We present a simple binary route-choice Agent-Based Model that includes the interaction between agents in multiple congestion sensitive road networks, under different allocation of routing signals. We find that the frequency agents receive a better signal and the allocations used by the system have a great effect over the road network convergence to system optimum. The contribution of the findings enables a great reduction in aggregate network travel time only through a behavioral change to the agents.
Klein, I., Levy, N., & Ben-Elia, E. (2017). An Agent-Based Model of a System-Optimal ATIS. In Procedia Computer Science (Vol. 109, pp. 893–898). Elsevier B.V. https://doi.org/10.1016/j.procs.2017.05.417