Jamie Smith

Jamie Smith has more than twenty-five years of embedded design and test & measurement experience in safety-critical industries. I am currently the VP of Products for Safety-Critical Systems at Imandra. We provide development and testing tools for safety-critical systems and neural networks. I spent most of my career at National Instruments (now NI), where I led our automotive research and development team and our industrial internet of things groups. Jamie earned a Master of Science in Applied Physics from Stanford and a Bachelor's in Physics from UC Santa Barbara. He is a frequent speaker at Autonomous Vehicle conferences.

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Presentation

Create Critical Scenario Libraries Using Automated Reasoning to Prove Coverage

The real world represents an infinite number of potential testing scenarios. Industry experts can use their experience and road data to identify and define a wide range of scenarios for testing, but there are still countless unknown-unsafe scenarios. Symbolic Artificial Intelligence is the state-of-the-art approach for generating and filtering a complete library of known and unknown scenarios for scenario-based testing. The Imandra automated reasoning engine models and reasons about behaviors of actors and the environment for any ODD to create a complete library of critical OpenScenario 1.x or 2.x files for simulation-based testing.