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Laying the groundwork for self-driving vehicle safety

By: Eric Meyhofer, CEO of Uber Advanced Technologies Group

Around the world, regulators, technology developers, and industry standard-setting bodies are already working on a range of approaches to self-driving vehicle safety. However, the complexity of self-driving technology and the variety in development approaches across the industry means that, to date, no single standard or test alone can help the public understand how companies are addressing safety.

At Uber ATG, we feel a responsibility to foster open, public dialogue around our safety approach for the testing and development of self-driving vehicles. We publicly started this conversation last fall when we released our Voluntary Safety Self-Assessment, structured around our five Safety Principles: Proficient, Fail-Safe, Continuously Improving, Resilient, and Trustworthy. These principles are the foundation for Uber ATG’s Self-Driving Vehicle (SDV) Safety Case Framework. Today, we are sharing further details of that framework in conjunction with the annual Automated Vehicles Symposium, one of the largest cross-sectoral gatherings of leaders and innovators working to advance safe self-driving technologies.

We are putting forward a safety case framework for self-driving vehicles during development and into deployment with the goal of providing additional transparency around our safety approach. We are also open sourcing this with humble hope of aiding safety case development efforts within the industry, and potentially informing various voluntary standard-setting efforts already underway.

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Our Safety Case Framework

What is a safety case?

What is Uber ATG’s SDV Safety Case Framework?

Our safety case starts with a primary claim: our self-driving vehicles are acceptably safe to operate on public roads. From this claim we work top-down to define the argument structure that would be necessary to support the claim. This framework is intended to set out the full spectrum of conditions — from Mission Specialist hiring and training, to cybersecurity, to transparent reporting, to incorporation of legal requirements — that we believe should be considered as self-driving systems are built, tested, and brought to market.

The engineering processes for the development and testing of self-driving vehicles are still evolving. We have combined guidance from governments, established best practices from safety-critical industries, and voluntary industry standards with academic research and key learnings from our own development.

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A dynamic framework utilizing Goal Structuring Notation

Operating a fleet of shared, self-driving vehicles gives rise to a number of important considerations that are not focused on safety, including, for example, data-privacy sensitivities. We will appropriately address these considerations, but they are outside the scope of this SDV Safety Case Framework.

Where to from here?

Satisfying the conditions of this SDV Safety Case Framework is no small task, and we do not claim to have met all of them ourselves for fully driverless operations. We also recognize new or refined best practices may emerge over time, and we will consider these for incorporation into our SDV Safety Case Framework as they surface.

In order to realize the potential of self-driving technology to its fullest, we must come together and collaborate on safety. We hope you join us in the conversation.

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