TRACK: Telemetry-Based Racing Analysis and Coaching Kit in Sim Racing Games

Key points

• We report this framework together with its limitations: we calibrate each clustering result against a null, and when one does not separate from chance, we say so.1
• Instead of restricting ourselves to scoring drivers or sorting them into preset labels, we represent each recording session as a compact geometry in a four-dimensional behavioral space (speed, braking, strategy, and consistency), and we group these fingerprints by their similarity using unsupervised clustering.1
• It is also not clear whether a driver's grouping carries over from one corner type to the next.1
• We also normalize each metric against a reinforcement-learning reference agent.1

Sources (1)

• [1]TRACK: Telemetry-Based Racing Analysis and Coaching Kit in Sim Racing Games
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 01:29 PM

  This paper presents TRACK (Telemetry-Based Racing Analysis and Coaching Kit), which is a framework for analyzing driving performance in sim racing and profiling how individual drivers behave behind the wheel.

  We report this framework together with its limitations: we calibrate each clustering result against a null, and when one does not separate from chance, we say so.

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