🚦 OpenEnv – Smart Traffic AI Simulator
📌 Problem
Urban areas face traffic congestion and delayed emergency response. There is no intelligent system that dynamically optimizes traffic in real time.
💡 Solution
We built an OpenEnv-based simulation where an AI agent learns to manage traffic and prioritize emergency vehicles using a step-based environment.
⚙️ Environment API
reset() → initializes environmentstep(action) → returns (state, reward, done, info)state() → current state
🤖 Agent
A rule-based intelligent agent that:
- Prioritizes ambulance movement 🚑
- Optimizes traffic flow 🚦
📊 Results
Smart Agent vs Random Agent:
- Random Score: -496
- Smart Score: -117
👉 Significant improvement observed
🛠️ Tech Stack
- Python
- Gradio
- OpenEnv concepts
🚀 Future Scope
- Multi-signal system
- Real-time traffic data integration
- Reinforcement learning model
- Multiple Emergency vehicles (Firetrucks,police vehicles,etc)
