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Vehicle bypassing is known to negatively affect delays at traffic diverges.However, due to the complexities of this phenomenon, accurate and yet simplemodels of such lane change maneuvers are hard to develop. In this work, wepresent a macroscopic model for predicting the number of vehicles that bypassat a traffic diverge. We take into account the selfishness of vehicles inselecting their lanes; every vehicle selects lanes such that its own cost isminimized. We discuss how we model the costs experienced by the vehicles. Then,taking into account the selfish behavior of the vehicles, we model the lanechoice of vehicles at a traffic diverge as a Wardrop equilibrium. We state andprove the properties of Wardrop equilibrium in our model. We show that therealways exists an equilibrium for our model. Moreover, unlike most nonlinearasymmetrical routing games, we prove that the equilibrium is unique under mildassumptions. We discuss how our model can be easily calibrated by running asimple optimization problem. Using our calibrated model, we validate it throughsimulation studies and demonstrate that our model successfully predicts theaggregate lane change maneuvers that are performed by vehicles for bypassing ata traffic diverge. We further discuss how our model can be employed to obtainthe optimal lane choice behavior of the vehicles, where the social or totalcost of vehicles is minimized. Finally, we demonstrate how our model can beutilized in scenarios where a central authority can dictate the lane choice andtrajectory of certain vehicles so as to increase the overall vehicle mobilityat a traffic diverge. Examples of such scenarios include the case when bothhuman driven and autonomous vehicles coexist in the network. We show howcertain decisions of the central authority can affect the total delays in suchscenarios via an example.

A Game Theoretic Macroscopic Model of Bypassing at Traffic Diverges with Applications to Mixed Autonomy Networks