  In this paper, we present an optimal control framework to address motion
coordination of connected automated vehicles (CAVs) in the presence of
human-driven vehicles (HDVs) in merging scenarios. Our framework combines an
unconstrained trajectory solution of a low-level energy-optimal control problem
with an upper-level optimization problem that yields the minimum travel time
for CAVs. We predict the future trajectories of the HDVs using Newell's
car-following model. To handle potential deviations of HDVs' actual behavior
from the predicted one, we design a safety filter for CAVs based on control
barrier functions. The effectiveness of the proposed control framework is
demonstrated via simulations with heterogeneous human driving behaviors.
