Title: Researching Autonomous Driving Through AWS Deepracer
Student: Jacob McCalip
Advisor: Kecheng Yang
Date and Time: Fri Dec 2, 9:00 AM - 9:30 AM
Location: https://txstate.zoom.us/my/yangk
Abstract: Autonomous driving has the potential to reduce energy consumption, reduce travel time, and reduce driving casualties. The most advanced self-driving cars on the road today are of level 2 autonomy. We are working directly on level 5 automation through AWS's DeepRacer: a 1/18th scale car with an open-source ecosystem of both virtual and physical tools built on reinforcement learning. This presentation will deliver an overview of how we simulate models, use data analysis on these models, bridge the Sim2Real gap, the role of ROS, and how the behavior of the model is programmed
Deadline: Dec. 28, 2022, midnight