Fast and Modular Autonomy Software for Autonomous Racing Vehicles
Andrew Saba, Aderotimi Adetunji, Adam Johnson, Aadi Kothari, Matthew, Sivaprakasam, Joshua Spisak, Prem Bharatia, Arjun Chauhan, Brendan Duff Jr.,, Noah Gasparro, Charles King, Ryan Larkin, Brian Mao, Micah Nye, Anjali, Parashar, Joseph Attias, Aurimas Balciunas, Austin Brown

TL;DR
This paper presents a modular, high-speed autonomy software stack for autonomous racing vehicles, tested in the Indy Autonomous Challenge, emphasizing rapid deployment, real-world performance, and lessons learned for future improvements.
Contribution
The paper introduces a fast, modular autonomy software framework specifically designed for high-speed racing scenarios, with detailed analysis and deployment insights from the IAC competition.
Findings
Effective agent detection and motion planning at high speeds
Identified challenges in multi-agent scenarios and real-world deployment
Lessons learned for improving autonomous racing software
Abstract
Autonomous motorsports aim to replicate the human racecar driver with software and sensors. As in traditional motorsports, Autonomous Racing Vehicles (ARVs) are pushed to their handling limits in multi-agent scenarios at extremely high () speeds. This Operational Design Domain (ODD) presents unique challenges across the autonomy stack. The Indy Autonomous Challenge (IAC) is an international competition aiming to advance autonomous vehicle development through ARV competitions. While far from challenging what a human racecar driver can do, the IAC is pushing the state of the art by facilitating full-sized ARV competitions. This paper details the MIT-Pitt-RW Team's approach to autonomous racing in the IAC. In this work, we present our modular and fast approach to agent detection, motion planning and controls to create an autonomy stack. We also provide analysis of the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
