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Found 5 papers, 4 papers with code
A Comparison Benchmark for Distributed Hybrid MPC Control Methods: Distributed Vehicle Platooning
We propose distributed control of a platoon of autonomous vehicles as a comparison benchmark problem.
Multi-Agent Reinforcement Learning via Distributed MPC as a Function Approximator
Existing work on RL has demonstrated the use of model predictive control (MPC) as a function approximator for the policy and value functions.
Model Predictive Control
Multi-agent Reinforcement Learning
+3
Reinforcement Learning with Model Predictive Control for Highway Ramp Metering
In the backdrop of an increasingly pressing need for effective urban and highway transportation systems, this work explores the synergy between model-based and learning-based strategies to enhance traffic flow management by use of an innovative approach to the problem of ramp metering control that embeds Reinforcement Learning (RL) techniques within the Model Predictive Control (MPC) framework.
Model-based Reinforcement Learning
Model Predictive Control
+2
Proactive Emergency Collision Avoidance for Automated Driving in Highway Scenarios
Uncertainty in the behavior of other traffic participants is a crucial factor in collision avoidance for automated driving; here, stochastic metrics should often be considered to avoid overly conservative decisions.
Learning safety in model-based Reinforcement Learning using MPC and Gaussian Processes
We propose a method to encourage safety in Model Predictive Control (MPC)-based Reinforcement Learning (RL) via Gaussian Process (GP) regression.
