Abstract: Methods and systems to improve the accuracy of traffic signal state change predictions are disclosed. Predictions can be broadcast to vehicle drivers or autonomous systems to improve safety, fuel efficiency and reduce delays. Predictions for fixed-time signals are generated based on their scheduled timing plan and the current clock/time, but these predictions are subject variations, for example, due to traffic signal controller clock drift. Real-time actual, not predicted, data is collected and utilized to correct for these variations. Further, real-time probe data is collected and used to validate correctness of the generated predictions in real time. In one embodiment, GPS data from travelers' devices is utilized to assess validity of the generated predictions, looking particularly at signal stop line crossings relative to predicted green time window. If crossings observed in real time contradict the predicted signal state, the data service providing predictions to users may be suspended.

Abstract: Methods and systems to improve the accuracy of traffic signal state change predictions are disclosed. Predictions can be broadcast to vehicle drivers or autonomous systems to improve safety, fuel efficiency and reduce delays. Predictions for fixed-time signals are generated based on their scheduled timing plan and the current clock/time, but these predictions are subject variations, for example, due to traffic signal controller clock drift. Real-time actual, not predicted, data is collected and utilized to correct for these variations. Further, real-time probe data is collected and used to validate correctness of the generated predictions in real time. In one embodiment, GPS data from travelers' devices is utilized to assess validity of the generated predictions, looking particularly at signal stop line crossings relative to predicted green time window. If crossings observed in real time contradict the predicted signal state, the data service providing predictions to users may be suspended.