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