A Path-Based Day-To-Day Traffic Dynamics Model with One-Step Forward-Thinking

This paper establishes a path-based day-to-day traffic dynamics model to capture travelers’ one-step forward-thinking behavior in rerouting process. The model is termed as the forward-thinking nonlinear pairwise swapping process (FT-NPSP) model. We theoretically prove that FT-NPSP does not necessarily lead to the known UE state when reaching stability. Numerical experiments are also conducted on the classical Braess network to characterize the model. The numerical results suggest that travelers’ one-step forward-thinking behavior shows complex impact on day-to-day network traffic evolution, making the flow evolution much more unpredictable than the model without forward-thinking. This might in some degree break our intuitive cognition on forward-thinking travel behavior that it more perhaps promotes the stability of network traffic evolution. This study may deepen our understanding on the complex network traffic evolution, and then contribute to the development of more useful managements.