From Zero to High-Speed Racing: An Autonomous Racing Stack

TL;DR

This paper presents the development and evaluation of the Autonomous Race Stack (ARS), a modular system enabling high-speed autonomous racing up to 260 km/h, with detailed performance analysis and a new multi-sensor dataset.

Contribution

Introduction of a modular, evolving autonomous racing system (ARS) with comprehensive performance evaluation and publicly released high-speed datasets.

Findings

Achieved speeds up to 260 km/h in real-world racing scenarios

Compared control, perception, and estimation across different track types

Provided insights into challenges of high-speed autonomous racing

Abstract

High-speed, head-to-head autonomous racing presents substantial technical and logistical challenges, including precise localization, rapid perception, dynamic planning, and real-time control-compounded by limited track access and costly hardware. This paper introduces the Autonomous Race Stack (ARS), developed by the IU Luddy Autonomous Racing team for the Indy Autonomous Challenge (IAC). We present three iterations of our ARS, each validated on different tracks and achieving speeds up to 260 km/h. Our contributions include: (i) the modular architecture and evolution of the ARS across ARS1, ARS2, and ARS3; (ii) a detailed performance evaluation that contrasts control, perception, and estimation across oval and road-course environments; and (iii) the release of a high-speed, multi-sensor dataset collected from oval and road-course tracks. Our findings highlight the unique challenges and insights from real-world high-speed full-scale autonomous racing.