IBM driver tool predicts traffic jams

IBM is testing smartphone software designed to predict traffic jams and warn motorists before they even take to the roads.

IBM said that its employees in the San Francisco and Silicon Valley areas of Northern California have been testing technology that “will ultimately help drivers around the world” avoid fouled traffic.

Those involved in the pilot project agree to have location-sensing capabilities in their smartphones automatically track where they drive and when, according to IBM Smarter Traveler programme manager John Day.

The information is fed through the internet to computers that identify patterns such as commutes to and from work.

Meanwhile, data collected from roadway censors commonly used for online traffic maps is analysed to determine conditions that usually lead to trouble.

For example, congestion at a certain off-ramp or bridge entrance may consistently lead to traffic backing up in another area. The results are combined to form personalised predictions of when a motorist is apt to run into highway headaches.

“We wanted to take advantage of analytic tools to provide predictive capabilities; to get correlations with minor slowdowns and major ones that happen after that,” Mr Day said.

“So you can run a query at any point for a journey and predict 35 or 40 minutes in advance what it will look like, then couple that with a personal approach for the individual traveller.”

The smartphone application lets people receive customised alerts warning of probable traffic trouble before they set out on commutes or other routine drives.The service is powered by a “first-of-its-kind learning and predictive analytics tool” called the Traffic Prediction Tool developed by IBM Research.

TPT continuously analyses congestion data, commuter locations and expected travel start times throughout a metropolitan region that can affect commuters on highways, rail-lines and urban roads.

The pilot project has been going on for about five months.