IBM Traffic Prediction Tool
Improve transport operations and planning
Traffic congestion is worsening. Demand is increasing. Growing cities require more and more capacity. But in dense urban areas, traditional construction of new capacity is cost-prohibitive—and often physically impossible. The IBM® Traffic Prediction Tool can bring real differentiating value to municipalities struggling with traffic congestion by producing accurate traffic predictions that can be used for improving transport operations and planning.
Anticipate, manage and control traffic flow
The Traffic Predication Tool can help you build an instrumented system that uses historical traffic data and real-time traffic input from your municipality’s transport system to predict traffic flows over pre-set durations of 10, 15, 30, 45 and 60 minutes. It harnesses real-time transportation data generated by people moving through your city—in cars, on trains and on buses. By integrating all of this information, it can be analyzed and used in new ways to build a smarter transportation system. Traffic controllers can anticipate and better manage the flow of traffic to prevent the build-up of congestion. The Traffic Prediction Tool can enable more intelligent use of your city's existing infrastructure. Multimodal, real-time management of your transportation system can deliver more capacity from the existing network, delaying or obviating the need for massive infrastructure investments.
Gain more accurate traffic predictions
Harnessing real-time traffic data and using it to improve your transportation system can result in shorter commute times, thus increasing customer satisfaction and ridership of public transit systems. And this increase in public transit usage can reduce carbon emissions. The Traffic Prediction Tool:
Take advantage of innovative technology
Developed by IBM's Watson Research Laboratories, the Traffic Prediction Tool is a patent-pending technology for predicting traffic flows and speeds on road segments. The tool provides the characteristics—such as volume and speed—that best describe the traffic state into the short- and medium-term future. The technology makes use of adaptive statistical techniques in conjunction with automated error correction for multiple time horizons. It has been tested in Singapore, where the Land Transport Authority is working with IBM and others to develop technology that will provide one-hour traffic predictions.