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
Dec 12, 2018 12:00 AM
Event
Invited Talk at the MIT-IBM Watson AI Lab
Location
MIT-IBM Watson AI Lab, Cambridge, MA
Michal Gregor
Michal Gregor
Researcher – Expert

My research interests include distributed robotics, mobile computing and programmable matter.

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