Engineers have developed a new semiautonomous safety system that uses an onboard camera and laser rangefinder to identify hazards in a vehicle’s environment.
Sterling Anderson and Karl Iagnemma from MIT 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.
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 said.
“If you want to drive, it’ll just … make sure you don’t hit anything,” Anderson said.
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 neighbouring 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.
Anderson and Iagnemma integrated this human perspective into their robotic system.
The team 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 findings were presented at the Intelligent Vehicles Symposium in Spain.