Intel, Mobileye: Formula proves safety of autonomous vehicles
The solution, which was presented by Mobileye CEO and Intel senior vice president professor Amnon Shashua at the World Knowledge Forum in Seoul, South Korea, is offered in the form of a mathematical formula. According to Shashua, the formula is designed to ensure that a self-driving vehicle operates in a responsible manner and does not cause accidents for which it can be blamed.
Shashua, and his colleague Shai Shalev-Shwartz, developed the formula in hopes that it can bring certainty to questions about liability and blame in the event of an accident involving a driverless vehicle. They have proposed a Responsibility Sensitive Safety model, which is designed to ensure that self-driving cars will operate only within a framework defined as “safe” according to clear definitions of fault that are agreed upon by both industry and regulators.
Current vehicle accident rules and laws assume a human driver in control of a car. Industry and policymakers, say Shashua, now need to “collaboratively construct standards that definitively assign accident fault” for when accidents between human-driven and self-driving vehicles inevitably occur.
“The ability to assign fault is the key,” he says. “Just like the best human drivers in the world, self-driving cars cannot avoid accidents due to actions beyond their control. But the most responsible, aware and cautious driver is very unlikely to cause an accident of his or her own fault, particularly if they had 360-degree vision and lightning-fast reaction times like autonomous vehicles will.”
The solution is described in both an academic paper (“On a Formal Model of Safe and Scalable Self-driving Cars“) and a summary paper (see “A Plan to Develop Safe Autonomous Vehicles. And Prove It.“) In addition to the mathematical model for safety assurance, the paper also describes the design of a system that not only adheres to the authors’ safety assurance requirements, but is economically scalable to millions of cars – the latter being a “fundamental pillar” for the proposed framework, the authors say.
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