mlsanityData to 7 Oct 2026

Neural Network Based Model Predictive Control for an Autonomous Vehicle

arXiv 2107.14573 ↗First posted 30 Jul 2021cs.RO cs.AIcited by 0

On the map: End-to-end autonomous driving → Reinforcement learning for driving

Abstract (arXiv)

We study learning based controllers as a replacement for model predictive controllers (MPC) for the control of autonomous vehicles. We concentrate for the experiments on the simple yet representative bicycle model. We compare training by supervised learning and by reinforcement learning. We also discuss the neural net architectures so as to obtain small nets with the best performances. This work aims at producing controllers that can both be embedded on real-time platforms and amenable to verification by formal methods techniques.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Reinforcement learning for driving, one of 9 directions in End-to-end autonomous driving. Builds on 7 of its 24 references that are in the map. First posted on arXiv 30 Jul 2021.

Builds on

7 of 24 references.

References · 7

  1. 2015Continuous control with deep reinforcement learningcited by 3,279
  2. 2016Understanding Deep Neural Networks with Rectified Linear Unitscited by 253
  3. 2018Verisig: verifying safety properties of hybrid systems with neural network controllerscited by 83
  4. 2018Efficient representation and approximation of model predictive control laws via deep learningcited by 55
  5. 2015How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategiescited by 26
  6. 2019Comparison of Deep Reinforcement Learning and Model Predictive Control for Adaptive Cruise Controlcited by 19
  7. 2019Case Study: Verifying the Safety of an Autonomous Racing Car with a Neural Network Controllercited by 17

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  1. 2025Autonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration
  2. 2024Faster Model Predictive Control via Self-Supervised Initialization Learning
  3. 2021A predictive safety filter for learning-based racing control
  4. 2024PlanNetX: Learning an Efficient Neural Network Planner from MPC for Longitudinal Control
  5. 2022Modelling Controllers for Cyber Physical Systems Using Neural Networks ↗
  6. 2023Model Predictive Inferential Control of Neural State-Space Models for Autonomous Vehicle Motion Planning ↗
  7. 2023Learning the References of Online Model Predictive Control for Urban Self-Driving
  8. 2022MPC-based Imitation Learning for Safe and Human-like Autonomous Driving