RaceAI - Live Race Strategy & Telemetry Assistant

Make race decisions faster than human engineers - pit at the perfect lap, optimize pace, and win with AI-powered race strategy.

Comment

Inspiration

Modern racing relies heavily on strategy — timing the pit stop, analyzing tire wear, and reacting to changing pace can be the difference between winning and finishing mid-pack. We built RaceAI to bridge the gap, giving anyone access to real-time strategy intelligence powered by AI and telemetry analytics.

What it does

RaceAI analyzes real race data and provides:

  • Optimal pit window prediction
  • Lap time trend analysis
  • Finish position prediction (ML)
  • Real-time strategy dashboard
  • Telemetry alerts (fuel, tires, brakes)
  • AI-generated pit calls
  • Monte-Carlo simulation for decision confidence
  • Exportable PDF race reports

How we built it

We integrated multiple components:

  • Python + Streamlit: Real-time dashboard UI
  • Scikit-Learn (Regression Model): Predict finish position
  • NumPy + Pandas: Data preprocessing and lap/telemetry analysis
  • Matplotlib: Data visualizations (lap charts, simulations)
  • ReportLab: Automated PDF race reports
  • Text-To-Speech (pyttsx3): Realistic AI pit radio calls

Challenges we ran into

  • Cleaning telemetry data from uneven formats
  • Automatically detecting column mappings from different race logs
  • Handling real-time simulation refresh while keeping UI responsive
  • Deploying the app and ensuring package compatibility

Accomplishments that we're proud of

We're proud of building a tool that democratizes access to data-driven strategy, empowering sim racers and smaller teams.

What we learned

We gained experience in:

  • Real-time data visualization
  • Machine learning feature engineering
  • Building interactive AI-powered dashboards
  • Combining racing domain knowledge with data science
  • Handling deployment workflows and packaging apps

What's next for RaceAI - Live Race Strategy & Telemetry Assistant

Future features include:

  • GPS racing line analysis
  • Reinforcement learning strategy model
  • Cloud-connected live motorsport mode
  • Driver fatigue detection
  • Support for F1-style multi-driver teams

Built With

Share this project:

Updates