Berkeley duo's plan to solve traffic jams: Hyper-fast lanes for self-driving cars

The two graduate students at the University of California, Berkeley, have devised a system that would have tightly-packed clusters of autonomous vehicles zipping past local traffic at speeds of more than 100mph, all on existing roadways. They call it Hyperlane, and it works a lot like high-speed toll lanes already do, only with a central computer controlling everything.

Although fully autonomous cars are not yet legal on most public roads, manufacturers like Volvo and Tesla already offer autonomous features on their vehicles – adaptive cruise control and, in some cases, systems that steer the car with limited driver input.

Barrs and Chen came up with Hyperlane after taking a close look at proposed high-speed rail systems like the troubled Los Angeles to San Francisco route. The bottom line is that high-speed rail is expensive – at its current, ever-rising cost estimate, the California rail project would cost $139m per mile. So the two researchers concocted a mashup of bullet train and dedicated toll lane, which they say would only cost about $12m per mile.