CAT Vehicle 2019

Eric Av's Video experience: Autonomous driving has captured academic and public imaginations for years. This project attempts to implicitly teach a car to follow the best optimized route to a destination while avoiding obstacles. The car is taught the optimized route based on a reward/penalty system via reinforcement learning.

This video describes my experience with the CAT Vehicel REU program at the University of Arizona during the 2019 summer. During this program, I realized I enjoy making games for reinforcement learning and what I wanted to research in graduate school. I would recommend this program due to the great mentors who supported me and the friends I made over the summer.

Video about Chris's CAT Vehicle Project: showing that a vehicle with FollowerStopper in a singular lane without merges will not crash and that it will be string stable, effectively dissipating human-caused traffic waves if enough vehicles are deployed in the traffic flow.

Video of Daniels project: checking whether the velocity controller, FollowerStopper, is safe and string stable. 

This silly video provides a brief overview of what our group (Jill Alexander and I) accomplished during our time at the UofA CAT Vehicle REU.

Video by 2019 CAT Vehicle Alum Jill Alexander. 

Jill Alexander (Boise State University)
Alex Pyryt (Univ. of Maryland Baltimore County)

This modeling language can save valuable testing time by quickly creating usable test files for complex physics based models such as the CAT Vehicle.

Jill Alexander (Boise State University) Alex Pyryt (Univ. of Maryland Baltimore County)