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What is RL-Enhanced Event-Triggered MPC for AVs about?

This paper presents a reinforcement learning-based event-triggered model predictive control (MPC) approach for autonomous vehicle path following, aiming to reduce computational demands compared to traditional time-triggered MPC. The proposed method leverages a model-free reinforcement learning agent to learn an optimal event-trigger policy by interacting with the MPC closed-loop system, which is assumed to be unknown to the agent. The effectiveness of the approach is demonstrated through numerical simulatio

Author

Mohsen E

Language

EN