MIT Techs Develop an ‘Intelligent Co-pilot’ for Cars

via MIT News Office

A utility vehicle equipped with a laser range finder drives through a field, avoiding obstacles without human intervention.Barrels and cones dot an open field in Saline, Mich., forming an obstacle course for a modified vehicle. A driver remotely steers the vehicle through the course from a nearby location as a researcher looks on. Occasionally, the researcher instructs the driver to keep the wheel straight—a trajectory that appears to put the vehicle on a collision course with a barrel. Despite the driver’s actions, the vehicle steers itself around the obstacle, transitioning control back to the driver once the danger has passed.

The key to the maneuver is a new semiautonomous safety system developed by Sterling Anderson, a PhD student in MIT’s Department of Mechanical Engineering, and Karl Iagnemma, a principal research scientist in MIT’s Robotic Mobility Group.

The system uses an onboard camera and laser rangefinder to identify hazards in a vehicle’s environment. The team devised an algorithm to analyze the data and identify safe zones—avoiding, for example, barrels in a field, or other cars on a roadway. The system allows a driver to control the vehicle, only taking the wheel when the driver is about to exit a safe zone.

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Anderson, who has been testing the system in Michigan since last September, describes it as an “intelligent co-pilot” that monitors a driver’s performance and makes behind-the-scenes adjustments to keep the vehicle from colliding with obstacles, or within a safe region of the environment, such as a lane or open area.

“The real innovation is enabling the car to share [control] with you,” Anderson says. “If you want to drive, it’ll just … make sure you don’t hit anything.”

The group presented details of the safety system recently at the Intelligent Vehicles Symposium in Spain.

Off the beaten path

Robotics research has focused in recent years on developing systems—from cars to medical equipment to industrial machinery—that can be controlled by either robots or humans. For the most part, such systems operate along preprogrammed paths.

As an example, Anderson points to the technology behind self-parking cars. To parallel park, a driver engages the technology by flipping a switch and taking his hands off the wheel. The car then parks itself, following a preplanned path based on the distance between neighboring cars.

While a planned path may work well in a parking situation, Anderson says when it comes to driving, one or even multiple paths is far too limiting.

“The problem is, humans don’t think that way,” Anderson says. “When you and I drive, [we don’t] choose just one path and obsessively follow it. Typically you and I see a lane or a parking lot, and we say, ‘Here is the field of safe travel, here’s the entire region of the roadway I can use, and I’m not going to worry about remaining on a specific line, as long as I’m safely on the roadway and I avoid collisions.’”

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