Modeling the social-influence-based route choice behavior in a two-route network

In this paper, we first propose an instance-based learning theory (IBLT) model with social learning to study the day-to-day route choice behavior in a two-route network. We then define four indexes (i.e., efficiency, stability, cooperation, and equity) to investigate the effects of social learning on each traffic participant's route choice behavior in a two-route network. Numerical results show that social influence has some positive impacts on route choice behavior when more participants select the recommended routes. Cooperation among participants requires them to change their route choice behaviors against their natural tendencies. When each participant is very conscious of other participants’ route choice behaviors, it can alleviate the above phenomenon.