PLANNING AND LEADERSHIP FOR A BETTER WORLD
PLANNING AND LEADERSHIP FOR A BETTER WORLD Signing up for smarter traveler services could allow text messages to be sent to your cell phone just before you set out on your daily commute, predicting which will be the least congested route that day.
Traffic congestion forces U.S. commuters to waste an average of a week per year stuck in traffic—not to mention the 28 gallons of gas and over $800 in expenses incurred, according to Texas A&M University. In Silicon Valley, traffic congestion is even worse—15 percent worse—forcing commuters there to waste a cumulative total of 10 million annual hoursjust sitting in traffic.
IBM survey ranking the emotional and economic toll of commuting in each city on a scale of one to 100―with 100 being the most onerous. (Source: IBM)
For years, traffic problems were thought to be solved by adding capacity—more lanes, ramps and interchanges—but, unfortunately, these measures only caused further urbanization resulting in renewed congestion just a few years after adding capacity. Ramp metering and light synchronization have helped to smooth out congestion, but smart analysis software that can learn about traffic patterns and then predict and suggest alternative routes could actually eliminate congestion by routing the over-capacity travelers onto alternate routes.
Conventional GPS navigation units today already suggest alternative routes to take commuters around traffic congestion, but the Smarter Traffic Initiative aims to one-up these technologies with artificial intelligence that learns and predicts, thereby giving commuters advice on how to prevent congestion before it happens.
A cooperative effort by the California Department of Transportation (Caltrans), the California Center for Innovative Transportation (CCIT) and IBM, the Smarter Traffic Initiative aims to give San Francisco Bay Area subscribers smart anti-congestion messages automatically delivered to their cell phones.
"We're helping take the guesswork out of commuting," said Stefan Nusser, functional manager, Almaden Services Research, IBM. "We're blending the automated learning of travel routes with state-of-the-art traffic prediction of those routes to give travelers timely information that can help them make decisions about the best way to get to their destination."
Made smart by the Traffic Prediction Tool developed by IBM Research (Almaden, Calif.), its smart predictive algorithms continuously analyze congestion data. The system has already been proven effective in Singapore, which is developing a system that gives one-hour traffic predictions. The U.S. initiative will use Caltrans data to make Bay Area predictions—monitoring traffic conditions and subscriber locations, and then providing expert advice on commuting routes.
IBM's data-centric Traffic Prediction Tool will advise not only on commuting by car, but will also encourage alternatives including the fastest, most cost-effective and the most eco-friendly routes to a destination. The goal of the project is to motivate commuters on highways, rail lines and urban roads by giving them real-time choices regarding better ways to get to their destination—from mass transit to private car.
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