Car Race Simulation

The Formula E Race Simulator is designed to model and visualize a competitive mobility environment where multiple electric cars race around a virtual 2D circuit. Each car on individual parameters.

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⚡ Formula E Race Simulator (2D Real-Time Mobility System)

🏁 Problem Statement

The Formula E Race Simulator is designed to model and visualize a competitive mobility environment where multiple electric cars race around a virtual 2D circuit. Each car functions as an independent agent, governed by parameters such as speed, acceleration, battery capacity, and energy consumption.

The simulator captures the dynamics of real-world conditions like weather variations and pit stops, while continuously tracking and updating a live leaderboard.

This concept allows observation of how different mobility systems perform under changing environmental and operational conditions, highlighting the significance of energy efficiency, strategy, and adaptability in modern electric mobility ecosystems.

The project serves as a simplified representation of real-time transportation systems, where performance and sustainability must coexist. By incorporating simulation and analysis, it demonstrates how competitive and cooperative behaviors emerge in multi-agent mobility scenarios.

🎯 Core Objectives

1. Simulation of Multiple Agents

  • The system replicates the behavior of several electric cars, each operating autonomously with its own motion parameters.
  • Cars move along the race circuit, accelerating, decelerating, and adapting to environmental and situational changes.

2. Incorporation of Real-World Constraints

  • Models real-life factors such as battery depletion, pit stops for recharging, and weather influences.
  • Weather variations — like rain or wind — affect speed, traction, and energy usage, introducing unpredictability similar to real Formula E conditions.

3. Dynamic Leaderboard Tracking

  • A real-time leaderboard reflects ongoing race standings.
  • Cars are ranked based on laps completed, distance covered, and remaining energy.
  • Provides continuous insights into agent performance and efficiency throughout the simulation.

4. Telemetry and Performance Analytics

  • Captures and presents detailed telemetry data for each car:
    • Speed
    • Battery percentage
    • Distance traveled
    • Lap count
  • Enables analysis of driving strategies, energy management, and overall efficiency under varied conditions.

5. Interactive Visualization and Analysis

  • Beyond simulating motion, the system emphasizes interactive and clear data visualization.
  • Viewers can observe how environmental factors and car strategies influence performance over time.
  • Acts as both an analytical and educational tool for understanding competitive mobility systems.

🚀 Features

  • Real-time 2D race environment
  • Autonomous multi-agent car simulation
  • Dynamic leaderboard and live updates
  • Weather and pit stop modeling
  • Battery management and telemetry analytics
  • Educational visualization of energy efficiency and performance trade-offs

🧩 Future Enhancements

  • 3D visualization using Unity or Unreal Engine
  • Integration with real-time data sources (weather APIs)
  • Machine learning-based race strategy optimization
  • Multiplayer or competitive AI mode

📦 Installation & Usage

# Clone the repository
git clone https://github.com/lak7/formula-e-race-simulator.git

# Navigate to project folder
cd formula-e-race-simulator

# Install dependencies
pip install -r requirements.txt

# Run the simulator
python main.py

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