Python Backend -- RL-based dispatcher + delay prediction - Node.js Bridge -- WebSocket bridge connecting backend to frontend - React + Konva Frontend -- Real-time simulation, train animations & AI suggestions

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Project Structure

rail/
├── backend/              # Python backend (state manager, websocket server)
│   ├── state_manager.py
│   ├── websocket_server.py
│   └── ...
├── model/                # RL & delay prediction models
│   └── dispatcher2.py
├── frontend/             # React + TypeScript frontend
│   ├── src/
│   │   ├── components/   # Train.tsx, Simulation.tsx, SuggestionsPanel.tsx, etc.
│   │   └── ...
│   └── server.ts         # WebSocket bridge (Node.js)
└── README.md

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Quick Setup

Backend (Python)

Requirements: Python 3.10+, venv

cd backend
python -m venv .venv
source .venv/Scripts/activate  # (or .venv/bin/activate on macOS/Linux)

pip install -r requirements.txt
python websocket_server.py

This will start the backend WebSocket server on ws://localhost:8765.

Bridge (Node.js)

Requirements: Node.js 18+, npm

cd frontend
npm install
npm run server

This runs the WebSocket bridge on ws://localhost:3001 that relays data between Python backend & frontend.

Frontend (React + Vite)

In a second terminal:

cd frontend
npm run dev

This starts the React app on http://localhost:5173.

Demo Flow

1. Start backend (python websocket_server.py)
2. Start bridge (npm run server)
3. Start frontend (npm run dev)
4. Open http://localhost:5173 and watch trains + suggestions update live.

Current Features

✅ Real-time train simulation (React-Konva)
✅ RL-based delay mitigation model (PPO)
✅ WebSocket bridge for backend-frontend sync
✅ AI suggestions panel (accept/reject actions)
✅ Modular architecture -- ready for further UI polish

Next Steps (For Frontend )

• Polish train animation curves & speed scaling
• Add signal color transitions (red → green)
• Improve UI/UX for suggestions panel (click-to-apply)
• Visualize metrics dashboard (on-time %, conflicts prevented)

Contributing

Focus areas: - Better visualization of track network More intuitive UI/UX for train interactions Styling & theming

Demo Tips

When demoing: - Keep backend + bridge + frontend running simultaneously. - Open browser console to show incoming WS data (state_update & suggestions). - Highlight AI suggestions being applied live.