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Modeling Traveler's Day-to-Day Rerouting Behavior considering Multiday Experiences

This paper proposes a multiday nonlinear pairwise swapping dynamic (MNPSD) model to describe travelers' day-to-day selfish rerouting behaviors. By introducing a perceived route cost measure, formulated as the descending weighted average of the actual route costs experienced in the past several days, MNPSD can capture various experiential perception levels. It is proved that both stationary path flow pattern and stationary link flow pattern of MNPSD are equivalent to Wardrop user equilibrium. Given that the perceived weight decreases exponentially, numerical sensitivity analyses are executed to explore the effects of experiential perceptions on rerouting behaviors. Numerical results suggest that (1) the ultimate states of route swaps depend much more on the reaction sensitivity than on the capacity interference, (2) too much dependence on the historical experience can increase the risk of instability rather than stability, and (3) for high reaction sensitivity network, the instability can be remedied by incorporating proper perception experience.