  Speed advisory systems for connected vehicles rely on the estimation of green
(or red) light duration at signalized intersections. A particular challenge is
to predict the signal phases of semi- and fully-actuated traffic lights. In
this paper, we introduce an algorithm that processes traffic measurement data
collected from advanced detectors on road links and assigns "PASS"/"WAIT"
labels to connected vehicles according to their predicted ability to go through
the upcoming signalized intersection within the current phase. Additional
computations provide an estimate for the duration of the current green phase
that can be used by the Speed Advisory System to minimize fuel consumption.
Simulation results show 95% prediction accuracy, which yields up to 30%
reduction in fuel consumption when used in a driver-assistance system. Traffic
progression quality also benefits from our algorithm demonstrating an
improvement of 20% at peak for medium traffic demand, reducing delays and
idling at intersections.
