Hybrid ML-Physics Sim for F1 Strategies
π‘Open-source hybrid physics-ML sim nails F1 strategies via Monte Carlo!
β‘ 30-Second TL;DR
What Changed
Deterministic baseline simulator handles tyre deg, fuel, DRS, traffic
Why It Matters
This hybrid approach demonstrates scalable ML augmentation of physics sims, useful for sports analytics and beyond. Open-source nature enables practitioners to adapt for other simulation domains.
What To Do Next
Clone the GitHub repo and train your own residual model on FastF1 data.
Key Points
- β’Deterministic baseline simulator handles tyre deg, fuel, DRS, traffic
- β’LightGBM residual corrects pace deltas from FastF1 telemetry
- β’10k Monte Carlo sims yield P10/P50/P90 distributions per driver
- β’Safety car classifier modulates SC probability per lap
- β’Strategy optimizer at 400 iterations for fast web responses
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Original source: Reddit r/MachineLearning β
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