Machine Learning For The Safety Validation Of Autonomous Vehicles

Anthony Corso, 5th year Ph.D. student in the Aeronautics and Astronautics Department at Stanford University joins 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.

Download slides here:
https://984e930c-03a5-4c3f-b41d-38daef8335bc.usrfiles.com/ugd/984e93_ff91776fd0a74ff7af3c7c882142958c.pptx

Видео Machine Learning For The Safety Validation Of Autonomous Vehicles канала Apex AI