Abstract

Driverless racecar competitions are often perceived as recreational. However, their academic, industry, and research benefits are potentially tremendous, as several significant lessons can be learned from these competitions to advance autonomous mobility. This study was motivated (and its conduction facilitated) by the active involvement of the authors in several autonomous racing initiatives in the United States. The study first synthesized and analyzed information from existing literature related to the key modules of autonomous vehicle (AV) operations as part of AV racing competitions and identified some lessons that could be learned in the context of each module – perception and sensing, data fusion, path planning and decision making, vehicle dynamics and control, and hardware and software safety. After synthesizing such information, the study establishes that high-speed AV tests and competitions where multiple teams push the limits of sensing, decision-making, and control serve as testbeds for creating, developing, and refining AV technologies. This is because the AV racing events have used controlled environment platforms to demonstrate what autonomous systems can achieve under extreme conditions, and allowing testing of edge-case scenarios and performance extremes that would be too risky or impractical on public roads. Further, by demonstrating what autonomous systems can achieve under extreme conditions and edge cases, the AV racing events have shown that they foster innovation in a safe and controlled environment. The identified lessons from the racing competitions can serve as a knowledge base to facilitate safe and efficient AV operations on high-speed road transportation corridors such as freeways. The discussion includes caveats regarding the dichotomies between AV operations guideway (racetrack vs. roadway) and AV vehicle designs (race car designs vs. standard automobile and truck design), and how these differences temper the translation of lessons learned from AV racing to real-world (roadway) AV operations. In sum, the study outcomes support the notion that high-speed AV events can continue to serve as proving grounds for testing edge cases of autonomous operations to facilitate safety and movement efficiency in autonomous driving in the real world. In the prospective era of AV operations on public roads, the lessons learned can help enhance AV design and sensing/communication capabilities for roadway operations specifically. The lessons can also promote transportation mobility, safety, reliability, and economic productivity associated with autonomous mobility at high-speed road corridors, particularly freeways.

Keywords

Autonomous vehicles, Self-driving competition, High speed, Racing, Edge cases

DOI

10.5703/1288284318631

Date of this Version

4-2026

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