in , ,

(video) Machine Learning For The Safety Validation Of Autonomous Vehicles

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.

Get the slides here:

What do you think?

486 points
Upvote Downvote

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Smart City LiDAR Applications Providing Numerous Possibilities

Smart City LiDAR Applications Providing Numerous Possibilities

(video) Oxbotica | Off-Road | Mining