A researcher's algorithm breakthrough could mean that we won't have to wait for car-to-car communication or fully autonomous vehicles before journey times are cut and unnecessary traffic jams eliminated.

Berthold Horn, a professor in MIT's Department of Electrical Engineering and Computer Science was so infuriated by unexplained traffic jams -- where cars come to a standstill for no apparent reason -- that he developed and tested an algorithm.

His algorithm understands and mitigates unexplained bottlenecks that could be incorporated into existing adaptive cruise control systems -- a standard feature on many top-end cars.

Adaptive cruise control uses sensors such as radar and rangefinders to monitor the speed of the vehicle in front in order to keep a safe distance.

So if your car is traveling at 100 km/h and the car in front slows down to 80km/h, the system backs off the accelerator or gently applies the brakes to maintain the same safe distance.

Horn's research shows that if these existing systems were adapted to use his algorithm and to monitor the speed of vehicles behind as well as ahead, that "traffic flow instabilities" could be eradicated.

This is because traffic flow instabilities arise because the actions of the driver at the head of a queue -- for instance accelerating or braking hard -- create a wave of amplification that ripples through the line of vehicles behind.

If, for instance the first car decelerates, each following vehicle would also have to respond more quickly and forcefully in order to match their speed. Than means the tenth car in the line could be forced to perform an emergency stop, which would in turn bring all traffic from the 11th car onwards to a complete standstill and a traffic jam is born.

"Suppose that you introduce a perturbation by just braking really hard for a moment, then that will propagate upstream and increase in amplitude as it goes away from you," Horn says. "It's kind of a chaotic system. It has positive feedback, and some little perturbation can get it going."

If a system can monitor bilateral distance -- i.e., between the car in front and behind -- then it will be able to slow down a vehicle at a rate that is fast enough to avoid hitting the car in front but is not so fast or abrupt as to cause the car behind into an emergency stop.

Horn's algorithm has been thoroughly tested via computer modeling and takes into account a number of real-life traffic flow variables such as drivers' reaction times and the likelihood that they have a heavy right foot. The only variation in his results was the time taken to smooth out a disruption.

As big a breakthrough as this could be, there is a catch. In order for the system to have the desired effect it would need to be installed on a large percentage of cars.

Thanks to the costs of the sensors involved, forward-facing adaptive cruise control is only a standard feature on cars such as Mercedes, BMWs, Audis, Jaguars, Lexus and Cadillacs, and integrating a second, rear-facing system would double the cost of such systems.

However, Horn points out that a bilateral control system could be built using cameras rather than sensors.

"There are several techniques," Horn says. "One is using binocular stereo, where you have two cameras, and that allows you to get distance as well as relative velocity. The disadvantage of that is, well, two cameras, plus alignment. If they ever get out of alignment, you have to recalibrate them."