# er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds

arXiv: https://arxiv.org/abs/2310.18112 · HTML: https://mlsanity.com/paper/2310.18112/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 54 references that are in the map.
- First posted on arXiv 27 Oct 2023.

## Builds on (most cited first, 18 of 18)

- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning](https://mlsanity.com/paper/1805.04687/) (2018)
- [Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing](https://mlsanity.com/paper/2202.07008/) (2022)
- [Optimization-Based Autonomous Racing of 1:43 Scale RC Cars](https://mlsanity.com/paper/1711.07300/) (2017)
- [AMZ Driverless: The Full Autonomous Racing System](https://mlsanity.com/paper/1905.05150/) (2019)
- [HPIPM: a high-performance quadratic programming framework for model predictive control](https://mlsanity.com/paper/2003.02547/) (2020)
- [Multilayer Graph-Based Trajectory Planning for Race Vehicles in Dynamic Scenarios](https://mlsanity.com/paper/2005.08664/) (2020)
- [TUM autonomous motorsport: An autonomous racing software for the Indy Autonomous Challenge](https://mlsanity.com/paper/2205.15979/) (2022)
- [Optimization-Based Hierarchical Motion Planning for Autonomous Racing](https://mlsanity.com/paper/2003.04882/) (2020)
- [Accurate, Low-Latency Visual Perception for Autonomous Racing:Challenges, Mechanisms, and Practical Solutions](https://mlsanity.com/paper/2007.13971/) (2020)
- [Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds](https://mlsanity.com/paper/2207.11136/) (2022)
- [Sampling-based Algorithms for Optimal Motion Planning Using Closed-loop Prediction](https://mlsanity.com/paper/1601.06326/) (2016)
- [The Autonomous Racing Software Stack of the KIT19d](https://mlsanity.com/paper/2010.02828/) (2020)
- [FSOCO: The Formula Student Objects in Context Dataset](https://mlsanity.com/paper/2012.07139/) (2020)
- [Autonomous Electric Race Car Design](https://mlsanity.com/paper/1711.00548/) (2017)
- [From perception to control: an autonomous driving system for a formula student driverless car](https://mlsanity.com/paper/1909.00119/) (2019)
- [Autonomous Formula Racecar: Overall System Design and Experimental Validation](https://mlsanity.com/paper/2009.00385/) (2020)
- [A Resilient Navigation and Path Planning System for High-speed Autonomous Race Car](https://mlsanity.com/paper/2207.12232/) (2022)

## Built on by (most cited first, 3 of 3)

- [A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential](https://mlsanity.com/paper/2312.14808/) (2023)
- [Trajectory Planning Using Reinforcement Learning for Interactive Overtaking Maneuvers in Autonomous Racing Scenarios](https://mlsanity.com/paper/2404.10658/) (2024)
- [AARK: An Open Toolkit for Autonomous Racing Research](https://mlsanity.com/paper/2410.00358/) (2024)

## Abstract (arXiv)

The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at unprecedented speed and in head-to-head scenario, using independently developed software on open-wheel racecars. This paper presents the complete software architecture used by team TII EuroRacing (TII-ER), covering all the modules needed to avoid static obstacles, perform active overtakes and reach speeds above 75 m/s (270 km/h). In addition to the most common modules related to perception, planning, and control, we discuss the approaches used for vehicle dynamics modelling, simulation, telemetry, and safety. Overall results and the performance of each module are described, as well as the lessons learned during the first two events of the competition on oval tracks, where the team placed respectively second and third.