Predicting Traffic Jams

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IBM is developing a new traffic analysis system that can predict where traffic jams will occur before the driver finds him or herself stuck in one.  The system uses predictive modeling, incorporating data from road sensors, weather conditions, historical traffic data, and real-time GPS data from taxis.  Road tested in Singapore, Finland, and New Jersey, the system has been able to accurately predict traffic volume 85% to 93% and travel speeds 87% to 95% of the time.  The modeling system can predict the occurrence of a traffic jam one hour before it occurs.

Read more: Predictive Modeling Warns Drivers One Hour before Jams Occur


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