May 10, 2013, 9:56 AM — Researchers are developing machine-to-machine (M2M) communication technology that allows cars to exchange data with each other, meaning vehicles will soon know what the cars all around you are doing on the highway.
Your car, for instance, could "see" the velocity of nearby vehicles and react when they turn or brake suddenly. And with computer algorithms and predictive models, your car will be able to predict where other vehicles are going and measure the other drivers' skills -- ensuring you're safe from their bad moves.
"We're even imagining in the future cars would be able to ask other cars, 'Hey, can I cut into your lane?' Then the other car would let you in," said Jennifer Healey, a research scientist with Intel.
Intel is working with National Taiwan University on M2M connectivity between vehicles as a way to make roads more predictable and safe.
"Car accidents are the leading cause of death in people 16 to 19 in the United States. And 75% of these accidents have nothing to do with drugs or alcohol," said Healey, who delivered a TED Talk on the subject in March (see video below).
She recounted her first accident when she was a young driver: The driver she was following on a highway slammed on his brakes and the resulting collision totaled her car. "I think we can transform the driving experience by letting our cars talk to each other," she said.
That idea came from caravanning, Healey said, citing an available, but-not-yet-deployed technology that uses direct line of site infrared (IR) and a range finder in order to automatically adjust the speed of cars so they can travel at a measured distance from each other. In other words, they're electronically tethered to one another.
Instead of using IR, the researchers wanted something that is omnidirectional. They tried radio communications, but quickly discovered that omnidirectional radio signals tend to bounce off vehicles, making them unreliable at high speeds.
So Healey and university researchers began using unique Internet Protocol addresses for vehicles, which would allow them to be instantly identifiable to nearby cars around on the same network.
"Imagine a group of cars traveling down the road together as an ad hoc network," she said. "Let's say you are three cars ahead of me and I get those IP packets that say I'm the packet from the blue car whose GPS position is here. Now I can associate my position with the unique ID of that physical blue object."
Along with a steady stream of data a bout the GPS location of cars around you, your car could also know drivers' intentions.
"I could [upload] my route to the cloud and, for example, let cars around me know I'll be on Rte. 101 for the next 10 minutes, and then I'm going to exit," Healey said. "You're augmenting on-road perception."