Traffic prediction using real-world transportation data

A method of predicting traffic on a road network in view of an event having an identified time and an identified location in the road network, the method comprising:

• retrieving attributes from past events on the road network;
• selecting, by a processor, a subset of the attributes that are correlated with traffic parameters comprising delayed traffic speeds, affected backlogs of vehicles, and amounts of time needed to clear backlogs of vehicles;
• discovering, by a processor, corresponding values for the traffic parameters under all combinations of the selected attributes;
• matching, by a processor, current attributes for the event in the road network to previous event attributes using the corresponding values for the traffic parameters to identify a subset of the past events;
• using, by a processor, the identified time, the identified location, and the subset of the past events to predict (i) a delayed traffic speed for the event, (ii) an affected backlog of vehicles on one or more roads approaching the event in the road network, and (iii) an amount of time needed for the affected backlog of vehicles to be cleared in the road network;
• and
• providing prediction data to a navigation device for the road network, the prediction data comprising (i) the delayed traffic speed for the event, (ii) the affected backlog of vehicles, and (iii) the amount of time needed for the affected backlog of vehicles to be cleared in the road network.