  Automated vehicles can gather information about surrounding traffic and plan
safe and energy-efficient driving behavior, which is known as eco-driving.
Conventional eco-driving designs only consider preceding vehicles in the same
lane as the ego vehicle. In heavy traffic, however, vehicles in adjacent lanes
may cut into the ego vehicle's lane, influencing the ego vehicle's eco-driving
behavior and compromising the energy-saving performance. Therefore, in this
paper, we propose an eco-driving design that accounts for neighbor vehicles
that have cut-in intentions. Specifically, we integrate a leader-follower game
to predict the interaction between the ego and the cut-in vehicles and a
model-predictive controller for planning energy-efficient behavior for the
automated ego vehicle. We show that the leader-follower game model can
reasonably represent the interactive motion between the ego vehicle and the
cut-in vehicle. More importantly, we show that the proposed design can predict
and react to neighbor vehicles' cut-in behaviors properly, leading to improved
energy efficiency in cut-in scenarios compared to baseline designs that
consider preceding vehicles only.
