31 citations · 36 across the 11 of their papers we have counts for
8 papers · 1 filter
Cooperation-Aware Lane Change Maneuver in Dense Traffic based on Model Predictive Control with Recurrent Neural Network
Sangjae Bae, Dhruv Saxena, Alireza Nakhaei +3
This paper presents a real-time lane change control framework of autonomous driving in dense traffic, which exploits cooperative behaviors of other drivers. This paper focuses on h…
Safe Reinforcement Learning on Autonomous Vehicles
David Isele, Alireza Nakhaei, Kikuo Fujimura
There have been numerous advances in reinforcement learning, but the typically unconstrained exploration of the learning process prevents the adoption of these methods in many safe…
Interaction-Aware Multi-Agent Reinforcement Learning for Mobile Agents with Individual Goals
Anahita Mohseni-Kabir, David Isele, Kikuo Fujimura
In a multi-agent setting, the optimal policy of a single agent is largely dependent on the behavior of other agents. We investigate the problem of multi-agent reinforcement learnin…
Cooperation-Aware Reinforcement Learning for Merging in Dense Traffic
Maxime Bouton, Alireza Nakhaei, Kikuo Fujimura +1
Decision making in dense traffic can be challenging for autonomous vehicles. An autonomous system only relying on predefined road priorities and considering other drivers as moving…
Reinforcement Learning with Probabilistic Guarantees for Autonomous Driving
Maxime Bouton, Jesper Karlsson, Alireza Nakhaei +3
Designing reliable decision strategies for autonomous urban driving is challenging. Reinforcement learning (RL) has been used to automatically derive suitable behavior in uncertain…
Uncertainty-Aware Data Aggregation for Deep Imitation Learning
Yuchen Cui, David Isele, Scott Niekum +1
Estimating statistical uncertainties allows autonomous agents to communicate their confidence during task execution and is important for applications in safety-critical domains suc…