Eugene Vinitsky

According to our database, Eugene Vinitsky authored at least 32 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

From Sim to Real: A Pipeline for Training and Deploying Traffic Smoothing Cruise Controllers.

Nathan Lichtlé, Eugene Vinitsky, Matthew Nice, Rahul Bhadani, Matthew R. Bunting, Fangyu Wu, Benedetto Piccoli, Benjamin Seibold, Daniel B. Work, Jonathan W. Lee, Jonathan Sprinkle, Alexandre M. Bayen

IEEE Trans. Robotics, 2024

Few-shot In-Context Preference Learning Using Large Language Models.

Chao Yu, Hong Lu, Jiaxuan Gao, Qixin Tan, Xinting Yang, Yu Wang, Yi Wu, Eugene Vinitsky

CoRR, 2024

GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS.

Saman Kazemkhani, Aarav Pandya, Daphne Cornelisse, Brennan Shacklett, Eugene Vinitsky

CoRR, 2024

Human-compatible driving partners through data-regularized self-play reinforcement learning.

Daphne Cornelisse, Eugene Vinitsky

CoRR, 2024

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

Kathy Jang, Nathan Lichtlé, Eugene Vinitsky, Adit Shah, Matthew R. Bunting, Matthew Nice, Benedetto Piccoli, Benjamin Seibold, Daniel B. Work, Maria Laura Delle Monache, Jonathan Sprinkle, Jonathan W. Lee, Alexandre M. Bayen

CoRR, 2024

Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs.

Jonathan W. Lee, Han Wang, Kathy Jang, Amaury Hayat, Matthew R. Bunting, Arwa Alanqary, William Barbour, Zhe Fu, Xiaoqian Gong, George Gunter, Sharon Hornstein, Abdul Rahman Kreidieh, Nathan Lichtlé, Matthew Walter Nice, William A. Richardson, Adit Shah, Eugene Vinitsky, Fangyu Wu, Shengquan Xiang, Sulaiman Almatrudi, Fahd Althukair, Rahul Bhadani, Joy Carpio, Raphaël Chekroun, Eric Cheng, Maria Teresa Chiri, Fang-Chieh Chou, Ryan Delorenzo, Marsalis T. Gibson, Derek Gloudemans, Anish Gollakota, Junyi Ji, Alexander Keimer, Nour Khoudari, Malaika Mahmood, Mikail Mahmood, Hossein Nick Zinat Matin, Sean T. McQuade, Rabie Ramadan, Daniel Urieli, Xia Wang, Yanbing Wang, Rita Xu, Mengsha Yao, Yiling You, Gergely Zachár, Yibo Zhao, Mostafa Ameli, Mirza Najamuddin Baig, Sarah Bhaskaran, Kenneth Butts, Manasi Gowda, Caroline Janssen, John Lee, Liam Pedersen, Riley Wagner, Zimo Zhang, Chang Zhou, Daniel B. Work, Benjamin Seibold, Jonathan Sprinkle, Benedetto Piccoli, Maria Laura Delle Monache, Alexandre M. Bayen

CoRR, 2024

Human-compatible driving agents through data-regularized self-play reinforcement learning.

Daphne Cornelisse, Eugene Vinitsky

RLJ, 2024

2023

Optimizing Mixed Autonomy Traffic Flow with Decentralized Autonomous Vehicles and Multi-Agent Reinforcement Learning.

Eugene Vinitsky, Nathan Lichtlé, Kanaad Parvate, Alexandre M. Bayen

ACM Trans. Cyber Phys. Syst., April, 2023

Unified Automatic Control of Vehicular Systems With Reinforcement Learning.

Zhongxia Yan, Abdul Rahman Kreidieh, Eugene Vinitsky, Alexandre M. Bayen, Cathy Wu

IEEE Trans Autom. Sci. Eng., April, 2023

Traffic Smoothing Controllers for Autonomous Vehicles Using Deep Reinforcement Learning and Real-World Trajectory Data.

Nathan Lichtlé, Kathy Jang, Adit Shah, Eugene Vinitsky, Jonathan W. Lee, Alexandre M. Bayen

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Stabilizing Unsupervised Environment Design with a Learned Adversary.

Ishita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis, Eugene Vinitsky, Tim Rocktäschel

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

From sim-to-real: learning and deploying autonomous vehicle controllers that improve transportation metrics

Eugene Vinitsky

PhD thesis, 2022

Flow: A Modular Learning Framework for Mixed Autonomy Traffic.

Cathy Wu, Abdul Rahman Kreidieh, Kanaad Parvate, Eugene Vinitsky, Alexandre M. Bayen

IEEE Trans. Robotics, 2022

On the approximability of Time Disjoint Walks.

Alexandre M. Bayen, Jesse Goodman, Eugene Vinitsky

J. Comb. Optim., 2022

The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games.

Chao Yu, Akash Velu, Eugene Vinitsky, Jiaxuan Gao, Yu Wang, Alexandre M. Bayen, Yi Wu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world.

Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, Jakob Foerster

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deploying Traffic Smoothing Cruise Controllers Learned from Trajectory Data.

Nathan Lichtlé, Eugene Vinitsky, Matthew Nice, Benjamin Seibold, Dan Work, Alexandre M. Bayen

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings.

Eugene Vinitsky, Raphael Köster, John P. Agapiou, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, Joel Z. Leibo

CoRR, 2021

Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers.

Jonathan W. Lee, George Gunter, Rabie Ramadan, Sulaiman Almatrudi, Paige Arnold, John Aquino, William Barbour, Rahul Bhadani, Joy Carpio, Fang-Chieh Chou, Marsalis T. Gibson, Xiaoqian Gong, Amaury Hayat, Nour Khoudari, Abdul Rahman Kreidieh, Maya Kumar, Nathan Lichtlé, Sean T. McQuade, Brian Q. Nguyen, Megan Ross, Sydney Truong, Eugene Vinitsky, Yibo Zhao, Jonathan Sprinkle, Benedetto Piccoli, Alexandre M. Bayen, Daniel B. Work, Benjamin Seibold

CoRR, 2021

The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games.

Chao Yu, Akash Velu, Eugene Vinitsky, Yu Wang, Alexandre M. Bayen, Yi Wu

CoRR, 2021

Fuel Consumption Reduction of Multi-Lane Road Networks using Decentralized Mixed-Autonomy Control.

Nathan Lichtlé, Eugene Vinitsky, George Gunter, Akash Velu, Alexandre M. Bayen

Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

2020

Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RL.

Eugene Vinitsky, Nathan Lichtle, Kanaad Parvate, Alexandre M. Bayen

CoRR, 2020

Robust Reinforcement Learning using Adversarial Populations.

Eugene Vinitsky, Yuqing Du, Kanaad Parvate, Kathy Jang, Pieter Abbeel, Alexandre M. Bayen

CoRR, 2020

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design.

Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre M. Bayen, Stuart Russell, Andrew Critch, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Zero-Shot Autonomous Vehicle Policy Transfer: From Simulation to Real-World via Adversarial Learning.

Behdad Chalaki, Logan E. Beaver, Ben Remer, Kathy Jang, Eugene Vinitsky, Alexandre M. Bayen, Andreas A. Malikopoulos

Proceedings of the 16th IEEE International Conference on Control & Automation, 2020

2019

Simulation to scaled city: zero-shot policy transfer for traffic control via autonomous vehicles.

Kathy Jang, Eugene Vinitsky, Behdad Chalaki, Ben Remer, Logan Beaver, Andreas A. Malikopoulos, Alexandre M. Bayen

Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems, 2019

2018

Lagrangian Control through Deep-RL: Applications to Bottleneck Decongestion.

Eugene Vinitsky, Kanaad Parvate, Aboudy Kreidieh, Cathy Wu, Alexandre M. Bayen

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

Benchmarks for reinforcement learning in mixed-autonomy traffic.

Eugene Vinitsky, Aboudy Kreidieh, Luc Le Flem, Nishant Kheterpal, Kathy Jang, Cathy Wu, Fangyu Wu, Richard Liaw, Eric Liang, Alexandre M. Bayen

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control.

Cathy Wu, Aboudy Kreidieh, Kanaad Parvate, Eugene Vinitsky, Alexandre M. Bayen

CoRR, 2017

Multi-lane reduction: A stochastic single-lane model for lane changing.

Cathy Wu, Eugene Vinitsky, Aboudy Kreidieh, Alexandre M. Bayen

Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Framework for control and deep reinforcement learning in traffic.

Cathy Wu, Kanaad Parvate, Nishant Kheterpal, Leah Dickstein, Ankur Mehta, Eugene Vinitsky, Alexandre M. Bayen

Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Emergent Behaviors in Mixed-Autonomy Traffic.

Cathy Wu, Aboudy Kreidieh, Eugene Vinitsky, Alexandre M. Bayen

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017