  Vehicle trajectory optimization is essential to ensure vehicles travel
efficiently and safely. This paper presents an infrastructure assisted
constrained connected automated vehicles (CAVs) trajectory optimization method
on curved roads. This paper systematically formulates the problem based on a
curvilinear coordinate which is flexible to model complex road geometries.
Further, to deal with the spatial varying road obstacles, traffic regulations,
and geometric characteristics, two-dimensional vehicle kinematics is given in a
spatial formulation with exact road information provided by the infrastructure.
Consequently, we applied a multi-objective model predictive control (MPC)
approach to optimize the trajectories in a rolling horizon while satisfying the
collision avoidances and vehicle kinematics constraints. To verify the
efficiency of our method, a numerical simulation is conducted. As the results
suggest, the proposed method can provide smooth vehicular trajectories, avoid
road obstacles, and simultaneously follow traffic regulations, which is robust
to road geometries and disturbances.
