Knowledge is Power for CommutersApril 15, 2011 By: Melanie Martella, Sensors
Although my commute typically consists of a trip down the stairs and through the kitchen, I am continually fascinated by the tools that exist to help commuters make their daily slog to the office even a smidge less painful. Easing traffic congestion decreases gas consumption and pollution and I'd hope that by making commuters less stressed, it would also increase their productivity and make the world just a touch happier. Yes, I am an optimist, why do you ask?
Out here in the woods, our traffic woes are less about congestion than about the delays caused by inclement weather, accidents, and the people who insist on driving 10 mph below the speed limit on two-lane roads but for urban dwellers it's all about too many vehicles sharing the road at once. Once upon a time (February 2008, if we're being picky) the California Center for Innovative Transportation (CCIT) at the University of California at Berkeley started a project called Mobile Century. The goal of the project was to use GPS-equipped cellphones to collect traffic data from 100 vehicles driving on a 10 mile stretch of highway in the San Francisco Bay region. And this project was sufficiently successful that Mobile Century spawned the Mobile Millennium project which aimed to take the traffic data from GPS-enabled phones and use it to provide real-time traffic info to drivers.
This week, IBM announced a new collaboration with the Mobile Millennium group within CCIT and the California Department of Transportation (Caltrans) that aims to take this idea further: to use traffic data to give drivers predictive information about what they'll find on the roads-based on their route history and informed by real-time traffic info-before they're trapped in a tailback and unable to take evasive maneuvers. The Smarter Traveler research initiative takes traffic data from the existing highway and traffic-sensing systems as well as real-time data collected from GPS-enabled cellphones (carried by people participating in the project) and then feeds it into IBM's Traffic Prediction Tool. Participating drivers then get a series of alerts sent to their phones, based on their preferred route, giving them a heads up on what to expect and (ideally) allowing them to avoid troublespots completely. Also, the lucky, lucky transportation authorities get an additional tool to help them achieve more efficient traffic flow. Win, win!
It's also another exercise in acquiring, managing, and doing useful things with very large data sets, which is an important skill in and of itself, when you consider the continuing development of large-scale monitoring systems for water management, the Smart Grid, structural health, environmental sensing, oil and gas exploration, and who knows what else! The pilot project itself is deeply interesting but, as the smartphone has proven itself an excellent springboard for innovation, the large data sets and the successful mining and use thereof have similar potential.
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