  We derive time and energy-optimal control policies for a Connected Autonomous
Vehicle (CAV) to complete lane change maneuvers in mixed traffic. The
interaction between CAVs and Human-Driven Vehicles (HDVs) requires designing
the best possible response of a CAV to actions by its neighboring HDVs. This
interaction is formulated using a bilevel optimization setting with an
appropriate behavioral model for an HDV's. Then, an iterated best response
(IBR) method is used to determine a Nash equilibrium. However, we also show
that when a common and simple-to-detect condition applies, the optimal
lane-changing policy is in fact independent of HDV behavior with a CAV changing
lanes by cooperating with another CAV in the target lane and always merging
ahead of it. Thus, the dependence on the interaction between CAVs and HDVs may
be eliminated in such cases. Simulation results are included to show the
effectiveness of our controllers in terms of cost, safety guarantees, and
disruption to the traffic flow when uncontrollable HDVs are present.
