Search Results for author: Alexandre Bayen

Found 16 papers, 6 papers with code

A rigorous multi-population multi-lane hybrid traffic model and its mean-field limit for dissipation of waves via autonomous vehicles

no code implementations13 May 2022 Nicolas Kardous, Amaury Hayat, Sean T. McQuade, Xiaoqian Gong, Sydney Truong, Tinhinane Mezair, Paige Arnold, Ryan Delorenzo, Alexandre Bayen, Benedetto Piccoli

The choice of these parameters in the lane-change mechanism is critical to modeling traffic accurately, because different parameter values can lead to drastically different traffic behaviors.

Autonomous Vehicles

Multi-Adversarial Safety Analysis for Autonomous Vehicles

no code implementations29 Dec 2021 Gilbert Bahati, Marsalis Gibson, Alexandre Bayen

This work in progress considers reachability-based safety analysis in the domain of autonomous driving in multi-agent systems.

Autonomous Driving

Composing MPC with LQR and Neural Network for Amortized Efficient and Stable Control

no code implementations14 Dec 2021 Fangyu Wu, Guanhua Wang, Siyuan Zhuang, Kehan Wang, Alexander Keimer, Ion Stoica, Alexandre Bayen

The proposed scheme does not require pre-computation and can improve the amortized running time of the composed MPC with a well-trained neural network.

Limitations and Improvements of the Intelligent Driver Model (IDM)

no code implementations2 Apr 2021 Saleh Albeaik, Alexandre Bayen, Maria Teresa Chiri, Xiaoqian Gong, Amaury Hayat, Nicolas Kardous, Alexander Keimer, Sean T. McQuade, Benedetto Piccoli, Yiling You

First it is shown that, for a specific class of initial data, the vehicles' velocities become negative or even diverge to $-\infty$ in finite time, both undesirable properties for a car-following model.

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

6 code implementations2 Mar 2021 Chao Yu, Akash Velu, Eugene Vinitsky, Yu Wang, Alexandre Bayen, Yi Wu

Proximal Policy Optimization (PPO) is a popular on-policy reinforcement learning algorithm but is significantly less utilized than off-policy learning algorithms in multi-agent settings.

Starcraft Starcraft II

Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms

no code implementations1 Jan 2021 Chao Yu, Akash Velu, Eugene Vinitsky, Yu Wang, Alexandre Bayen, Yi Wu

We benchmark commonly used multi-agent deep reinforcement learning (MARL) algorithms on a variety of cooperative multi-agent games.

reinforcement-learning Starcraft

A Graph Convolutional Network with Signal Phasing Information for Arterial Traffic Prediction

1 code implementation25 Dec 2020 Victor Chan, Qijian Gan, Alexandre Bayen

We fill this gap by enhancing a deep learning approach, Diffusion Convolutional Recurrent Neural Network, with spatial information generated from signal timing plans at targeted intersections.

Traffic Prediction

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

1 code implementation30 Oct 2020 Eugene Vinitsky, Nathan Lichtle, Kanaad Parvate, Alexandre Bayen

We apply multi-agent reinforcement algorithms to this problem and demonstrate that significant improvements in bottleneck throughput, from 20\% at a 5\% penetration rate to 33\% at a 40\% penetration rate, can be achieved.

Autonomous Vehicles

Robust Reinforcement Learning using Adversarial Populations

1 code implementation4 Aug 2020 Eugene Vinitsky, Yuqing Du, Kanaad Parvate, Kathy Jang, Pieter Abbeel, Alexandre Bayen

Reinforcement Learning (RL) is an effective tool for controller design but can struggle with issues of robustness, failing catastrophically when the underlying system dynamics are perturbed.

Out-of-Distribution Generalization reinforcement-learning

Simulation to Scaled City: Zero-Shot Policy Transfer for Traffic Control via Autonomous Vehicles

1 code implementation14 Dec 2018 Kathy Jang, Eugene Vinitsky, Behdad Chalaki, Ben Remer, Logan Beaver, Andreas Malikopoulos, Alexandre Bayen

We then directly transfer this policy without any tuning to the University of Delaware Scaled Smart City (UDSSC), a 1:25 scale testbed for connected and automated vehicles.

Autonomous Vehicles reinforcement-learning

Adaptive Averaging in Accelerated Descent Dynamics

no code implementations NeurIPS 2016 Walid Krichene, Alexandre Bayen, Peter L. Bartlett

This dynamics can be described naturally as a coupling of a dual variable accumulating gradients at a given rate $\eta(t)$, and a primal variable obtained as the weighted average of the mirrored dual trajectory, with weights $w(t)$.

Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games

no code implementations NeurIPS 2016 Maximilian Balandat, Walid Krichene, Claire Tomlin, Alexandre Bayen

We study a general adversarial online learning problem, in which we are given a decision set X' in a reflexive Banach space X and a sequence of reward vectors in the dual space of X.

online learning

Minimizing Regret on Reflexive Banach Spaces and Learning Nash Equilibria in Continuous Zero-Sum Games

no code implementations3 Jun 2016 Maximilian Balandat, Walid Krichene, Claire Tomlin, Alexandre Bayen

Under the assumption of uniformly continuous rewards, we obtain explicit anytime regret bounds in a setting where the decision set is the set of probability distributions on a compact metric space $S$ whose Radon-Nikodym derivatives are elements of $L^p(S)$ for some $p > 1$.

online learning

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