# Robust Modeling and Controls for Racing on the Edge

arXiv: https://arxiv.org/abs/2205.10841 · HTML: https://mlsanity.com/paper/2205.10841/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2022.

## Built on by (most cited first, 2 of 2)

- [Fast and Modular Autonomy Software for Autonomous Racing Vehicles](https://mlsanity.com/paper/2408.15425/) (2024)
- [Model Parameter Identification via a Hyperparameter Optimization Scheme for Autonomous Racing Systems](https://mlsanity.com/paper/2301.01470/) (2023)

## Abstract (arXiv)

Race cars are routinely driven to the edge of their handling limits in dynamic scenarios well above 200mph. Similar challenges are posed in autonomous racing, where a software stack, instead of a human driver, interacts within a multi-agent environment. For an Autonomous Racing Vehicle (ARV), operating at the edge of handling limits and acting safely in these dynamic environments is still an unsolved problem. In this paper, we present a baseline controls stack for an ARV capable of operating safely up to 140mph. Additionally, limitations in the current approach are discussed to highlight the need for improved dynamics modeling and learning.