Traffic Flow Analysis & Simulation Tools 🚦

Table of Contents

1. Project Overview
2. Key Features
3. Project Structure
4. Research Paper
5. License
6. Acknowledgements
7. Diagram of the App
8. Dashboards Overview
   • Data Analysis Dashboard
   • Traffic Simulation Dashboard
9. Installation & Setup
   • Prerequisites
   • General Installation Steps

Project Overview

This repository contains the final degree project for obtaining the title of Software Engineer at the University of Málaga (UMA). The project received honors with a final grade of 9.4.

The goal of this project is to study traffic flow in a specific zone through data extraction, refinement, analysis, and simulation using a multi-tool system. The tools are built using Python with libraries like MESA, DashPlotly, and MongoDB.

Key Features:

• Automatic Data Collection: Extract traffic data from the TomTom API using the Vector Flow Tiles Service to gather real-time and historical traffic information.
• Data Refinement: Clean and process the extracted data, converting it from GeoJSON format into a graph representation of the area. The data is then stored efficiently in MongoDB for further use.
• Data Analysis Dashboard: Visualize historical traffic trends through an interactive dashboard with various filters. The dashboard automatically generates analytical insights and visualizations, with the option to download the results.
• Traffic Simulation Dashboard: Simulate traffic behavior using an Agent-Based Model (ABM) and visualize detailed graphs of the simulation outcomes. The results can also be downloaded for further analysis.

Project Structure

The project is organized into four distinct parts:

1. extract_data
2. refine_data
3. data_dashboard
4. simulator_dashboard

Research Paper

For detailed information about the research and methodologies behind this project, you can find the full paper here.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements

Special thanks to Eduardo Guzmán and Juan Palma for providing guidance.

Feel free to open issues, contribute, or contact me if you have any questions or suggestions.

Diagram of the App

The diagram below outlines the architecture and flow of the application:

Dashboards Overview

This section provides a visual representation of the two dashboards included in the project.

Data Analysis Dashboard

Screenshot of the Data Analysis Dashboard, visualizing historical traffic data.

Traffic Simulation Dashboard

Screenshot of the Traffic Simulation Dashboard, simulating traffic flow using an Agent-Based Model (ABM).

Installation & Setup

Prerequisites:

• Python 3.x
• MongoDB (Running instance)
• Clone this repository:

  git clone https://github.com/JCamacho4/traffic-digital-twin.git
  cd repo_name

General Installation Steps:

Each part of the project is contained in its own folder, with specific installation and setup instructions. Please refer to the README.md file in each directory for detailed steps on how to configure and run that part of the project:

1. 1_extract_data: Instructions for data extraction using the TomTom API.

   • Go to extract data instructions

2. 2_refine_data: Instructions for refining and storing the collected data in MongoDB.

   • Go to refine data instructions

3. 3_data_dashboard: Instructions for running the historical data analysis dashboard.

   • Go to data dashboard instructions

4. 4_simulator_dashboard: Instructions for running the traffic simulation dashboard.

   • Go to simulation dashboard instructions

Before proceeding with each part, ensure you have installed the required Python libraries and filled in the necessary .env files as per the instructions in each respective folder.