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Scientist develops 'smart car system' that can tell if you are driving wrong

Drivers may soon be able tell if they are driving wrong, thanks to a new research by Indian scientist.

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Drivers may soon be able tell if they are driving wrong, thanks to a new research by Indian scientist.

Assistant professor Ashutosh Saxena has come up with an algorithm that can predict if you're going to commit an error while driving. The computer can guess the driver's intentions a few seconds in advance by monitoring a driver's head movements and watching the road ahead. This can be lifesaving tool as it will help the driver take the safest course on road.

Cornell University professor, Saxena , who has jointly developed the system, explained that though there are many systems which work outside the vehicle, internal monitoring of the driver will be the next leap in ensuring automobile safety. Combining driver anticipation with radar or cameras to locate other vehicles, the car's safety system could warn the driver when the anticipated action could be dangerous. The warning might be a light, a sound or even a vibration.

Drawing on street maps and GPS information, the system also might give an "illegal turn" message if the driver was planning to turn the wrong way on a one-way street. To develop the system, Saxena and colleagues recorded video of 10 drivers, along with video of the road ahead, for 1,180 miles of freeway and city driving over a period of two months. A computer using face detection and tracking software identified head movements and learned to associate them with turns and lane changes, so that the final system can anticipate possible actions the driver may take. The computer continuously reports its anticipations to the car's central safety system.

In a test against another data set of videos with different drivers, the system correctly predicted the driver's actions 77.4% of the time, anticipating an average 3.53 seconds in advance. Those few extra seconds might save lives, Saxena said. However, the system still needs refinement, the researchers noted.

The system will be demonstrated in a workshop on at the 2015 Robotic Science and Systems conference in Rome.

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