Washington, D.C. – IBM has announced a new research initiative to build personalized travel routes for commuters to avoid traffic gridlock. The company announced the initiative at a “smart transportation” event in Washington.
IBM researchers are using advanced analytics to develop adaptive traffic systems that will intuitively learn traveller patterns and behaviour, providing more dynamic travel safety and route information to travellers than is available today.
The new models will predict the outcomes of varying transportation routes to provide a personalized recommendation to get commuters where they need to go in the fastest time. The project intends to provide information that goes well beyond traditional traffic reports, after-the-fact devices that only indicate when drivers are already in traffic jams, or Web-based applications that give estimated travel time in traffic. The models will include such factors as traffic collisions, the commuter’s location, current and planned road construction, most-travelled days of the week, expected work start times, local events that may affect traffic, alternate options such as rail or ferries, parking availability, and weather.
Working with state and local transportation agencies, IBM plans to launch pilot projects for select sets of commuters to analyze, test and refine the new systems. The information will be communicated via the Web through mobile voice interaction, combined with advanced mapping applications on mobile devices.
“The data exists to give commuters and transportation agencies a better way to manage traffic, but today, it’s not connected,” said Gerry Mooney, IBM’s general manager of public sector. “IBM has the ability to correlate all of this information to better predict demand, optimize capacity to help improve traveller and highway safety as well as reduce our impact on the environment.”
According to the Texas Transportation Institute, traffic congestion in the U.S. burns enough fuel each year to fill 58 supertankers, and wastes enough time to consume 105 million weeks of vacation.