Google’s driverless car is no match for the Canadian winter.

Google hasn’t said exactly what’s plaguing its car’s ability to cope with flurries, but its self-driving car project director Chris Urmson recently admitted snow is a struggle.

“It turns out in Mountain View, it doesn’t snow,” he reportedly said of the car’s California testing location at the annual Automotive News World Congress conference in Detroit last week. As a solution, he suggested Google deploy the vehicle to other places for testing and “push the technological boundaries into these more challenging situations.”

Aaron Brindle, a Google spokesperson, confirmed in an email to the Star that snow is a challenge for the car.

“When it’s snowing or really foggy, for example, a human driver has limited visibility — so too do our vehicles,” he wrote. “Though we’re working on improving this, the good news is that, in the meantime, our cars recognize when they have limited visibility and will make the safe decision not to drive.”

When self-navigating automobiles encounter snow and ice, driving becomes tricky, say experts who believe obstacle detection technology has a long way to go before it can cope with the winter elements.

“A lot of these vehicles use computer vision systems to look at the roadway ahead to understand where the lane boundaries are. When the road is covered in snow, they can’t see the lane boundaries,” said Steven Shladover, an advanced transportation researcher from the University of California, Berkeley.

Part of the problem, Massachusetts Institute of Technology mechanical engineering professor John Leonard adds, is that the light-detection sensors Google and other self-driving vehicles use can be tricked by snow into perceiving that there is a “phantom obstacle” in the way.

Experts believe that computer vision systems cannot sense black ice even when equipped with built-in digital maps, GPS technology and laser scanners for positioning and obstacle detection. Using those tools, self-driving cars build maps that are accurate up to a few centimeters. But when snow builds into banks and covers the roads, shifting every few moments, it means everything needs to be remapped.

That mapping falls partially on sensors, which Leonard says sometimes “don’t give good measurements off of snow” because “instead of measuring the position of a snowbank, sensor measurements might get reflected away or be absorbed by the snow.”

Black ice might not even register with current sensors; human drivers often can’t detect the ice themselves.

When a self-navigating vehicle can’t decipher the snow and ice and feels challenged, Shladover says it will either stop or return control over to a human driver. The same thing happens when a self-driving car encounters another car backing out of a driveway, a construction zone, an animal scampering across the street or debris left on a roadway.

So how long will it take the brains behind automated cars to develop a way to deal with unexpected elements?

Decades, according to Leonard.

“It’s important to not underestimate how hard the remaining problems are,” Leonard says. “We shouldn’t get our hopes up too much that it is all going to happen overnight.”

Shladover agrees. He says companies are “pretty far off” from an automated car that can handle snow and ice because there are an infinite number of circumstances a vehicle can contend with as it speeds down the street.

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“When you consider millions of vehicles on the road driving multiple hours per day, no designer sitting at a computer is going to be able to think of every situation that every vehicle is going to encounter,” he says. “It is extremely complicated.”

Currently, he says, self-driving cars are really only able to navigate on highways or freeways, where traffic is moving in one direction. Cars that can contend with local streets and intersections will “take a while” to develop, and a vehicle that takes riders to while they rest or do something else is “decades away,” he says.

However, Shladover says, systems that do portions of the driving are “coming along” and those that park cars at low speeds in suitably equipped garages are “probably coming quite soon.”

As for Google, Brindle says “while you may not see the vehicle on the streets of Toronto this winter, our hope is that we make good progress over the course of this year and potentially run small pilot tests in California in the near future.”

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