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This paper models adaptive cruise control combined with automated lane change assist to investigate the energy consumption improvements that such a system may provide compared to conventional adaptive cruise control. Automatically executing a lane change may improve efficiency, for example, when following a vehicle that is slowing to make a turn. Changing lanes while maintaining speed is hypothesized to be more efficient than staying in the same lane as the turning vehicle and reducing speed. The differences in such scenarios are simulated in a virtual environment using a cuboid model with idealized sensors. The ego-vehicle detects scenarios and performs a lane change to reduce or eliminate required speed changes. The results of the simulations compare the energy content of the resulting drive cycle as an idealized method to measure energy consumption for each cruise control strategy.