Nathan Lichtlé

17 papers A* 2Journal 10Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Supervised and Unsupervised Neural Network Solver for First Order Hyperbolic Nonlinear PDEs.
CoRR
Zakaria Baba, Alexandre M. Bayen, Alexi Canesse, Maria Laura Delle Monache, Martin Drieux, Zhe Fu, Nathan Lichtlé, Zihe Liu, Hossein Nick Zinat Matin, Benedetto Piccoli
2025 J jnl
(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs.
CoRR
Nathan Lichtlé, Alexi Canesse, Zhe Fu, Hossein Nick Zinat Matin, Maria Laura Delle Monache, Alexandre M. Bayen
2025 — conf
A Tutorial on Neural Network-Based Solvers for Hyperbolic Conservation Laws: Supervised vs. Unsupervised Learning, and Applications to Traffic Modeling.
NeuS
Alexi Canesse, Zhe Fu, Nathan Lichtlé, Hossein Nick Zinat Matin, Zihe Liu, Maria Laura Delle Monache, Alexandre M. Bayen
2025 J jnl
A novel approach to feedback control with deep reinforcement learning.
Syst. Control. Lett.
Kala Agbo bidi, Jean-Michel Coron, Amaury Hayat, Nathan Lichtlé
2025 — conf
Verifiable Language Model Explanations for Deep RL-Based Flow Smoothing.
ITSC
Ashish Pandian, Ashwin Dara, Adrien Bindel, Nathan Lichtlé, Prasen Jit Singh, Fatimah Alzamzami, Esam Othman, Sulaiman Almatrudi, Jonathan W. Lee, Alexandre M. Bayen
2024 J jnl
From Sim to Real: A Pipeline for Training and Deploying Traffic Smoothing Cruise Controllers.
IEEE Trans. Robotics
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
2024 J jnl
Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test.
CoRR
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
2024 — —
Stabilization and control of dynamical systems: from classical methods to reinforcement learning. (Stabilisation et contrôle des systèmes dynamiques : des méthodes classiques à l'apprentissage par renforcement).
Nathan Lichtlé
2024 J jnl
Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs.
CoRR
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
2024 J jnl
Traffic Smoothing Controllers for Autonomous Vehicles Using Deep Reinforcement Learning and Real-World Trajectory Data.
CoRR
Nathan Lichtlé, Kathy Jang, Adit Shah, Eugene Vinitsky, Jonathan W. Lee, Alexandre M. Bayen
2023 J jnl
Optimizing Mixed Autonomy Traffic Flow with Decentralized Autonomous Vehicles and Multi-Agent Reinforcement Learning.
ACM Trans. Cyber Phys. Syst.
Eugene Vinitsky, Nathan Lichtlé, Kanaad Parvate, Alexandre M. Bayen
2023 — conf
Traffic Smoothing Controllers for Autonomous Vehicles Using Deep Reinforcement Learning and Real-World Trajectory Data.
ITSC
Nathan Lichtlé, Kathy Jang, Adit Shah, Eugene Vinitsky, Jonathan W. Lee, Alexandre M. Bayen
2022 A* conf
Deploying Traffic Smoothing Cruise Controllers Learned from Trajectory Data.
ICRA
Nathan Lichtlé, Eugene Vinitsky, Matthew Nice, Benjamin Seibold, Dan Work, Alexandre M. Bayen
2022 A* conf
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world.
NeurIPS
Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, Jakob N. Foerster
2022 J jnl
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world.
CoRR
Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, Jakob N. Foerster
2021 — conf
Fuel Consumption Reduction of Multi-Lane Road Networks using Decentralized Mixed-Autonomy Control.
ITSC
Nathan Lichtlé, Eugene Vinitsky, George Gunter, Akash Velu, Alexandre M. Bayen
2021 J jnl
Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers.
CoRR
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