Formula One Track Optimization & Analysis

FOTOA is an interactive F1 lap-time simulator. You can draw a custom circuit or select a real F1 track from FastF1 telemetry, then compute a theoretical minimum lap time with segment-level telemetry data, actionable insights, and heatmap overlays.

• Node.js 18+
• Python 3.10+

cd backend

# optional but recommended
python -m venv ..\cqvenv
..\cqvenv\Scripts\activate

pip install fastapi uvicorn numpy pydantic fastf1 python-multipart

uvicorn main:app --reload --host 0.0.0.0 --port 8000

cd frontend
npm install
npm run dev

Optional env file in frontend/.env:

VITE_API_BASE_URL=http://localhost:8000

• Backend health: http://localhost:8000/health
• Frontend dev server: shown by Vite in terminal (default http://localhost:5173)
• I also added widgets in the top right of the webpage indicating front/backend connection status

This was a CodeQuantum submission. This year's theme was Formula One. Applying for the Data Science and General tracks, I wanted to create a novel, technically rigorous solution. I specifically honed in on F1 lap performance. There is so much data behind the sport, but also so much math behind making predictions. Each track and lap is a combination of track geometry, vehicle limits, and driver control transitions (accelerate/coast/brake). FOTOA was built to make those tradeoffs visual, interactive, and easy to understand, not just numerical.

• Frontend: React + Vite, canvas-based editor, real-time drag/tug interaction, telemetry cards, and UI controls.
• Backend: Python + FastAPI with /api/track routes for solve/catalog/extract.
• Track data: FastF1 session telemetry for real circuits, cached on disk for faster repeat loads.
• Solver core:
  • Track preprocessing, resampling, and smoothing
  • Curvature-based cornering speed limits
  • Forward acceleration pass + backward braking pass
  • Segment-time integration + heatmap/control profile generation

• FastF1 cold loads were SUPER slow; I solved it by caching data and pre-warming.
• Mapping telemetry-derived segments to smooth canvas rendering without visual misalignment.
• Balancing solver realism vs optimism through parameter calibration (I was overly optimistic).
• Keeping drag/tug interaction smooth while preserving valid non-self-intersecting loops (for every kind of user ;) ).

• Built a full end-to-end loop: select/draw track → solve → heatmap → telemetry.
• Added real-track ingestion from FastF1 instead of static/demo geometry.
• Worked with data and topics in a field I was not previously familiar with
• Implemented runtime UX polish: notifications, annotations, and persistent telemetry summaries.
• Calibrated solver constants to produce more plausible lap-time estimates.

• Telemetry preprocessing quality strongly affects solver quality.
• A fast-feeling product needs a cache strategy as much as an algorithm strategy.
• Canvas interaction design (draw/drag/hover states) is key for trust and usability.
• Physics-inspired constraints need practical calibration against known laps.

• Per-track calibration profiles (circuit-specific realism tuning).
• Expose solver realism presets in the UI.
• Add export/import of custom tracks and solver runs.
• Improve annotation set (e.g., longest full-throttle section, max braking zone).
• Even though I solved the loading and caching problem with the FastF1 data, I would like to make it more robust.

Input: normalized points, canvas size, closed loop flag, track scale in miles.

Returns:

• minTimeSeconds
• segments[] with from, to, speed, acceleration, curvature, lateralG, heat, phase, seconds

Returns available real F1 tracks generated from FastF1 event schedules.

Input:

{ "trackId": "2025_r19_race" }

Returns:

• normalized points[]
• trackLengthMiles (when available)

CQ_hacks/
├── README.md
├── README_Template.md
├── .gitignore
├── backend/
│   ├── main.py
│   ├── api/
│   │   ├── solve_track.py
│   │   └── extract_track.py
│   ├── solver/
│   │   ├── types.py
│   │   ├── utils.py
│   │   ├── forward_pass.py
│   │   ├── backward_pass.py
│   │   └── optimizer.py
│   ├── .fastf1_cache/
│   └── .track_points_cache/
└── frontend/
    ├── index.html
    ├── package.json
    ├── src/
    │   ├── App.jsx
    │   ├── main.jsx
    │   ├── styles.css
    │   ├── components/
    │   └── utils/
    └── dist/   # generated by npm run build