Autonomous vehicles would have to drive hundreds of millions of miles, and in some cases hundreds of billions of miles, to generate enough data to clearly demonstrate their safety, according to a new RAND report.
As a result, alternative testing methods must be developed to supplement on-the-road testing, which could be in the form of accelerated testing, virtual testing and simulators, mathematical modeling, scenario testing, and pilot studies.
Researchers caution it may not be possible to establish with certainty the reliability of autonomous vehicles prior to making them available for public use. The researchers say in parallel to creating new testing methods, it is imperative to develop regulations and policies that can evolve with the technology.
Although the total number of crashes, injuries, and fatalities from human drivers is high, the rate of these failures is low in comparison with the number of miles that people drive. "The most autonomous miles any developer has logged are about 1.3 million, and that took several years," says RAND study co-author Susan M. Paddock. "This is important data, but it does not come close to the level of driving that is needed to calculate safety rates. Even if autonomous vehicle fleets are driven 10 million miles, one still would not be able to draw statistical conclusions about safety and reliability."
From RAND Corporation
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