On average, self driving car technology is faced with a lot of challenges such as more than 5 million crashes take place annually and 22 percent of them are weather-related, the Federal Highway Administration (FHWA) reports.
Now with more autonomous vehicles being deployed on highways around the country, researchers are working on ways to fine-tune and enhance the technology that controls these vehicles. Capabilities the cars are being taught include identifying cyclists, maintaining speed limits and learning traffic patterns. Tackling the challenge that bad weather poses is just one step of the process.
With mass-market availability of electric cars around the corner. Self driving car technology such as in the Waymo’s cars will be faced with teaching these cars how to operate reliably in scenarios that don’t happen often in real life and are therefore difficult to gather data on. Anything from strange weather occurrences and other vehicles’ unpredictable driving patterns to more common but irregular situations, like emergency vehicles and snowfall, can pose a data problem. Without consistent opportunities to encounter these situations during average training sessions, self driving car technology often must undergo specialized training for those scenarios, which takes time.
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