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Traditional traffic light systems struggle with real-time adaptation. This project proposes a scalable, intelligent alternative by using reinforcement learning to control signal phases based on real-time traffic conditions.\n\n---\n\n## 🪀 Key Features\n- Intelligent traffic light control using Deep Q-Learning (DQL)\n- SUMO-based simulation environment\n- Emergency vehicle prioritization\n- Real-time traffic flow optimization\n- Comparison with traditional Q-Learning\n\n---\n\n## 🔄 Algorithms Used\n- **Q-Learning**: For simple environments with reduced state spaces\n- **Deep Q-Networks (DQN)**: For complex, dynamic traffic scenarios\n\n---\n\n## 💡 Technologies \u0026 Tools\n- Python\n- SUMO (Simulation of Urban Mobility)\n- TraCI (Traffic Control Interface)\n- TensorFlow / Keras\n- NumPy, Matplotlib\n\n---\n\n## 📈 Results Summary\n| Model              | Reward   | Vehicles Waiting | Avg Speed (m/s) | Avg Wait Time (s) |\n|--------------------|----------|------------------|------------------|--------------------|\n| Baseline Simulation | -15255.36 | 405              | 4.2              | 3493.33            |\n| Q-Learning         | -2327.62 | 5                | 4.6              | 79.22              |\n| Deep Q-Learning    | 2774.90  | 0                | 6.5              | 15.66              |\n\n---\n\n## 🌐 How to Run\n```bash\n# Step 1: Install dependencies\npip install -r requirements.txt\n\n# Step 2: Run environment simulation\npython RL_env.py\n\n# or use Jupyter Notebooks for step-by-step walkthrough\njupyter notebook dql-simulation-1.ipynb\n```\n\n---\n\n## 🚀 Future Enhancements\n- Train on larger datasets like Kinetics or real-world city data\n- Optimize the model for real-time, on-device deployment\n- Deploy as a web application for live simulations and demos\n\n---\n\n## 🤝 Contributors\n- Aryan Patil ([GitHub](https://github.com/aryanator))\n- Harsh Anilkumar Ramani\n- Saiteja Kalam\n- Chandra Mourya\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharshramani00%2Ftrafficsignaloptimizationforsmartcitiesusingdeep-reinforcementlearning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fharshramani00%2Ftrafficsignaloptimizationforsmartcitiesusingdeep-reinforcementlearning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharshramani00%2Ftrafficsignaloptimizationforsmartcitiesusingdeep-reinforcementlearning/lists"}