# Predictive safety filter enhanced curriculum learning control for efficient vehicle dynamics controller

arXiv: https://arxiv.org/abs/2608.09653 · HTML: https://mlsanity.com/paper/2608.09653/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 10 Aug 2026.

## Abstract (arXiv)

Recent advances in learning-based control have enabled impressive achievements in solving complex control problems in various domains. However, since learning-based control may not be able to realize safety-guaranties, it is of great importance to enhance safety and robustness while maintaining good performances. Take vehicle motion & dynamics control as an example, in order to overcome the pain points of traditional methods such as heavy parameter calibration effort and learning-based control to bring better performance and efficiency in stability & agility over prior work for state-based vehicle control tasks, in this work, our method aims to develop a curriculum learning controller enhanced with physics-based predictive safety filter. The validation is conducted with the Python-CarSim platform, demonstrating better improvements and scalability under various maneuvers.
