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🚦 OpenEnv – Smart Traffic AI Simulator

πŸ“Œ Problem

Urban areas face traffic congestion and delayed emergency response. There is no intelligent system that dynamically optimizes traffic in real time.

πŸ’‘ Solution

We built an OpenEnv-based simulation where an AI agent learns to manage traffic and prioritize emergency vehicles using a step-based environment.

βš™οΈ Environment API

  • reset() β†’ initializes environment
  • step(action) β†’ returns (state, reward, done, info)
  • state() β†’ current state

πŸ€– Agent

A rule-based intelligent agent that:

  • Prioritizes ambulance movement πŸš‘
  • Optimizes traffic flow 🚦

πŸ“Š Results

Smart Agent vs Random Agent:

  • Random Score: -496
  • Smart Score: -117 πŸ‘‰ Significant improvement observed

πŸ› οΈ Tech Stack

  • Python
  • Gradio
  • OpenEnv concepts

πŸš€ Future Scope

  • Multi-signal system
  • Real-time traffic data integration
  • Reinforcement learning model
  • Multiple Emergency vehicles (Firetrucks,police vehicles,etc)
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