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Speed advisory systems for connected vehicles rely on the estimation of green(or red) light duration at signalized intersections. A particular challenge isto predict the signal phases of semi- and fully-actuated traffic lights. Inthis paper, we introduce an algorithm that processes traffic measurement datacollected from advanced detectors on road links and assigns "PASS"/"WAIT"labels to connected vehicles according to their predicted ability to go throughthe upcoming signalized intersection within the current phase. Additionalcomputations provide an estimate for the duration of the current green phasethat 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. Trafficprogression quality also benefits from our algorithm demonstrating animprovement of 20% at peak for medium traffic demand, reducing delays andidling at intersections.

Speed Advisory System Using Real-Time Actuated Traffic Light Phase Length Prediction