Designing, simulating, and performing the 100-AV field test for the CIRCLES consortium: Methodology and Implementation of the Largest mobile traffic control experiment to date

no code implementations • 23 Apr 2024 • Mostafa Ameli, Sean McQuade, Jonathan W. Lee, Matthew Bunting, Matthew Nice, Han Wang, William Barbour, Ryan Weightman, Chris Denaro, Ryan Delorenzo, Sharon Hornstein, Jon F. Davis, Dan Timsit, Riley Wagner, Rita Xu, Malaika Mahmood, Mikail Mahmood, Maria Laura Delle Monache, Benjamin Seibold, Daniel B. Work, Jonathan Sprinkle, Benedetto Piccoli, Alexandre M. Bayen

This article is a tutorial for developing analytical and simulation-based tools essential for designing and executing a live traffic control experiment like the MVT.

Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test

no code implementations • 26 Feb 2024 • Kathy Jang, Nathan Lichtlé, Eugene Vinitsky, Adit Shah, Matthew Bunting, Matthew Nice, Benedetto Piccoli, Benjamin Seibold, Daniel B. Work, Maria Laura Delle Monache, Jonathan Sprinkle, Jonathan W. Lee, Alexandre M. Bayen

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles.

Autonomous Driving Reinforcement Learning (RL) +1