Eugene Vinitsky

Orcid: 0000-0003-2372-4944

According to our database1, Eugene Vinitsky authored at least 31 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
From Sim to Real: A Pipeline for Training and Deploying Traffic Smoothing Cruise Controllers.
IEEE Trans. Robotics, 2024

GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS.
CoRR, 2024

Human-compatible driving partners through data-regularized self-play reinforcement learning.
CoRR, 2024

Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test.
CoRR, 2024

Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs.
CoRR, 2024

Human-compatible driving agents through data-regularized self-play reinforcement learning.
Proceedings of the 1st Reinforcement Learning Conference, 2024

2023
Optimizing Mixed Autonomy Traffic Flow with Decentralized Autonomous Vehicles and Multi-Agent Reinforcement Learning.
ACM Trans. Cyber Phys. Syst., April, 2023

Unified Automatic Control of Vehicular Systems With Reinforcement Learning.
IEEE Trans Autom. Sci. Eng., April, 2023

Traffic Smoothing Controllers for Autonomous Vehicles Using Deep Reinforcement Learning and Real-World Trajectory Data.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Stabilizing Unsupervised Environment Design with a Learned Adversary.
Proceedings of the Conference on Lifelong Learning Agents, 2023

2022
From sim-to-real: learning and deploying autonomous vehicle controllers that improve transportation metrics
PhD thesis, 2022

Flow: A Modular Learning Framework for Mixed Autonomy Traffic.
IEEE Trans. Robotics, 2022

On the approximability of Time Disjoint Walks.
J. Comb. Optim., 2022

The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games.
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.
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.
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.
CoRR, 2021

Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers.
CoRR, 2021

The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games.
CoRR, 2021

Fuel Consumption Reduction of Multi-Lane Road Networks using Decentralized Mixed-Autonomy Control.
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.
CoRR, 2020

Robust Reinforcement Learning using Adversarial Populations.
CoRR, 2020

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design.
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.
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.
Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems, 2019

2018
Lagrangian Control through Deep-RL: Applications to Bottleneck Decongestion.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

Benchmarks for reinforcement learning in mixed-autonomy traffic.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017
Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control.
CoRR, 2017

Multi-lane reduction: A stochastic single-lane model for lane changing.
Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Framework for control and deep reinforcement learning in traffic.
Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Emergent Behaviors in Mixed-Autonomy Traffic.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017


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