Minimalistic Autonomous Stack for High-Speed Time-Trial Racing

2025-09-23

AI Summary

Dedicated high-speed racetracks for full-scale autonomous racing validation are scarce, and real-vehicle testing is prohibitively expensive. Method: This paper proposes a minimalist autonomous driving architecture that integrates high-precision trajectory tracking, vehicle dynamics modeling, and safety-aware decision-making—streamlining the conventional perception-planning-control stack to reduce reliance on extensive track-based verification. Contribution/Results: Deployed on a real racecar with only 11 hours of cumulative on-track testing, the system achieves stable operation at up to 206 km/h and accumulates 325 km of high-speed laps. Experimental results demonstrate exceptional trajectory tracking accuracy, strong robustness against dynamic disturbances, and engineering scalability under severe resource constraints. This work establishes a new paradigm for developing high-performance autonomous racecars in settings with limited testing infrastructure and budget.

Technology Category

• Computer Vision: Motion & Tracking
• Planning, Routing, and Scheduling: Model-Based Reasoning
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements

Abstract

Autonomous racing has seen significant advancements, driven by competitions such as the Indy Autonomous Challenge (IAC) and the Abu Dhabi Autonomous Racing League (A2RL). However, developing an autonomous racing stack for a full-scale car is often constrained by limited access to dedicated test tracks, restricting opportunities for real-world validation. While previous work typically requires extended development cycles and significant track time, this paper introduces a minimalistic autonomous racing stack for high-speed time-trial racing that emphasizes rapid deployment and efficient system integration with minimal on-track testing. The proposed stack was validated on real speedways, achieving a top speed of 206 km/h within just 11 hours' practice run on the track with 325 km in total. Additionally, we present the system performance analysis, including tracking accuracy, vehicle dynamics, and safety considerations, offering insights for teams seeking to rapidly develop and deploy an autonomous racing stack with limited track access.

Problem

• Developing autonomous racing systems with limited track access
• Reducing extensive track testing requirements for validation
• Enabling rapid deployment of high-speed autonomous racing stacks

Innovation

• Minimalistic autonomous racing stack for high-speed time-trials
• Emphasizes rapid deployment and efficient system integration
• Validated on real speedways with minimal on-track testing