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MIT develops AI-based 'driving buddy'
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EE Times


PORTLAND, Ore. — MIT researchers are collaborating with Volkswagen and Audi to develop an AI-based "driving buddy" that could help motorists avoid traffic jams or remind them to fill an empty gas tank.

By observing a driver's habits, the artificial intelligence tool called AIDA (Affective Intelligent Driving Agent) learns routines and how best to assist with navigation and maintenance. AIDA is being developed by Audi and the Volkswagen Group of America's Electronics Research Lab in collaboration with MIT's Personal Robots Group along with its Media Lab and SENSEable City Lab.

"The key lies in all the real-time feeds that AIDA can process, both from inside the car and real-time information about the city outside the car," said professor Carlo Ratti, director of the SENSEable City Lab. "By combining and analyzing all these feeds, AIDA can start to understand your mood [and] the goals you would like to achieve."

MIT's artificial intelligence tool called AIDA will serve as a driving buddy for Audi and Volkswagons owners.

The project was inspired by the amount of sensor data streaming in from current automotive systems used to monitor everything from weather to traffic conditions. By fusing data streams and personalizing the relevant elements, the researchers said AIDA could perform the same kind of tasks as a driving buddy.

Unlike a nagging "backseat driver," AIDA's "face" includes mood icons like a smile. Installed in the center of the dashboard, AIDA includes an array of sensors designed to interpret drivers' mood based on facial expression and other cues.

MIT's Personal Robots Group has been developing mood reading software in a quest for what it calls sociable robots.

AIDA would be capable of understanding typical human activities such as going to the store or a gas station. That ability is integrated into its database of a locale and its observations of the driver's habits (such as driving to work at the same time every week day). When the software infers that help is needed to, for instance, avoid a traffic jam, the system suggests an alternative route.

As it learns, AIDA would amass a personal database of a driver's most frequent destinations and routes, then compare them to its knowledge of environmental conditions, including local weather or special events.






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