Machine Learning For The Safety Validation Of Autonomous Vehicles
Time & Location
About the Event
Join us for this month’s Autoware Meetup. On July 30th at 6pm Pacific Time, Anthony Corso, 5th year Ph.D. student in the Aeronautics and Astronautics Department at Stanford University will join Sanjay Krishnan, VP of Product at Apex.AI to discuss automotive validation.
Autonomous vehicles (AVs) require rigorous testing before deployment. Due to the complexity of these systems, formal verification may be impossible and real-world testing may be dangerous and expensive during development. This is where AST fits in. Anthony Corso presents his work on Adaptive Stress Testing (AST), a technique for automatically finding the most likely failures of an autonomous system in simulation. AST treats the AV as a black box and uses reinforcement learning to manipulate the driving environment toward challenging scenarios. He will demonstrate the discovery of failures for aircraft collision avoidance systems, simple autonomous vehicles and a vision-based controller that uses a neural network. You don’t want to miss this discussion!