Acoustic-driven Vehicle Adaptation to Improve Driver’s Comfort

Acoustic-driven Vehicle Adaptation to Improve Driver’s Comfort

Abstract

The talk presented the work done as part of the VEHICAL project at UC Berkeley concerning driver modeling, decreasing acoustic annoyance, using real data from an instrumented car and using simulation and deep reinforcement learning, etc.; collaborators: Ruzena Bajcsy, Erickson R. Nascimento, Isabella Huang, Ismael Villegas.

Date
Event
Invited Talk at the Toyota Research Institute
Location
Toyota Research Institute, Cambridge, MA
Avatar
Michal Gregor
Researcher in Artificial Intelligence

My research interests include especially deep learning, deep reinforcement learning and other machine learning methods.