A driver remotely steers a modified vehicle through an obstacle 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 researchers at MIT.

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, 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.

The “intelligent co-pilot” 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 team integrated a human perspective into their robotic system and came up with an approach to identify safe zones, or “homotopies,” rather than specific paths of travel. Instead of mapping out individual paths along a roadway, the researchers divided a vehicle’s environment into triangles, with certain triangle edges representing an obstacle or a lane’s boundary.

The researchers devised an algorithm that “constrains” obstacle-abutting edges, allowing a driver to navigate across any triangle edge except those that are constrained. If a driver is in danger of crossing a constrained edge — for instance, if he’s fallen asleep at the wheel and is about to run into a barrier or obstacle — the system takes over, steering the car back into the safe zone.

So far, the team has run more than 1,200 trials of the system, with few collisions; most of these occurred when glitches in the vehicle’s camera failed to identify an obstacle. For the most part, the system has successfully helped drivers avoid collisions. The team is also hoping to pare down the system to identify obstacles using a single cellphone.