Researchers at MIT have developed a new semi-autonomous safety system for cars that allows a driver to control the vehicle, only taking the wheel when the driver is about to exit a “safe zone”. The system uses an onboard camera and laser rangefinder to identify hazards and identify the safe zones.
System co-developer Sterling Anderson, a PhD student in MIT’s Department of Mechanical Engineering, 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. If you want to drive, it’ll just … make sure you don’t hit anything.—Sterling Anderson
The group presented details of the safety system recently at the Intelligent Vehicles Symposium in Spain.
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—self-parking cars, for example. To parallel park, a driver engages the technology by flipping a switch and releasing control of the steering 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.
Anderson and Karl Iagnemma, a principal research scientist in MIT’s Robotic Mobility Group, devised 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 example, falling asleep at the wheel and 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.
Benjamin Saltsman, manager of intelligent truck vehicle technology and innovation at Eaton Corp., (who was not involved in the research) says the system has several advantages over fully autonomous variants such as the self-driving cars developed by Google and Ford. Such systems, he says, are loaded with expensive sensors, and require vast amounts of computation to plan out safe routes.
The implications of [Anderson's] system is it makes it lighter in terms of sensors and computational requirements than what a fully autonomous vehicle would require. This simplification makes it a lot less costly, and closer in terms of potential implementation.—Benjamin Saltsman
The team hopes to pare down the system to identify obstacles using a single cellphone.
You could stick your cellphone on the dashboard, and it would use the camera, accelerometers and gyro to provide the feedback needed by the system. I think we’ll find better ways of doing it that will be simpler, cheaper and allow more users access to the technology.—Sterling Anderson
This research was supported by the United States Army Research Office and the Defense Advanced Research Projects Agency. The experimental platform was developed in collaboration with Quantum Signal LLC with assistance from James Walker, Steven Peters and Sisir Karumanchi.