Smart-Ambulance-Navigation-System

The Smart Ambulance Navigation System is an intelligent simulation designed to optimize ambulance routing by minimizing travel time and avoiding traffic congestion. It uses real-time traffic data, dynamic rerouting algorithms, and traffic light control to ensure ambulances reach destinations as fast as possible.

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Features

• Real-time ambulance rerouting based on traffic conditions
• Traffic congestion detection and avoidance
• Traffic light preemption for ambulances
• Dynamic selection of destination points
• Supports multiple routing algorithms:
  • Dijkstra's Algorithm
  • A* Search
  • Bellman-Ford (BHK variant)
  • A* with Bee Colony Optimization (A* + BCO)

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Technologies Used

• Python (Core simulation)
• SUMO (Simulation of Urban Mobility)
• TraCI (Traffic Control Interface)
• NetworkX (Graph processing)
• Matplotlib (Data visualization)

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Installation

1. Install SUMO and ensure it is added to your system PATH.
2. Install Python dependencies:

pip install networkx matplotlib

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How to Run

1. Configure your SUMO environment with your .sumocfg file.
2. Update the ambulance settings in the script:

SUMO_CONFIG_FILE = "your_network.sumocfg"
AMBULANCE_ID = "ambulance_trip"
DEST_EDGE = "destination_edge_id"

3. Run the simulation:

python your_script.py

4. Output graphs and a metrics CSV will be generated automatically.

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Output Files

• metrics.csv - Stores time, speed, distance, and traffic volume data
• speed_vs_time.png - Graph of Ambulance Speed vs Time
• distance_vs_time.png - Graph of Distance Covered vs Time
• vehicles_vs_time.png - Graph of Traffic Volume vs Time

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Project Structure

Smart-Ambulance-Navigation-System/
├── your_script.py
├── metrics.csv
├── speed_vs_time.png
├── distance_vs_time.png
├── vehicles_vs_time.png
└── README.md

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Future Improvements

• Integrate real-time traffic API data (Google Maps, OpenStreetMap)
• Multi-ambulance coordination
• Dynamic hospital selection based on availability
• Predictive traffic analysis using machine learning