  Trajectory planning in automated driving typically focuses on satisfying
safety and comfort requirements within the vehicle's onboard sensor range. This
paper introduces a method that leverages anticipatory road data, such as speed
limits, road slopes, and traffic lights, beyond the local perception range to
optimize energy-efficient braking trajectories. For that, coasting, which
reduces energy consumption, and active braking are combined to transition from
the current vehicle velocity to a lower target velocity at a given distance
ahead. Finding the switching instants between the coasting phases and the
continuous control for the braking phase is addressed as an optimal trade-off
between maximizing coasting periods and minimizing braking effort. The
resulting switched optimal control problem is solved by deriving necessary
optimality conditions. To facilitate the incorporation of additional
feasibility constraints for multi-phase trajectories, a sub-optimal alternative
solution based on parametric optimization is proposed. Both methods are
compared in simulation.
