Autonomous vehicles have difficulty navigating bad weather. Heavy rain, snow, and fog can do a lot to scramble a robotaxis perception systems, which largely rely on cameras, radar, and lidar to “see” the world around it. Wet roads can create reflections that confuse cameras. Fog can screw up sensor data. And ice can form on the lidar, inhibiting the sensor’s ability to send out laser points to gauge distance from other objects on the road.
From an article in The Verge by Andrew J. Hawkins
Waymo, the Alphabet company that aims to deploy fleets of robotaxis all over the country, has been quietly investing in weather research since its early days as a “moonshot” project out of Google’s X division. And while its autonomous vehicles still struggled to navigate certain inclement conditions, the company has gotten a lot better at detecting and predicting the weather in the cities in which it operates — even creating a first-of-its-kind fog map for San Francisco.
The map is a product of millions of data points collected by Waymo’s fleet of autonomous vehicles as they traverse San Francisco’s fog-drenched streets. Combined with special weather-detecting vehicles equipped with visibility sensors, Waymo is able to create a new meteorological “metric” that it then feeds to its autonomous “Waymo Driver” to aid its decision-making.
“We’re describing our vehicles as mobile weather stations,” said Daniel Rothenberg, a trained meteorologist and a member of the company’s weather team, in an interview with The Verge. “And that’s exactly how they’re functioning.”
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