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GCC AI Research

Mission Performance: Automatic and Adaptive Race Pace Progression for Autonomous Racing

arXiv · · Notable

Summary

This paper describes the Mission Performance module, an automatic and adaptive system for fully autonomous racing cars, designed to manage longitudinal, lateral, and combined performances. The module guides motion planners and controllers by adapting their target performance to accelerate laptime progression while ensuring safety. Its effectiveness was demonstrated on the EAV-25 Dallara Superformula at the Yas Marina Circuit during the Abu Dhabi Autonomous Racing League (A2RL) Season 2. Why it matters: This research advances autonomous driving capabilities in high-performance racing, showcasing practical AI applications and technological development in the Middle East.

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Minimalistic Autonomous Stack for High-Speed Time-Trial Racing

arXiv ·

This paper introduces a minimalistic autonomous racing stack designed for high-speed time-trial racing, emphasizing rapid deployment and efficient system integration with minimal on-track testing. Validated on real speedways, the stack achieved a top speed of 206 km/h within just 11 hours of practice, covering 325 km. The system performance analysis includes tracking accuracy, vehicle dynamics, and safety considerations. Why it matters: This research offers insights for teams aiming to quickly develop and deploy autonomous racing stacks with limited track access, potentially accelerating innovation in autonomous vehicle technology within the A2RL and similar racing initiatives.