Nathan Lichtle

According to our database, Nathan Lichtle authored at least 10 papers between 2019 and 2024.

Collaborative distances:

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

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

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

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

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

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

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

2019

Inter-Level Cooperation in Hierarchical Reinforcement Learning.

Abdul Rahman Kreidieh, Samyak Parajuli, Nathan Lichtle, Yiling You, Rayyan Nasr, Alexandre M. Bayen

CoRR, 2019