Berkeley duo’s plan to solve traffic jams: hyper-fast lanes for self-driving cars – Benjamin Preston Last modified on Saturday 3 June 2017 07.01 EDT


Anthony Barrs and Baiyu Chen’s Hyperlane system proposes clusters of self-driving cars zipping past local traffic at 100mph, controlled by a central computer

Hyperlane works a lot like existing dedicated commuter lanes, only instead of paying extra to use them, the separate lanes are only for autonomous vehicles.
Hyperlane works a lot like existing dedicated commuter lanes, only instead of paying extra to use them, the separate lanes are only for autonomous vehicles. Photograph: Alamy

These days there are so many self-driving cars coming down the pipeline it seems inevitable they’ll soon be stuck in a robot traffic jam – just like the human-piloted cars of today. Well, not if Anthony Barrs and Baiyu Chen get their way.

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.

“Long story short: high-speed rail didn’t pencil out over here,” Barrs said of the perennially back-burnered California rail project. “We’re primarily looking at cities with major nodes that need to be connected, where high-speed would create high value.”

Barrs and Chen said Hyperlane would work well in the San Francisco Bay area, as well as in metropolitan regions like Dallas-Ft Worth and Baltimore-Washington. It wouldn’t work in high-density metro areas with no space to expand roads – New York City, for example – or in medium- and low-density cities where lower traffic volume wouldn’t justify the cost of construction.

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