A driver remotely steers a modified utility vehicle through an obstacle course of barrels and cones dotting a Michigan field. A researcher tells the driver to keep the wheel straight—putting the vehicle on a collision course with a barrel. But the vehicle steers itself around the obstacle, handing control back to the driver once the danger has passed.
A new semiautonomous safety system developed by PhD student Sterling Anderson and Karl Iagnemma of MIT’s Robotic Mobility Group uses an onboard camera and laser range finder to identify nearby hazards. An algorithm analyzes the data and identifies safe zones where there’s no danger of colliding with, say, barrels in a field or other cars on the road. When a driver is in danger of leaving a safe zone, the system takes the wheel.
Anderson and Iagnemma identified safe zones by dividing a vehicle’s environment into triangles, with certain edges representing an obstacle or lane boundary. Their algorithm “constrains” obstacle-abutting edges, allowing a driver to navigate across any unconstrained triangle edge. If a driver is in danger of crossing a constrained edge—for instance, if he’s fallen asleep and is about to run into a barrier—the system, which Anderson calls an “intelligent copilot,” steers the car back into the safe zone.
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