🏎️ F1 Live Strategy Simulator & Monte Carlo Engine

📌 Overview

An advanced, real-time Formula 1 race strategy simulator that combines a high-performance C++ Monte Carlo Engine with a Python-based live telemetry tracker. This project is designed to predict race outcomes, evaluate tyre degradation, and optimize pit-stop strategies dynamically using live AWS telemetry data.

⚙️ Core Architecture

The system follows a strict decoupling between heavy mathematical computation and live data processing:

1. The C++ Core Engine (/src, /include/f1sim): Handles the mathematical modeling of the race. It features a custom tyre degradation model and a Monte Carlo simulation engine capable of running thousands of race permutations in milliseconds to calculate expected total race times and probabilistic finishing positions.
2. The Python Telemetry Layer (/scripts): Acts as the live data ingestion and visualization layer. It hooks into live telemetry (via AWS/FastF1), handles missing data points (e.g., VSC latency dropouts), and outputs the current race state to live_state.json.
3. Inter-Process Communication: The C++ engine parses the live JSON state (via nlohmann/json), computes the Monte Carlo distributions, and exports the results to CSV files (monte_carlo_results.csv), which are then dynamically plotted by Python using Matplotlib.

🛠️ Key Features

• Live AWS Telemetry Integration: Real-time tracking of lap times, tyre compounds, and driver positions.
• Dynamic Tyre Degradation Model: Calculates performance drop-off based on tyre age and compound (Soft, Medium, Hard).
• Monte Carlo Strategy Optimization: Runs probabilistic distributions to determine the optimal pit lap and predict final race gaps.
• Robust Anomaly Handling: Features a "memory" state in the Python tracker to handle temporary F1 API telemetry dropouts (e.g., during pit entry or Virtual Safety Car periods) without crashing the C++ engine.

📂 Project Structure

f1_strategy_sim/
├── include/f1sim/       # C++ Headers (Car, RaceSession, MonteCarloEngine, TyreModel, etc.)
├── src/                 # C++ Source Files 
├── scripts/             # Python Modules (live_tracker.py, mega_dashboard.py)
├── tests/               # Unit tests for the C++ mathematical models
├── CMakeLists.txt       # Build configuration
└── live_dashboard.bat   # Windows execution script to run the full pipeline

🚀 Build and Run

Prerequisites

• C++17 Compiler (GCC/MSVC) and CMake.
• Python 3.9+ with requirements-live.txt installed.

Build the C++ Engine

mkdir build && cd build
cmake ..
cmake --build . --config Release

Run the Live Dashboard

Execute the batch script to launch both the live tracker and the Monte Carlo visualization dashboard simultaneously:

./live_dashboard.bat

👨‍💻 Author

Sergio Software Engineering & Race Strategy Enthusiast