Models and Predictive Control for Nonplanar Vehicle Navigation
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Abstract (arXiv)
We present a simplified model of a vehicle driving on a nonplanar road. A parametric surface is used to describe the nonplanar road which can describe any combination of curvature, bank and slope. We show that the proposed modeling approach generalizes planar vehicle models that reference a centerline, such as the Frenet model. We use the proposed approach for vehicle path planning and following using model predictive control. We also model and control vehicle contact with the road surface. We demonstrate that the proposed controller improves speed and lane following on complex roads compared to planar vehicle controllers, and mitigates loss of control on complex road surfaces including off-camber turns.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Apr 2021.
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Citing papers per year: 2022: 2; 2023: 2.
4 papers.
- 2022Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigationcited by 29
- 2022A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurationscited by 4
- 2023Predictive Control for Autonomous Driving with Uncertain, Multi-modal Predictionscited by 4
- 2023GAN-MPC: Training Model Predictive Controllers with Parameterized Cost Functions using Demonstrations from Non-identical Expertscited by 1
- 2023Predictive Control for Autonomous Driving with Uncertain, Multi-modal Predictions31 Oct 2023
- 2023GAN-MPC: Training Model Predictive Controllers with Parameterized Cost Functions using Demonstrations from Non-identical Experts30 May 2023
- 2022A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations29 Nov 2022
- 2022Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation22 Sep 2022